From 1fa21cea48f5425b4abb01715e0780741e7b9c17 Mon Sep 17 00:00:00 2001
From: Jon Gauthier <jon@gauthiers.net>
Date: Wed, 27 May 2020 13:22:29 -0400
Subject: [PATCH 1/8] [ci skip] remove unused ngram spec binary

---
 models/ngram/bin/spec | 15 ---------------
 1 file changed, 15 deletions(-)
 delete mode 100755 models/ngram/bin/spec

diff --git a/models/ngram/bin/spec b/models/ngram/bin/spec
deleted file mode 100755
index 4b17e39..0000000
--- a/models/ngram/bin/spec
+++ /dev/null
@@ -1,15 +0,0 @@
-#!/usr/bin/env python3
-
-import json
-import sys
-
-with open("/opt/spec.json", "r") as spec_f:
-    spec = json.load(spec_f)
-
-with open("/opt/vocab.txt", "r") as f:
-    vocab = set(l.strip() for l in f)
-
-# Insert vocabulary information.
-spec["vocabulary"]["items"] = spec["vocabulary"]["unk_types"] + list(vocab)
-
-json.dump(spec, sys.stdout)

From acb78b6fb5af979f45d49ec123a7e91232ae64bc Mon Sep 17 00:00:00 2001
From: Jon Gauthier <jon@gauthiers.net>
Date: Wed, 27 May 2020 13:43:10 -0400
Subject: [PATCH 2/8] ngram: support checkpoint mounting

---
 models/ngram/Dockerfile         | 12 +++++++++---
 models/ngram/bin/get_surprisals |  2 +-
 models/ngram/bin/tokenize       | 10 +++++++---
 models/ngram/spec.template.json |  2 +-
 4 files changed, 18 insertions(+), 8 deletions(-)

diff --git a/models/ngram/Dockerfile b/models/ngram/Dockerfile
index 489ebfe..f0d97e8 100644
--- a/models/ngram/Dockerfile
+++ b/models/ngram/Dockerfile
@@ -9,7 +9,9 @@ RUN mkdir ${HOME}/.ssh && echo "StrictHostKeyChecking no" >> ${HOME}/.ssh/config
       && chmod 600 ${HOME}/.ssh/id_rsa
 RUN mkdir -p /opt/srilm \
         && scp -To "StrictHostKeyChecking=no" \
-        cpl@syntaxgym.org:/home/cpl/srilm/{srilm-1.7.2.tar.gz,wiki_kn_5gram.lm} /opt/srilm
+            cpl@syntaxgym.org:/home/cpl/srilm/{srilm-1.7.2.tar.gz,wiki_kn_5gram.lm} /opt/srilm \
+        && mkdir /opt/srilm/checkpoint \
+        && mv /opt/srilm/wiki_kn_5gram.lm /opt/srilm/checkpoint/model.lm
 RUN rm -rf ${HOME}/.ssh
 
 RUN cd /opt/srilm && tar -xvzf srilm-1.7.2.tar.gz && \
@@ -35,11 +37,15 @@ RUN conda install -qy --freeze-installed numpy nomkl \
         && pip install nose jsonschema
 COPY test.py /opt/test.py
 
-COPY ${MODEL_ROOT}/vocab.txt /opt/vocab.txt
+ENV LMZOO_CHECKPOINT_PATH /opt/srilm/checkpoint
+ENV LMZOO_VOCABULARY_PATH vocab
+
+COPY ${MODEL_ROOT}/vocab.txt "$LMZOO_CHECKPOINT_PATH/$LMZOO_VOCABULARY_PATH"
 COPY ${MODEL_ROOT}/get_surprisals.awk /opt/get_surprisals.awk
 COPY ${MODEL_ROOT}/tokenizer /opt/tokenizer
 COPY ${MODEL_ROOT}/bin /opt/bin
 COPY shared/unkify /opt/bin/unkify
+COPY shared/spec /opt/bin/spec
 COPY shared/unsupported /opt/bin/get_predictions.hdf5
 
 ENV PATH "/opt/bin:${PATH}"
@@ -54,4 +60,4 @@ ARG FILES_SHA1
 COPY ${MODEL_ROOT}/spec.template.json /tmp/spec.template.json
 RUN BUILD_DATETIME="$(date)" cat /tmp/spec.template.json | \
             sed "s/<image\.sha1>/$COMMIT/g; s/<image\.files_sha1>/${FILES_SHA1}/g; s/<image\.datetime>/${BUILD_DATETIME}/g" \
-            > /opt/spec.json
+            > /opt/spec.template.json
diff --git a/models/ngram/bin/get_surprisals b/models/ngram/bin/get_surprisals
index 2891031..f2a4c3f 100755
--- a/models/ngram/bin/get_surprisals
+++ b/models/ngram/bin/get_surprisals
@@ -1,6 +1,6 @@
 #!/usr/bin/env bash
 
 tokenize "$1" > /tmp/input_tokenized
-/opt/srilm/bin/i686-m64/ngram -lm /opt/srilm/wiki_kn_5gram.lm \
+/opt/srilm/bin/i686-m64/ngram -lm "${LMZOO_CHECKPOINT_PATH}/model.lm" \
         -ppl /tmp/input_tokenized -debug 2 -order 5 \
         | gawk -f /opt/get_surprisals.awk
diff --git a/models/ngram/bin/tokenize b/models/ngram/bin/tokenize
index dc4492f..dc693e9 100755
--- a/models/ngram/bin/tokenize
+++ b/models/ngram/bin/tokenize
@@ -1,11 +1,15 @@
 #!/usr/bin/env python3
 
-with open("/opt/vocab.txt", "r") as f:
-    vocab = set(l.strip() for l in f)
-
+import os
+from pathlib import Path
 import subprocess
 import sys
 
+checkpoint_path = Path(os.environ["LMZOO_CHECKPOINT_PATH"])
+vocab_path = checkpoint_path / Path(os.environ["LMZOO_VOCABULARY_PATH"])
+with vocab_path.open("r", encoding="utf-8") as f:
+    vocab = set([line.strip() for line in f])
+
 tokenized = subprocess.check_output(["tokenize_inner", sys.argv[1]]).decode("utf-8").strip()
 for line in tokenized.strip().split("\n"):
     unks = [token if token in vocab else "<unk>" for token in line.strip(" ").split(" ")]
diff --git a/models/ngram/spec.template.json b/models/ngram/spec.template.json
index 8f85d19..f328fc5 100644
--- a/models/ngram/spec.template.json
+++ b/models/ngram/spec.template.json
@@ -12,7 +12,7 @@
             "unkify": true,
             "get_surprisals": true,
             "get_predictions": false,
-            "mount_checkpoint": false
+            "mount_checkpoint": true
         },
         "gpu": {
             "required": false,

From 4ffacab18b24a478c68efda7bc44fa1448400676 Mon Sep 17 00:00:00 2001
From: Jon Gauthier <jon@gauthiers.net>
Date: Wed, 27 May 2020 17:39:47 -0400
Subject: [PATCH 3/8] ordered-neurons: do not redundantly lowercase token. also
 update registry.

---
 docs/registry.json                       | 28 ++++++++++++------------
 models/ordered-neurons/get_surprisals.py |  2 +-
 2 files changed, 15 insertions(+), 15 deletions(-)

diff --git a/docs/registry.json b/docs/registry.json
index 659a2dd..ac35f44 100644
--- a/docs/registry.json
+++ b/docs/registry.json
@@ -92,9 +92,9 @@
     "ref_url": "http://www.speech.sri.com/projects/srilm",
     "image": {
       "maintainer": "jon@gauthiers.net",
-      "version": "ca867981a9bd1ac987447ab6f77e0850236f604d",
-      "checksum": "7cdb266af3d7c0cd55b3358673e32182b20a07bf",
-      "datetime": "2020-05-25T17:41:24.168534461Z",
+      "version": "960a916a6a5425499035735db661c894b3a43ab7",
+      "checksum": "17d96e641074fdcebf932c6c8765c4faf0d4fa37",
+      "datetime": "2020-05-27T17:42:33.609856965Z",
       "supported_features": {
         "tokenize": true,
         "unkify": true,
@@ -109,7 +109,7 @@
       "registry": "docker.io",
       "name": "cpllab/language-models",
       "tag": "ngram",
-      "size": 880207473
+      "size": 880261703
     },
     "tokenizer": {
       "type": "word",
@@ -121,9 +121,9 @@
     "ref_url": "https://github.com/yikangshen/Ordered-Neurons",
     "image": {
       "maintainer": "jon@gauthiers.net",
-      "version": "ca867981a9bd1ac987447ab6f77e0850236f604d",
-      "checksum": "f302550ef5bd6f45c6adbbd98eefc56db7f0dd73",
-      "datetime": "2020-05-25T17:43:02.573233114Z",
+      "version": "7c51f5f336c85addad5fc0cef4b5466bc86a2f2a",
+      "checksum": "4993e00d6b31f7493cfe6fa9867ef4eedf44af60",
+      "datetime": "2020-05-27T21:38:33.515783684Z",
       "supported_features": {
         "tokenize": true,
         "unkify": true,
@@ -138,7 +138,7 @@
       "registry": "docker.io",
       "name": "cpllab/language-models",
       "tag": "ordered-neurons",
-      "size": 3218739014
+      "size": 3218739006
     },
     "tokenizer": {
       "type": "word",
@@ -179,9 +179,9 @@
     "ref_url": "https://github.com/cpllab/tinylstm",
     "image": {
       "maintainer": "jon@gauthiers.net",
-      "version": "75a97862cbbade0574d9a03ddd60103b7fe07363",
-      "checksum": "ac57eb3c8b19985978b61df9415e3a95be6ae7b4",
-      "datetime": "2020-05-26T18:32:16.22094886Z",
+      "version": "9d8db666f1fe9fa22cbd37ab6eff7c15a0fb6a8a",
+      "checksum": "344a20e0e67a8ee39c38e34ae1a015f2eb8e99d3",
+      "datetime": "2020-05-26T18:39:22.988852042Z",
       "supported_features": {
         "tokenize": true,
         "unkify": true,
@@ -191,12 +191,12 @@
       },
       "gpu": {
         "required": false,
-        "supported": false
+        "supported": true
       },
       "registry": "docker.io",
       "name": "cpllab/language-models",
       "tag": "tinylstm",
-      "size": 3295284385
+      "size": 3295284357
     },
     "tokenizer": {
       "type": "word",
@@ -204,4 +204,4 @@
     },
     "shortname": "tinylstm"
   }
-}
+}
\ No newline at end of file
diff --git a/models/ordered-neurons/get_surprisals.py b/models/ordered-neurons/get_surprisals.py
index e91d298..757a5dd 100644
--- a/models/ordered-neurons/get_surprisals.py
+++ b/models/ordered-neurons/get_surprisals.py
@@ -68,7 +68,7 @@ def get_surprisals(sentences, corpus, outf, seed):
         data_source = torch.LongTensor(len(sentence))
         for j, token in enumerate(sentence):
             try:
-                data_source[j] = corpus.dictionary.word2idx[token.lower()]
+                data_source[j] = corpus.dictionary.word2idx[token]
             except KeyError:
                 raise RuntimeError("Internal error: Dictionary lookup failed. This should not happen with properly unked inputs.")
 

From ff221826d027a94bcc60c207c676c96f10cc8dd1 Mon Sep 17 00:00:00 2001
From: Jon Gauthier <jon@gauthiers.net>
Date: Thu, 28 May 2020 13:13:35 -0400
Subject: [PATCH 4/8] Singularity backend: include GPU libraries if available

---
 lm_zoo/backends/singularity.py | 22 +++++++++++++++++++---
 1 file changed, 19 insertions(+), 3 deletions(-)

diff --git a/lm_zoo/backends/singularity.py b/lm_zoo/backends/singularity.py
index 8e3613c..68a51e8 100644
--- a/lm_zoo/backends/singularity.py
+++ b/lm_zoo/backends/singularity.py
@@ -2,7 +2,8 @@
 import logging
 import os
 from pathlib import Path
-from subprocess import CalledProcessError
+import shutil
+from subprocess import CalledProcessError, check_output
 import sys
 from tempfile import NamedTemporaryFile
 from typing import cast
@@ -49,6 +50,20 @@ def modified_environ(*remove, **update):
         [env.pop(k) for k in remove_after]
 
 
+def is_cuda_available():
+    """
+    Hacky method to check whether CUDA is available for use on this host.
+    """
+    if shutil.which("nvidia-smi") is None:
+        return False
+    try:
+        output = check_output(["nvidia-smi", "-L"])
+        has_gpus = bool(output.strip())
+        return has_gpus
+    except CalledProcessError:
+        return False
+
+
 class SingularityBackend(Backend):
 
     @classmethod
@@ -100,7 +115,8 @@ def run_command(self, model: Model, command_str,
         binds = ["%s:%s:%s" % (host, guest, mode)
                 for host, guest, mode in mounts]
 
-        nv = False # TODO
+        # TODO make configurable
+        nv = is_cuda_available()
 
         command = command_str.split(" ")
 
@@ -122,7 +138,7 @@ def run_command(self, model: Model, command_str,
         try:
             with modified_environ(**environment):
                 result = Client.execute(image=model.reference, command=command,
-                                        bind=binds, stream=True)
+                                        nv=nv, bind=binds, stream=True)
 
                 for line in result:
                     stdout.write(line)

From d1edc4813c3e44b17bdfbbe775ecf5df08a30c26 Mon Sep 17 00:00:00 2001
From: Jon Gauthier <jon@gauthiers.net>
Date: Mon, 8 Jun 2020 15:00:43 -0400
Subject: [PATCH 5/8] singularity backend: Force --containall. There were some
 concurrent container issues on OM where stdout was getting mixed up between
 containers ..

---
 lm_zoo/backends/singularity.py | 9 ++++++++-
 1 file changed, 8 insertions(+), 1 deletion(-)

diff --git a/lm_zoo/backends/singularity.py b/lm_zoo/backends/singularity.py
index 68a51e8..e4eb82f 100644
--- a/lm_zoo/backends/singularity.py
+++ b/lm_zoo/backends/singularity.py
@@ -137,8 +137,15 @@ def run_command(self, model: Model, command_str,
 
         try:
             with modified_environ(**environment):
+                exec_options = []
+
+                # Maximally isolate container from host -- this resolves some
+                # parallel execution issues we've observed in the past.
+                exec_options.append("--containall")
+
                 result = Client.execute(image=model.reference, command=command,
-                                        nv=nv, bind=binds, stream=True)
+                                        nv=nv, bind=binds, stream=True,
+                                        options=exec_options)
 
                 for line in result:
                     stdout.write(line)

From 17e6195dfd6a7a0f84a40540ffcf5f4a58609629 Mon Sep 17 00:00:00 2001
From: Jon Gauthier <jon@gauthiers.net>
Date: Wed, 1 Jul 2020 16:18:04 -0400
Subject: [PATCH 6/8] dynamic model table from registry JSON

---
 docs/_sources/models.rst.txt | 111 ++++++++++++++++++++++------
 docs/models.html             | 136 +++++++++++++++++++++--------------
 docs/models.rst              | 111 ++++++++++++++++++++++------
 docs/searchindex.js          |   2 +-
 4 files changed, 263 insertions(+), 97 deletions(-)

diff --git a/docs/_sources/models.rst.txt b/docs/_sources/models.rst.txt
index a51d9fd..46fb542 100644
--- a/docs/_sources/models.rst.txt
+++ b/docs/_sources/models.rst.txt
@@ -4,27 +4,94 @@ Official models
 LM Zoo ships with a set of official models that can be queried via the
 command-line tool.
 
+If you reference any of the model names mentioned here, LM Zoo will
+automatically download the relevant image from our public registry. For
+example, to get token-level predictions from the ``tinylstm`` model on a file
+``my_file.txt``::
+
+  $ lm-zoo get-predictions tinylstm my_file.text out.hdf5
+
+Note that not all models support all LM Zoo features. Check the final columns
+of the table to see if the features you need are supported in each model.
+
+
+
 Do you develop language models? please see our instructions on :ref:`contributing`.
 
-Model list
-^^^^^^^^^^^
-
-+------------------------+---------------------------------+---------------------------------------------------+
-| Model name             | Reference                       | Paper                                             |
-+========================+=================================+===================================================+
-| GPT-2-XL               | Radford et al. (2019)           | https://openai.com/blog/better-language-models/   |
-+------------------------+---------------------------------+---------------------------------------------------+
-| GPT-2                  | Radford et al. (2019)           | https://openai.com/blog/better-language-models/   |
-+------------------------+---------------------------------+---------------------------------------------------+
-| Transformer-XL         | Dai et al. (2019)               | https://www.aclweb.org/anthology/P19-1285/        |
-+------------------------+---------------------------------+---------------------------------------------------+
-| JRNN                   | Josefowicz et al. (2016)        | https://arxiv.org/abs/1602.02410                  |
-+------------------------+---------------------------------+---------------------------------------------------+
-| GRNN                   | Gulordava et al. (2018)         | https://www.aclweb.org/anthology/N18-1108/        |
-+------------------------+---------------------------------+---------------------------------------------------+
-| RNNG                   | Dyer et al. (2016)              | https://arxiv.org/abs/1602.07776                  |
-+------------------------+---------------------------------+---------------------------------------------------+
-| LSTM                   | Hochreiter & Schmidhuber (1997) | https://dl.acm.org/doi/10.1162/neco.1997.9.8.1735 |
-+------------------------+---------------------------------+---------------------------------------------------+
-| Ordered-Neurons        | Shen et al. (2019)              | https://openreview.net/forum?id=B1l6qiR5F7        |
-+------------------------+---------------------------------+---------------------------------------------------+
+
+.. raw:: html
+
+   <script type="text/javascript">
+      var registry_url = "https://cpllab.github.io/lm-zoo/registry.json";
+
+      var all_features = {
+         "tokenize": "<tt>tokenize</tt>",
+         "unkify": "<tt>unkify</tt>",
+         "get_surprisals": "<tt>get-surprisals</tt>",
+         "get_predictions": "<tt>get-predictions</tt>",
+         "mount_checkpoint": "Checkpoint mounting",
+      }
+
+      $(function(){
+
+      // Update feature list
+      var all_features_list = Object.keys(all_features);
+      $("#registry-feature-header").attr("colspan", all_features_list.length);
+      var registry_feature_list_htmls = $.map(all_features_list, function(name) {
+         var pretty_name = all_features[name];
+         return "<th id='feature-" + name + "' scope='col'>" + pretty_name + "</th>";
+      })
+      $("#registry-feature-list").html(registry_feature_list_htmls.join(""));
+
+      $.getJSON(registry_url, function(data) {
+         var items = $.map(data, function(registry_item, id) {
+            var reference_link = "<a href='" + registry_item["ref_url"] + "'>Link</a>";
+
+            var size_str;
+            var size = registry_item["image"]["size"] / 1024;
+            var next_size = size / 1024;
+            var labels = ["KB", "MB", "GB"];
+            var label_cur = 0;
+            while (next_size > 1024) {
+               size = next_size;
+               next_size = size / 1024;
+               label_cur += 1;
+            }
+            var round = function(x) { return Math.round(x * 100) / 100; }
+            var size_str = label_cur == labels.length - 1 ? round(size) + " " + labels[labels.length - 1]
+                                                          : round(next_size) + " " + labels[label_cur + 1];
+
+            var columns = [id, reference_link, size_str,
+                           new Date(Date.parse(registry_item["image"]["datetime"])).toLocaleDateString()];
+
+            var feature_columns = $.map(all_features_list, function(feature) {
+               var supported = registry_item["image"]["supported_features"][feature];
+               var td_class = supported ? "feature-supported" : "feature-unsupported";
+               var content = supported ? "Yes" : "No";
+               return "<td class='" + td_class + "'>" + content + "</td>";
+            });
+
+            return "<tr><td>" + columns.join("</td><td>") + "</td>" + feature_columns.join("") + "</tr>";
+         });
+         console.log(items.join(""))
+
+         $("#registry-table tbody").html(items.join(""));
+         //$("#registry-table tbody").html($("#registry-table tbody").html() + items.join(""))
+      })});
+   </script>
+
+   <table id="registry-table">
+      <thead>
+         <tr>
+            <th rowspan="2" scope="col">Model name</th>
+            <th rowspan="2" scope="col">Reference</th>
+            <th rowspan="2" scope="col">Size</th>
+            <th rowspan="2" scope="col">Last updated</th>
+            <th id="registry-feature-header" colspan="5" scope="colgroup">Supported features</th>
+         </tr>
+         <tr id="registry-feature-list">
+            <!--<th>1</th><th>2</th><th><tt>3</tt></th><th>4</th><th>5</th>-->
+         </tr>
+      </thead>
+      <tbody></tbody>
+   </table>
diff --git a/docs/models.html b/docs/models.html
index c8abd15..02b18c5 100644
--- a/docs/models.html
+++ b/docs/models.html
@@ -125,7 +125,7 @@
             
               <ul>
                 
-                  <li class="toctree-l2"><a href="#model-list" class="reference internal">Model list</a></li>
+                  <li class="toctree-l2"><a href="#official-models" class="reference internal">Official models</a></li>
                 
               </ul>
             
@@ -197,58 +197,90 @@
 <h1>Official models<a class="headerlink" href="#official-models" title="Permalink to this headline">¶</a></h1>
 <p>LM Zoo ships with a set of official models that can be queried via the
 command-line tool.</p>
-<p>Do you develop language models? please see our instructions on <a class="reference internal" href="contributing.html#contributing"><span class="std std-ref">Contributing to the LM Zoo</span></a>.</p>
-<div class="section" id="model-list">
-<h2>Model list<a class="headerlink" href="#model-list" title="Permalink to this headline">¶</a></h2>
-<table class="docutils align-default">
-<colgroup>
-<col style="width: 22%" />
-<col style="width: 31%" />
-<col style="width: 47%" />
-</colgroup>
-<thead>
-<tr class="row-odd"><th class="head"><p>Model name</p></th>
-<th class="head"><p>Reference</p></th>
-<th class="head"><p>Paper</p></th>
-</tr>
-</thead>
-<tbody>
-<tr class="row-even"><td><p>GPT-2-XL</p></td>
-<td><p>Radford et al. (2019)</p></td>
-<td><p><a class="reference external" href="https://openai.com/blog/better-language-models/">https://openai.com/blog/better-language-models/</a></p></td>
-</tr>
-<tr class="row-odd"><td><p>GPT-2</p></td>
-<td><p>Radford et al. (2019)</p></td>
-<td><p><a class="reference external" href="https://openai.com/blog/better-language-models/">https://openai.com/blog/better-language-models/</a></p></td>
-</tr>
-<tr class="row-even"><td><p>Transformer-XL</p></td>
-<td><p>Dai et al. (2019)</p></td>
-<td><p><a class="reference external" href="https://www.aclweb.org/anthology/P19-1285/">https://www.aclweb.org/anthology/P19-1285/</a></p></td>
-</tr>
-<tr class="row-odd"><td><p>JRNN</p></td>
-<td><p>Josefowicz et al. (2016)</p></td>
-<td><p><a class="reference external" href="https://arxiv.org/abs/1602.02410">https://arxiv.org/abs/1602.02410</a></p></td>
-</tr>
-<tr class="row-even"><td><p>GRNN</p></td>
-<td><p>Gulordava et al. (2018)</p></td>
-<td><p><a class="reference external" href="https://www.aclweb.org/anthology/N18-1108/">https://www.aclweb.org/anthology/N18-1108/</a></p></td>
-</tr>
-<tr class="row-odd"><td><p>RNNG</p></td>
-<td><p>Dyer et al. (2016)</p></td>
-<td><p><a class="reference external" href="https://arxiv.org/abs/1602.07776">https://arxiv.org/abs/1602.07776</a></p></td>
-</tr>
-<tr class="row-even"><td><p>LSTM</p></td>
-<td><p>Hochreiter &amp; Schmidhuber (1997)</p></td>
-<td><p><a class="reference external" href="https://dl.acm.org/doi/10.1162/neco.1997.9.8.1735">https://dl.acm.org/doi/10.1162/neco.1997.9.8.1735</a></p></td>
-</tr>
-<tr class="row-odd"><td><p>Ordered-Neurons</p></td>
-<td><p>Shen et al. (2019)</p></td>
-<td><p><a class="reference external" href="https://openreview.net/forum?id=B1l6qiR5F7">https://openreview.net/forum?id=B1l6qiR5F7</a></p></td>
-</tr>
-</tbody>
-</table>
-</div>
+<p>If you reference any of the model names mentioned here, LM Zoo will
+automatically download the relevant image from our public registry. For
+example, to get token-level predictions from the <code class="docutils literal notranslate"><span class="pre">tinylstm</span></code> model on a file
+<code class="docutils literal notranslate"><span class="pre">my_file.txt</span></code>:</p>
+<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>$ lm-zoo get-predictions tinylstm my_file.text out.hdf5
+</pre></div>
 </div>
+<p>Note that not all models support all LM Zoo features. Check the final columns
+of the table to see if the features you need are supported in each model.</p>
+<p>Do you develop language models? please see our instructions on <a class="reference internal" href="contributing.html#contributing"><span class="std std-ref">Contributing to the LM Zoo</span></a>.</p>
+<script type="text/javascript">
+   var registry_url = "https://cpllab.github.io/lm-zoo/registry.json";
+
+   var all_features = {
+      "tokenize": "<tt>tokenize</tt>",
+      "unkify": "<tt>unkify</tt>",
+      "get_surprisals": "<tt>get-surprisals</tt>",
+      "get_predictions": "<tt>get-predictions</tt>",
+      "mount_checkpoint": "Checkpoint mounting",
+   }
+
+   $(function(){
+
+   // Update feature list
+   var all_features_list = Object.keys(all_features);
+   $("#registry-feature-header").attr("colspan", all_features_list.length);
+   var registry_feature_list_htmls = $.map(all_features_list, function(name) {
+      var pretty_name = all_features[name];
+      return "<th id='feature-" + name + "' scope='col'>" + pretty_name + "</th>";
+   })
+   $("#registry-feature-list").html(registry_feature_list_htmls.join(""));
+
+   $.getJSON(registry_url, function(data) {
+      var items = $.map(data, function(registry_item, id) {
+         var reference_link = "<a href='" + registry_item["ref_url"] + "'>Link</a>";
+
+         var size_str;
+         var size = registry_item["image"]["size"] / 1024;
+         var next_size = size / 1024;
+         var labels = ["KB", "MB", "GB"];
+         var label_cur = 0;
+         while (next_size > 1024) {
+            size = next_size;
+            next_size = size / 1024;
+            label_cur += 1;
+         }
+         var round = function(x) { return Math.round(x * 100) / 100; }
+         var size_str = label_cur == labels.length - 1 ? round(size) + " " + labels[labels.length - 1]
+                                                       : round(next_size) + " " + labels[label_cur + 1];
+
+         var columns = [id, reference_link, size_str,
+                        new Date(Date.parse(registry_item["image"]["datetime"])).toLocaleDateString()];
+
+         var feature_columns = $.map(all_features_list, function(feature) {
+            var supported = registry_item["image"]["supported_features"][feature];
+            var td_class = supported ? "feature-supported" : "feature-unsupported";
+            var content = supported ? "Yes" : "No";
+            return "<td class='" + td_class + "'>" + content + "</td>";
+         });
+
+         return "<tr><td>" + columns.join("</td><td>") + "</td>" + feature_columns.join("") + "</tr>";
+      });
+      console.log(items.join(""))
+
+      $("#registry-table tbody").html(items.join(""));
+      //$("#registry-table tbody").html($("#registry-table tbody").html() + items.join(""))
+   })});
+</script>
+
+<table id="registry-table">
+   <thead>
+      <tr>
+         <th rowspan="2" scope="col">Model name</th>
+         <th rowspan="2" scope="col">Reference</th>
+         <th rowspan="2" scope="col">Size</th>
+         <th rowspan="2" scope="col">Last updated</th>
+         <th id="registry-feature-header" colspan="5" scope="colgroup">Supported features</th>
+      </tr>
+      <tr id="registry-feature-list">
+         <!--<th>1</th><th>2</th><th><tt>3</tt></th><th>4</th><th>5</th>-->
+      </tr>
+   </thead>
+   <tbody></tbody>
+</table></div>
 
 
           </div>
diff --git a/docs/models.rst b/docs/models.rst
index a51d9fd..46fb542 100644
--- a/docs/models.rst
+++ b/docs/models.rst
@@ -4,27 +4,94 @@ Official models
 LM Zoo ships with a set of official models that can be queried via the
 command-line tool.
 
+If you reference any of the model names mentioned here, LM Zoo will
+automatically download the relevant image from our public registry. For
+example, to get token-level predictions from the ``tinylstm`` model on a file
+``my_file.txt``::
+
+  $ lm-zoo get-predictions tinylstm my_file.text out.hdf5
+
+Note that not all models support all LM Zoo features. Check the final columns
+of the table to see if the features you need are supported in each model.
+
+
+
 Do you develop language models? please see our instructions on :ref:`contributing`.
 
-Model list
-^^^^^^^^^^^
-
-+------------------------+---------------------------------+---------------------------------------------------+
-| Model name             | Reference                       | Paper                                             |
-+========================+=================================+===================================================+
-| GPT-2-XL               | Radford et al. (2019)           | https://openai.com/blog/better-language-models/   |
-+------------------------+---------------------------------+---------------------------------------------------+
-| GPT-2                  | Radford et al. (2019)           | https://openai.com/blog/better-language-models/   |
-+------------------------+---------------------------------+---------------------------------------------------+
-| Transformer-XL         | Dai et al. (2019)               | https://www.aclweb.org/anthology/P19-1285/        |
-+------------------------+---------------------------------+---------------------------------------------------+
-| JRNN                   | Josefowicz et al. (2016)        | https://arxiv.org/abs/1602.02410                  |
-+------------------------+---------------------------------+---------------------------------------------------+
-| GRNN                   | Gulordava et al. (2018)         | https://www.aclweb.org/anthology/N18-1108/        |
-+------------------------+---------------------------------+---------------------------------------------------+
-| RNNG                   | Dyer et al. (2016)              | https://arxiv.org/abs/1602.07776                  |
-+------------------------+---------------------------------+---------------------------------------------------+
-| LSTM                   | Hochreiter & Schmidhuber (1997) | https://dl.acm.org/doi/10.1162/neco.1997.9.8.1735 |
-+------------------------+---------------------------------+---------------------------------------------------+
-| Ordered-Neurons        | Shen et al. (2019)              | https://openreview.net/forum?id=B1l6qiR5F7        |
-+------------------------+---------------------------------+---------------------------------------------------+
+
+.. raw:: html
+
+   <script type="text/javascript">
+      var registry_url = "https://cpllab.github.io/lm-zoo/registry.json";
+
+      var all_features = {
+         "tokenize": "<tt>tokenize</tt>",
+         "unkify": "<tt>unkify</tt>",
+         "get_surprisals": "<tt>get-surprisals</tt>",
+         "get_predictions": "<tt>get-predictions</tt>",
+         "mount_checkpoint": "Checkpoint mounting",
+      }
+
+      $(function(){
+
+      // Update feature list
+      var all_features_list = Object.keys(all_features);
+      $("#registry-feature-header").attr("colspan", all_features_list.length);
+      var registry_feature_list_htmls = $.map(all_features_list, function(name) {
+         var pretty_name = all_features[name];
+         return "<th id='feature-" + name + "' scope='col'>" + pretty_name + "</th>";
+      })
+      $("#registry-feature-list").html(registry_feature_list_htmls.join(""));
+
+      $.getJSON(registry_url, function(data) {
+         var items = $.map(data, function(registry_item, id) {
+            var reference_link = "<a href='" + registry_item["ref_url"] + "'>Link</a>";
+
+            var size_str;
+            var size = registry_item["image"]["size"] / 1024;
+            var next_size = size / 1024;
+            var labels = ["KB", "MB", "GB"];
+            var label_cur = 0;
+            while (next_size > 1024) {
+               size = next_size;
+               next_size = size / 1024;
+               label_cur += 1;
+            }
+            var round = function(x) { return Math.round(x * 100) / 100; }
+            var size_str = label_cur == labels.length - 1 ? round(size) + " " + labels[labels.length - 1]
+                                                          : round(next_size) + " " + labels[label_cur + 1];
+
+            var columns = [id, reference_link, size_str,
+                           new Date(Date.parse(registry_item["image"]["datetime"])).toLocaleDateString()];
+
+            var feature_columns = $.map(all_features_list, function(feature) {
+               var supported = registry_item["image"]["supported_features"][feature];
+               var td_class = supported ? "feature-supported" : "feature-unsupported";
+               var content = supported ? "Yes" : "No";
+               return "<td class='" + td_class + "'>" + content + "</td>";
+            });
+
+            return "<tr><td>" + columns.join("</td><td>") + "</td>" + feature_columns.join("") + "</tr>";
+         });
+         console.log(items.join(""))
+
+         $("#registry-table tbody").html(items.join(""));
+         //$("#registry-table tbody").html($("#registry-table tbody").html() + items.join(""))
+      })});
+   </script>
+
+   <table id="registry-table">
+      <thead>
+         <tr>
+            <th rowspan="2" scope="col">Model name</th>
+            <th rowspan="2" scope="col">Reference</th>
+            <th rowspan="2" scope="col">Size</th>
+            <th rowspan="2" scope="col">Last updated</th>
+            <th id="registry-feature-header" colspan="5" scope="colgroup">Supported features</th>
+         </tr>
+         <tr id="registry-feature-list">
+            <!--<th>1</th><th>2</th><th><tt>3</tt></th><th>4</th><th>5</th>-->
+         </tr>
+      </thead>
+      <tbody></tbody>
+   </table>
diff --git a/docs/searchindex.js b/docs/searchindex.js
index b029008..c53137f 100644
--- a/docs/searchindex.js
+++ b/docs/searchindex.js
@@ -1 +1 @@
-Search.setIndex({docnames:["commands","contributing","index","model_api","models","python_api","quickstart","support","thanks"],envversion:{"sphinx.domains.c":2,"sphinx.domains.changeset":1,"sphinx.domains.citation":1,"sphinx.domains.cpp":2,"sphinx.domains.index":1,"sphinx.domains.javascript":2,"sphinx.domains.math":2,"sphinx.domains.python":2,"sphinx.domains.rst":2,"sphinx.domains.std":1,sphinx:56},filenames:["commands.rst","contributing.rst","index.rst","model_api.rst","models.rst","python_api.rst","quickstart.rst","support.rst","thanks.rst"],objects:{"":{lm_zoo:[5,0,0,"-"]},"lm-zoo":{"--backend":[0,4,1,"cmdoption-lm-zoo-backend"],"--verbose":[0,4,1,"cmdoption-lm-zoo-v"],"-v":[0,4,1,"cmdoption-lm-zoo-v"]},"lm-zoo-get-predictions":{INFILE:[0,4,1,"cmdoption-lm-zoo-get-predictions-arg-INFILE"],MODEL:[0,4,1,"cmdoption-lm-zoo-get-predictions-arg-MODEL"],OUTFILE:[0,4,1,"cmdoption-lm-zoo-get-predictions-arg-OUTFILE"]},"lm-zoo-get-surprisals":{FILE:[0,4,1,"cmdoption-lm-zoo-get-surprisals-arg-FILE"],MODEL:[0,4,1,"cmdoption-lm-zoo-get-surprisals-arg-MODEL"]},"lm-zoo-list":{"--short":[0,4,1,"cmdoption-lm-zoo-list-short"]},"lm-zoo-tokenize":{FILE:[0,4,1,"cmdoption-lm-zoo-tokenize-arg-FILE"],MODEL:[0,4,1,"cmdoption-lm-zoo-tokenize-arg-MODEL"]},"lm-zoo-unkify":{FILE:[0,4,1,"cmdoption-lm-zoo-unkify-arg-FILE"],MODEL:[0,4,1,"cmdoption-lm-zoo-unkify-arg-MODEL"]},"lm_zoo.backends":{Backend:[5,1,1,""],get_backend:[5,2,1,""],get_compatible_backend:[5,2,1,""]},"lm_zoo.backends.docker":{DockerBackend:[5,1,1,""]},"lm_zoo.backends.singularity":{SingularityBackend:[5,1,1,""]},"lm_zoo.models":{DockerModel:[5,1,1,""],OfficialModel:[5,1,1,""],SingularityModel:[5,1,1,""]},"lm_zoo.models.OfficialModel":{from_dict:[5,3,1,""]},lm_zoo:{backends:[5,0,0,"-"],get_predictions:[5,2,1,""],get_surprisals:[5,2,1,""],models:[5,0,0,"-"],run_model_command:[5,2,1,""],spec:[5,2,1,""],tokenize:[5,2,1,""],unkify:[5,2,1,""]}},objnames:{"0":["py","module","Python 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prefix_typ:3,prepend:3,preprocess:[0,5],pretti:0,probabl:[0,3,5],probe:3,produc:[0,3,5],program:1,progress_stream:5,properti:3,provid:[0,1,2,3],psycholinguist:[2,8],pull:[1,3,5,6],python:6,queri:4,quickstart:2,radford:[],rais:5,raise_error:5,ram:6,rather:0,raw:0,read:1,readi:[2,6],recommend:1,ref_url:3,refer:4,registri:[4,5],reinvent:1,relev:[3,4],reliabl:6,repositori:[0,1,2,5],repres:[0,5],represent:2,request:[1,3,7],requir:[0,3],respond:1,respons:5,result:[0,3],reus:1,review:1,rnng:[3,6],root:1,routin:1,row:[0,3,5],run:[0,1,3,5,6],run_model_command:5,same:3,samsa:[2,6],schmidhub:[],script:3,section:[2,6],see:[1,2,3,4,6],seem:[2,6],sent:0,sentenc:[0,3,5],sentence_id:[0,2,3,5,6],sentinel_pattern:3,sentinel_posit:3,separ:[0,3],sequenc:[0,3,5],set:[1,3,4],sever:1,share:3,shell:5,shen:[],ship:4,shortnam:0,should:[0,1,3,5],simpli:3,singl:0,singular:[0,5],singularitybackend:5,singularitymodel:5,size:[3,4],slide:[2,6],slightli:[2,6],some:[3,6],sourc:2,space:[0,3,6],spec:[1,5],special:3,special_typ:3,specif:[3,5],specifi:[0,3],split:3,standard:[0,2,5],starter:1,state:[0,2],statu:[3,5],statuscod:5,stderr:[3,5],stdin:5,stdout:[3,5],step:1,stiff:[2,6],store:5,str:5,string:[0,3,5],structur:[0,1,5],sub:[0,5],subdirectori:1,submiss:1,substanti:6,subword:3,successfulli:1,suffix_typ:3,support:[1,2,4,6],supported_featur:3,surpris:[2,3,5,6],system:[1,6],tab:[0,3],tabl:4,take:1,templat:1,test:1,testtest2:[],text:[0,2,3,4,5,8],textiowrapp:5,than:0,thank:1,thei:[1,3],thi:[0,1,3,5],thread:1,tinylstm:4,tip:1,token:[2,4,5,6],token_id:[0,2,3,5,6],tool:[2,3,4],transform:[2,6],troubl:[2,6],tsv:3,tupl:5,txt:[2,4,6],type:[3,5],under:[0,3,5],union:5,unk:[0,2,3,6],unk_typ:3,unkifi:[1,5],unknown:[0,5],unsupport:3,until:1,updat:4,uri:3,usag:7,use:[1,2],used:[0,5],useful:1,uses:1,using:[1,3,6,8],utf:[0,3,5],valu:[0,3,5],variou:3,verbos:0,verifi:1,vermin:[2,6],version:3,via:[3,4,7],vitali:8,vocabulari:[0,3,5],w_1:[0,3,5],w_2:[0,5],w_i:[0,3,5],welcom:1,wget:[2,6],when:[1,2,3,5,6],where:[0,3,5],which:[0,1,3,5],whitespac:3,window:6,within:[1,3],woke:[2,6],word:[0,2,3,5],wrapper:[1,3],write:[0,1,3],written:3,www:[],you:[1,2,3,4,6,7],your:3,zero:3,zoo:[3,4,5,6,8]},titles:["<code class=\"docutils literal notranslate\"><span class=\"pre\">lm-zoo</span></code> commands","Contributing to the LM Zoo","Welcome to LM Zoo","Language model Docker API","Official models","Python API reference","Quickstart","Support","Acknowledgments"],titleterms:{acknowledg:8,acquir:1,api:[3,5],backend:5,binari:3,build:[1,3],code:1,command:[0,5],context:1,contribut:1,docker:[1,3],featur:3,format:3,get:[0,6],get_predict:3,get_surpris:3,hdf5:3,imag:1,instal:6,languag:[1,3],list:0,logo:8,major:5,model:[1,3,4,5],offici:4,open:1,output:3,partial:3,predict:0,prepar:1,python:5,quickstart:6,refer:5,requir:6,schema:3,script:1,share:1,sourc:1,spec:3,start:6,submit:1,support:[3,7],surpris:0,token:[0,3],unkifi:[0,3],welcom:2,your:1,zoo:[0,1,2]}})
\ No newline at end of file

From b7971dbdd828291e4caa37c3c0001efd05ee5e66 Mon Sep 17 00:00:00 2001
From: Jon Gauthier <jon@gauthiers.net>
Date: Fri, 26 Mar 2021 11:22:39 -0400
Subject: [PATCH 7/8] model test script: match T5 token sentinel. Fixes #61

---
 test.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/test.py b/test.py
index 5e17cd4..d9e0892 100644
--- a/test.py
+++ b/test.py
@@ -26,7 +26,7 @@
     LANGUAGE_MODEL_SPEC_SCHEMA = json.load(spec_f)
 
 SURPRISAL_RE = re.compile(r"sentence_id\ttoken_id\ttoken\tsurprisal\n"
-                           "(\d+\s+\d+\s+[\w.<>]+\s+[-\d.]+\n)+(\d+\s+\d+\s+[\w.<>]+\s+[-\d.]+)",
+                           "(\d+\s+\d+\s+[\w.<>\u2581]+\s+[-\d.]+\n)+(\d+\s+\d+\s+[\w.<>\u2581]+\s+[-\d.]+)",
                           flags=re.MULTILINE)
 
 

From c7c80227b63762ae470883d0e26495afe6c57d6c Mon Sep 17 00:00:00 2001
From: Jon Gauthier <jon@gauthiers.net>
Date: Fri, 26 Mar 2021 11:27:19 -0400
Subject: [PATCH 8/8] update dependencies

---
 Pipfile.lock | 839 +++++++++++++++++++++++++++------------------------
 1 file changed, 448 insertions(+), 391 deletions(-)

diff --git a/Pipfile.lock b/Pipfile.lock
index f42bc63..07eb0fb 100644
--- a/Pipfile.lock
+++ b/Pipfile.lock
@@ -14,19 +14,27 @@
         ]
     },
     "default": {
+        "cached-property": {
+            "hashes": [
+                "sha256:9fa5755838eecbb2d234c3aa390bd80fbd3ac6b6869109bfc1b499f7bd89a130",
+                "sha256:df4f613cf7ad9a588cc381aaf4a512d26265ecebd5eb9e1ba12f1319eb85a6a0"
+            ],
+            "markers": "python_version < '3.8'",
+            "version": "==1.5.2"
+        },
         "certifi": {
             "hashes": [
-                "sha256:1d987a998c75633c40847cc966fcf5904906c920a7f17ef374f5aa4282abd304",
-                "sha256:51fcb31174be6e6664c5f69e3e1691a2d72a1a12e90f872cbdb1567eb47b6519"
+                "sha256:1a4995114262bffbc2413b159f2a1a480c969de6e6eb13ee966d470af86af59c",
+                "sha256:719a74fb9e33b9bd44cc7f3a8d94bc35e4049deebe19ba7d8e108280cfd59830"
             ],
-            "version": "==2020.4.5.1"
+            "version": "==2020.12.5"
         },
         "chardet": {
             "hashes": [
-                "sha256:84ab92ed1c4d4f16916e05906b6b75a6c0fb5db821cc65e70cbd64a3e2a5eaae",
-                "sha256:fc323ffcaeaed0e0a02bf4d117757b98aed530d9ed4531e3e15460124c106691"
+                "sha256:0d6f53a15db4120f2b08c94f11e7d93d2c911ee118b6b30a04ec3ee8310179fa",
+                "sha256:f864054d66fd9118f2e67044ac8981a54775ec5b67aed0441892edb553d21da5"
             ],
-            "version": "==3.0.4"
+            "version": "==4.0.0"
         },
         "click": {
             "hashes": [
@@ -38,116 +46,101 @@
         },
         "colorama": {
             "hashes": [
-                "sha256:7d73d2a99753107a36ac6b455ee49046802e59d9d076ef8e47b61499fa29afff",
-                "sha256:e96da0d330793e2cb9485e9ddfd918d456036c7149416295932478192f4436a1"
+                "sha256:5941b2b48a20143d2267e95b1c2a7603ce057ee39fd88e7329b0c292aa16869b",
+                "sha256:9f47eda37229f68eee03b24b9748937c7dc3868f906e8ba69fbcbdd3bc5dc3e2"
             ],
-            "version": "==0.4.3"
+            "version": "==0.4.4"
         },
         "crayons": {
             "hashes": [
-                "sha256:50e5fa729d313e2c607ae8bf7b53bb487652e10bd8e7a1e08c4bc8bf62755ffc",
-                "sha256:8c9e4a3a607bc10e9a9140d496ecd16c6805088dd16c852c378f1f1d5db7aeb6"
+                "sha256:bd33b7547800f2cfbd26b38431f9e64b487a7de74a947b0fafc89b45a601813f",
+                "sha256:e73ad105c78935d71fe454dd4b85c5c437ba199294e7ffd3341842bc683654b1"
             ],
             "index": "pypi",
-            "version": "==0.3.0"
+            "version": "==0.4.0"
         },
         "docker": {
             "hashes": [
-                "sha256:1c2ddb7a047b2599d1faec00889561316c674f7099427b9c51e8cb804114b553",
-                "sha256:ddae66620ab5f4bce769f64bcd7934f880c8abe6aa50986298db56735d0f722e"
+                "sha256:d3393c878f575d3a9ca3b94471a3c89a6d960b35feb92f033c0de36cc9d934db",
+                "sha256:f3607d5695be025fa405a12aca2e5df702a57db63790c73b927eb6a94aac60af"
             ],
             "index": "pypi",
-            "version": "==4.2.0"
+            "version": "==4.4.4"
         },
         "h5py": {
             "hashes": [
-                "sha256:063947eaed5f271679ed4ffa36bb96f57bc14f44dd4336a827d9a02702e6ce6b",
-                "sha256:13c87efa24768a5e24e360a40e0bc4c49bcb7ce1bb13a3a7f9902cec302ccd36",
-                "sha256:16ead3c57141101e3296ebeed79c9c143c32bdd0e82a61a2fc67e8e6d493e9d1",
-                "sha256:3dad1730b6470fad853ef56d755d06bb916ee68a3d8272b3bab0c1ddf83bb99e",
-                "sha256:51ae56894c6c93159086ffa2c94b5b3388c0400548ab26555c143e7cfa05b8e5",
-                "sha256:54817b696e87eb9e403e42643305f142cd8b940fe9b3b490bbf98c3b8a894cf4",
-                "sha256:549ad124df27c056b2e255ea1c44d30fb7a17d17676d03096ad5cd85edb32dc1",
-                "sha256:64f74da4a1dd0d2042e7d04cf8294e04ddad686f8eba9bb79e517ae582f6668d",
-                "sha256:6998be619c695910cb0effe5eb15d3a511d3d1a5d217d4bd0bebad1151ec2262",
-                "sha256:6ef7ab1089e3ef53ca099038f3c0a94d03e3560e6aff0e9d6c64c55fb13fc681",
-                "sha256:769e141512b54dee14ec76ed354fcacfc7d97fea5a7646b709f7400cf1838630",
-                "sha256:79b23f47c6524d61f899254f5cd5e486e19868f1823298bc0c29d345c2447172",
-                "sha256:7be5754a159236e95bd196419485343e2b5875e806fe68919e087b6351f40a70",
-                "sha256:84412798925dc870ffd7107f045d7659e60f5d46d1c70c700375248bf6bf512d",
-                "sha256:86868dc07b9cc8cb7627372a2e6636cdc7a53b7e2854ad020c9e9d8a4d3fd0f5",
-                "sha256:8bb1d2de101f39743f91512a9750fb6c351c032e5cd3204b4487383e34da7f75",
-                "sha256:a5f82cd4938ff8761d9760af3274acf55afc3c91c649c50ab18fcff5510a14a5",
-                "sha256:aac4b57097ac29089f179bbc2a6e14102dd210618e94d77ee4831c65f82f17c0",
-                "sha256:bffbc48331b4a801d2f4b7dac8a72609f0b10e6e516e5c480a3e3241e091c878",
-                "sha256:c0d4b04bbf96c47b6d360cd06939e72def512b20a18a8547fa4af810258355d5",
-                "sha256:c54a2c0dd4957776ace7f95879d81582298c5daf89e77fb8bee7378f132951de",
-                "sha256:cbf28ae4b5af0f05aa6e7551cee304f1d317dbed1eb7ac1d827cee2f1ef97a99",
-                "sha256:d35f7a3a6cefec82bfdad2785e78359a0e6a5fbb3f605dd5623ce88082ccd681",
-                "sha256:d3c59549f90a891691991c17f8e58c8544060fdf3ccdea267100fa5f561ff62f",
-                "sha256:d7ae7a0576b06cb8e8a1c265a8bc4b73d05fdee6429bffc9a26a6eb531e79d72",
-                "sha256:ecf4d0b56ee394a0984de15bceeb97cbe1fe485f1ac205121293fc44dcf3f31f",
-                "sha256:f0e25bb91e7a02efccb50aba6591d3fe2c725479e34769802fcdd4076abfa917",
-                "sha256:f23951a53d18398ef1344c186fb04b26163ca6ce449ebd23404b153fd111ded9",
-                "sha256:ff7d241f866b718e4584fa95f520cb19405220c501bd3a53ee11871ba5166ea2"
+                "sha256:25294f2690c4813475f566663a21ef1c1b11ef892b26d46454bf0a59e507d5aa",
+                "sha256:4160cb0d35a83c6fb9f1cad65e826dfaeb044e001549ea78003573fb6bee4042",
+                "sha256:6766104ed13ff40b3b7bfd49f13fced5274103ee9af53667e7a97c5236b14741",
+                "sha256:7c5b5f18c96fb63399280a724734fd91e1781c6b60e385e439ad8e654a294ba4",
+                "sha256:89474be911bfcdb34cbf0d98b8ec48b578c27a89fdb1ae4ee7513f1ef8d9249e",
+                "sha256:90ee8a00aca5c4e0bbd821c1f6118cb9a814c15dcfdb03572c615a4431166480",
+                "sha256:a6632ac11167bbad1a8fc5c82508b97ab8c12bdfe4b659254b6f7f63d3c76744",
+                "sha256:d791b710d3e54c4d2c32cb881b183db5674ceb03bf6a0c1f3fb3cf50d8997e0a",
+                "sha256:d8467fa56356ad2efad2b5986326e71d4d74505de6f6c7bb46dbba09b37459ac",
+                "sha256:fdabe99139a9c5e1a416b7ed38c89505f8501b376d54496e1bb737cb33df61cf"
             ],
             "index": "pypi",
-            "version": "==2.10.0"
+            "version": "==3.2.1"
         },
         "idna": {
             "hashes": [
-                "sha256:7588d1c14ae4c77d74036e8c22ff447b26d0fde8f007354fd48a7814db15b7cb",
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+                "sha256:a93e34f10f67d81de706ce00bf8bb3798403cabce4ccb2de10c61b5ae8786ab5",
+                "sha256:d59842a5aa89ca03c2099312163ffdd06f56486050e641a45d926a072f04d994",
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             "index": "pypi",
-            "version": "==1.0.3"
+            "version": "==1.2.3"
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         "python-dateutil": {
             "hashes": [
@@ -159,25 +152,25 @@
         },
         "pytz": {
             "hashes": [
-                "sha256:a494d53b6d39c3c6e44c3bec237336e14305e4f29bbf800b599253057fbb79ed",
-                "sha256:c35965d010ce31b23eeb663ed3cc8c906275d6be1a34393a1d73a41febf4a048"
+                "sha256:83a4a90894bf38e243cf052c8b58f381bfe9a7a483f6a9cab140bc7f702ac4da",
+                "sha256:eb10ce3e7736052ed3623d49975ce333bcd712c7bb19a58b9e2089d4057d0798"
             ],
-            "version": "==2020.1"
+            "version": "==2021.1"
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         "requests": {
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-                "sha256:b3f43d496c6daba4493e7c431722aeb7dbc6288f52a6e04e7b6023b0247817e6"
+                "sha256:27973dd4a904a4f13b263a19c866c13b92a39ed1c964655f025f3f8d3d75b804",
+                "sha256:c210084e36a42ae6b9219e00e48287def368a26d03a048ddad7bfee44f75871e"
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             "index": "pypi",
-            "version": "==2.23.0"
+            "version": "==2.25.1"
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         "semver": {
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-                "sha256:b08a84f604ef579e474ce448672a05c8d50d1ee0b24cee9fb58a12b260e4d0dc"
+                "sha256:ced8b23dceb22134307c1b8abfa523da14198793d9787ac838e70e29e77458d4",
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             ],
-            "version": "==2.10.1"
+            "version": "==2.13.0"
         },
         "six": {
             "hashes": [
@@ -188,32 +181,32 @@
         },
         "spython": {
             "hashes": [
-                "sha256:e4eddd6f439fe9a9a0f6566e13d89ff096397f86043c50a8d8dcfc87e7b4d686"
+                "sha256:ee697d102a38d1d6958b4567b3975e168027336e2400a37066bcc27d57138b2a"
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             "index": "pypi",
-            "version": "==0.0.80"
+            "version": "==0.1.11"
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         "tqdm": {
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-                "sha256:acdafb20f51637ca3954150d0405ff1a7edde0ff19e38fb99a80a66210d2a28f"
+                "sha256:9fdf349068d047d4cfbe24862c425883af1db29bcddf4b0eeb2524f6fbdb23c7",
+                "sha256:d666ae29164da3e517fcf125e41d4fe96e5bb375cd87ff9763f6b38b5592fe33"
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             "index": "pypi",
-            "version": "==4.46.0"
+            "version": "==4.59.0"
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         "urllib3": {
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-                "sha256:88206b0eb87e6d677d424843ac5209e3fb9d0190d0ee169599165ec25e9d9115"
+                "sha256:2f4da4594db7e1e110a944bb1b551fdf4e6c136ad42e4234131391e21eb5b0df",
+                "sha256:e7b021f7241115872f92f43c6508082facffbd1c048e3c6e2bb9c2a157e28937"
             ],
-            "version": "==1.25.9"
+            "version": "==1.26.4"
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         "websocket-client": {
             "hashes": [
-                "sha256:0fc45c961324d79c781bab301359d5a1b00b13ad1b10415a4780229ef71a5549",
-                "sha256:d735b91d6d1692a6a181f2a8c9e0238e5f6373356f561bb9dc4c7af36f452010"
+                "sha256:44b5df8f08c74c3d82d28100fdc81f4536809ce98a17f0757557813275fbb663",
+                "sha256:63509b41d158ae5b7f67eb4ad20fecbb4eee99434e73e140354dc3ff8e09716f"
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-            "version": "==0.57.0"
+            "version": "==0.58.0"
         }
     },
     "develop": {
@@ -233,17 +226,17 @@
         },
         "attrs": {
             "hashes": [
-                "sha256:08a96c641c3a74e44eb59afb61a24f2cb9f4d7188748e76ba4bb5edfa3cb7d1c",
-                "sha256:f7b7ce16570fe9965acd6d30101a28f62fb4a7f9e926b3bbc9b61f8b04247e72"
+                "sha256:31b2eced602aa8423c2aea9c76a724617ed67cf9513173fd3a4f03e3a929c7e6",
+                "sha256:832aa3cde19744e49938b91fea06d69ecb9e649c93ba974535d08ad92164f700"
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-            "version": "==19.3.0"
+            "version": "==20.3.0"
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         "babel": {
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-                "sha256:d670ea0b10f8b723672d3a6abeb87b565b244da220d76b4dba1b66269ec152d4"
+                "sha256:9d35c22fcc79893c3ecc85ac4a56cde1ecf3f19c540bba0922308a6c06ca6fa5",
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-            "version": "==2.8.0"
+            "version": "==2.9.0"
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         "black": {
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@@ -255,17 +248,18 @@
         },
         "bleach": {
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-                "sha256:2bce3d8fab545a6528c8fa5d9f9ae8ebc85a56da365c7f85180bfe96a35ef22f",
-                "sha256:3c4c520fdb9db59ef139915a5db79f8b51bc2a7257ea0389f30c846883430a4b"
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-            "version": "==3.1.5"
+            "version": "==3.3.0"
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-                "sha256:9217a59f14a5682da7c4b8829deadbfc194ac22e9908ccf7c8820234e80a1504"
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-            "version": "==1.5.1"
+            "markers": "python_version < '3.8'",
+            "version": "==1.5.2"
         },
         "cerberus": {
             "hashes": [
@@ -275,50 +269,59 @@
         },
         "certifi": {
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-            "version": "==2020.4.5.1"
+            "version": "==2020.12.5"
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-            "version": "==3.0.4"
+            "version": "==4.0.0"
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         "click": {
             "hashes": [
@@ -330,48 +333,42 @@
         },
         "colorama": {
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-                "sha256:7d73d2a99753107a36ac6b455ee49046802e59d9d076ef8e47b61499fa29afff",
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-            "version": "==0.4.3"
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         "distlib": {
             "hashes": [
-                "sha256:2e166e231a26b36d6dfe35a48c4464346620f8645ed0ace01ee31822b288de21"
+                "sha256:8c09de2c67b3e7deef7184574fc060ab8a793e7adbb183d942c389c8b13c52fb",
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-            "version": "==0.3.0"
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         "docker": {
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-                "sha256:ddae66620ab5f4bce769f64bcd7934f880c8abe6aa50986298db56735d0f722e"
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             "index": "pypi",
-            "version": "==4.2.0"
+            "version": "==4.4.4"
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         "docutils": {
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@@ -382,10 +379,10 @@
         },
         "idna": {
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-                "sha256:7588d1c14ae4c77d74036e8c22ff447b26d0fde8f007354fd48a7814db15b7cb",
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-            "version": "==2.9"
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         "imagesize": {
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@@ -396,40 +393,47 @@
         },
         "importlib-metadata": {
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             "markers": "python_version < '3.8'",
-            "version": "==1.6.0"
+            "version": "==3.7.3"
+        },
+        "iniconfig": {
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         "jeepney": {
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             "markers": "sys_platform == 'linux'",
-            "version": "==0.4.3"
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         "jinja2": {
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-            "version": "==2.11.2"
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-            "version": "==2.0"
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-            "version": "==21.2.1"
+            "version": "==23.0.1"
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@@ -438,8 +442,12 @@
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@@ -448,53 +456,69 @@
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@@ -521,46 +545,39 @@
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-                "sha256:8e6199cf1288d48a0c44057f112acf18aa5ebabbf73faa242f598fbe145ba29e"
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@@ -570,10 +587,10 @@
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@@ -594,10 +611,10 @@
         },
         "py": {
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@@ -608,10 +625,10 @@
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@@ -622,19 +639,19 @@
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@@ -646,67 +663,105 @@
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+                "sha256:b98bc9db003f1079caf07b610377ed1ac2e2c11acc2bea4892e28cc5b509d8d5",
+                "sha256:b9d8d286c53fe0cbc6d20bf3d583cabcd1499d89034524e3b94c93a5ab85ca90",
+                "sha256:bcd945175c29a672f13fce13a11893556cd440e37c1b643d6eeab1988c8b209c",
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+                "sha256:c782da0e45aff131f0bed6e66fbcfa589ff2862fc719b83a88640daa01a5aff7",
+                "sha256:cb4ee827857a5ad9b8ae34d3c8cc51151cb4a3fe082c12ec20ec73e63cc7c6f0",
+                "sha256:d47d359545b0ccad29d572ecd52c9da945de7cd6cf9c0cfcb0269f76d3555689",
+                "sha256:dc9963aacb7da5177e40874585d7407c0f93fb9d7518ec58b86e562f633f36cd",
+                "sha256:ea2f41445852c660ba7c3ebf7d70b3779b20d9ca8ba54485a17740db49f46932",
+                "sha256:f5d0c921c99297354cecc5a416ee4280bd3f20fd81b9fb671ca6be71499c3fdf",
+                "sha256:f85d6f41e34f6a2d1607e312820971872944f1661a73d33e1e82d35ea3305e14"
+            ],
+            "version": "==2021.3.17"
         },
         "requests": {
             "hashes": [
-                "sha256:43999036bfa82904b6af1d99e4882b560e5e2c68e5c4b0aa03b655f3d7d73fee",
-                "sha256:b3f43d496c6daba4493e7c431722aeb7dbc6288f52a6e04e7b6023b0247817e6"
+                "sha256:27973dd4a904a4f13b263a19c866c13b92a39ed1c964655f025f3f8d3d75b804",
+                "sha256:c210084e36a42ae6b9219e00e48287def368a26d03a048ddad7bfee44f75871e"
             ],
             "index": "pypi",
-            "version": "==2.23.0"
+            "version": "==2.25.1"
         },
         "requests-toolbelt": {
             "hashes": [
@@ -717,18 +772,25 @@
         },
         "requirementslib": {
             "hashes": [
-                "sha256:3281c01d3f9fa4094abea4c74ee3ccbf5be5a31fbad27c990b61508fb5d1bd76",
-                "sha256:75ab3aca99480c7c6a27889b6461b5faa9dc27892f0e0a1a93b5b26507e34ad0"
+                "sha256:50d20f27e4515a2393695b0d886219598302163438ae054253147b2bad9b4a44",
+                "sha256:9c1e8666ca4512724cdd1739adcc7df19ec7ad2ed21f0e748f9631ad6b54f321"
             ],
-            "version": "==1.5.9"
+            "version": "==1.5.16"
+        },
+        "rfc3986": {
+            "hashes": [
+                "sha256:112398da31a3344dc25dbf477d8df6cb34f9278a94fee2625d89e4514be8bb9d",
+                "sha256:af9147e9aceda37c91a05f4deb128d4b4b49d6b199775fd2d2927768abdc8f50"
+            ],
+            "version": "==1.4.0"
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         "secretstorage": {
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-                "sha256:b5ec909dde94d4ae2fa26af7c089036997030f0cf0a5cb372b4cccabd81c143b"
+                "sha256:422d82c36172d88d6a0ed5afdec956514b189ddbfb72fefab0c8a1cee4eaf71f",
+                "sha256:fd666c51a6bf200643495a04abb261f83229dcb6fd8472ec393df7ffc8b6f195"
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             "markers": "sys_platform == 'linux'",
-            "version": "==3.1.2"
+            "version": "==3.3.1"
         },
         "six": {
             "hashes": [
@@ -739,33 +801,33 @@
         },
         "snowballstemmer": {
             "hashes": [
-                "sha256:209f257d7533fdb3cb73bdbd24f436239ca3b2fa67d56f6ff88e86be08cc5ef0",
-                "sha256:df3bac3df4c2c01363f3dd2cfa78cce2840a79b9f1c2d2de9ce8d31683992f52"
+                "sha256:b51b447bea85f9968c13b650126a888aabd4cb4463fca868ec596826325dedc2",
+                "sha256:e997baa4f2e9139951b6f4c631bad912dfd3c792467e2f03d7239464af90e914"
             ],
-            "version": "==2.0.0"
+            "version": "==2.1.0"
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         "sphinx": {
             "hashes": [
-                "sha256:62edfd92d955b868d6c124c0942eba966d54b5f3dcb4ded39e65f74abac3f572",
-                "sha256:f5505d74cf9592f3b997380f9bdb2d2d0320ed74dd69691e3ee0644b956b8d83"
+                "sha256:3f01732296465648da43dec8fb40dc451ba79eb3e2cc5c6d79005fd98197107d",
+                "sha256:ce9c228456131bab09a3d7d10ae58474de562a6f79abb3dc811ae401cf8c1abc"
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             "index": "pypi",
-            "version": "==3.0.3"
+            "version": "==3.5.3"
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         "sphinx-click": {
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-                "sha256:1b649ebe9f7a85b78ef6545d1dc258da5abca850ac6375be104d484a6334a728"
+                "sha256:1b6175df5392564fd3780000d4627e5a2c8c3b29d05ad311dbbe38fcf5f3327b",
+                "sha256:e738a2c7a87f23e67da4a9e28ca6f085d3ca626f0e4164847f77ff3c36c65df1"
             ],
             "index": "pypi",
-            "version": "==2.3.2"
+            "version": "==2.7.1"
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         "sphinx-jsonschema": {
             "hashes": [
-                "sha256:7fcc7bbec1d4f9cc9d8c564a59a3f6dad8878b30933fd644e20ede29b1ce3e3f"
+                "sha256:5728b3ece1fe475c285d5ae16953242c51b4e6852f48f0bb734cd8408f3ac8b3"
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             "index": "pypi",
-            "version": "==1.15"
+            "version": "==1.16.8"
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@@ -818,82 +880,84 @@
         },
         "toml": {
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-                "sha256:bda89d5935c2eac546d648028b9901107a595863cb36bae0c73ac804a9b4ce88"
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-            "version": "==0.10.1"
+            "version": "==0.10.2"
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         "tomlkit": {
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-                "sha256:e5d5f20809c2b09276a6c5d98fb0202325aee441a651db84ac12e0812ab7e569"
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-            "version": "==0.6.0"
+            "version": "==0.7.0"
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-            "version": "==4.46.0"
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-                "sha256:6e95524d8a547a91e08f404ae485bbb71962de46967e1b71a0cb89af24e761c5",
-                "sha256:79ee589a3caca649a9bfd2a8de4709837400dfa00b6cc81962a1e6a1815969ae",
-                "sha256:f8d2bd89d25bc39dabe7d23df520442fa1d8969b82544370e03d88b5a591c392"
+                "sha256:7cb407020f00f7bfc3cb3e7881628838e69d8f3fcab2f64742a5e76b2f841918",
+                "sha256:99d4073b617d30288f569d3f13d2bd7548c3a7e4c8de87db09a9d29bb3a4a60c",
+                "sha256:dafc7639cde7f1b6e1acc0f457842a83e722ccca8eef5270af2d74792619a89f"
             ],
-            "version": "==3.7.4.2"
+            "markers": "python_version < '3.8'",
+            "version": "==3.7.4.3"
         },
         "urllib3": {
             "hashes": [
-                "sha256:3018294ebefce6572a474f0604c2021e33b3fd8006ecd11d62107a5d2a963527",
-                "sha256:88206b0eb87e6d677d424843ac5209e3fb9d0190d0ee169599165ec25e9d9115"
+                "sha256:2f4da4594db7e1e110a944bb1b551fdf4e6c136ad42e4234131391e21eb5b0df",
+                "sha256:e7b021f7241115872f92f43c6508082facffbd1c048e3c6e2bb9c2a157e28937"
             ],
-            "version": "==1.25.9"
+            "version": "==1.26.4"
         },
         "vistir": {
             "hashes": [
@@ -902,13 +966,6 @@
             ],
             "version": "==0.5.2"
         },
-        "wcwidth": {
-            "hashes": [
-                "sha256:cafe2186b3c009a04067022ce1dcd79cb38d8d65ee4f4791b8888d6599d1bbe1",
-                "sha256:ee73862862a156bf77ff92b09034fc4825dd3af9cf81bc5b360668d425f3c5f1"
-            ],
-            "version": "==0.1.9"
-        },
         "webencodings": {
             "hashes": [
                 "sha256:a0af1213f3c2226497a97e2b3aa01a7e4bee4f403f95be16fc9acd2947514a78",
@@ -918,25 +975,25 @@
         },
         "websocket-client": {
             "hashes": [
-                "sha256:0fc45c961324d79c781bab301359d5a1b00b13ad1b10415a4780229ef71a5549",
-                "sha256:d735b91d6d1692a6a181f2a8c9e0238e5f6373356f561bb9dc4c7af36f452010"
+                "sha256:44b5df8f08c74c3d82d28100fdc81f4536809ce98a17f0757557813275fbb663",
+                "sha256:63509b41d158ae5b7f67eb4ad20fecbb4eee99434e73e140354dc3ff8e09716f"
             ],
-            "version": "==0.57.0"
+            "version": "==0.58.0"
         },
         "wheel": {
             "hashes": [
-                "sha256:8788e9155fe14f54164c1b9eb0a319d98ef02c160725587ad60f14ddc57b6f96",
-                "sha256:df277cb51e61359aba502208d680f90c0493adec6f0e848af94948778aed386e"
+                "sha256:78b5b185f0e5763c26ca1e324373aadd49182ca90e825f7853f4b2509215dc0e",
+                "sha256:e11eefd162658ea59a60a0f6c7d493a7190ea4b9a85e335b33489d9f17e0245e"
             ],
-            "version": "==0.34.2"
+            "version": "==0.36.2"
         },
         "zipp": {
             "hashes": [
-                "sha256:aa36550ff0c0b7ef7fa639055d797116ee891440eac1a56f378e2d3179e0320b",
-                "sha256:c599e4d75c98f6798c509911d08a22e6c021d074469042177c8c86fb92eefd96"
+                "sha256:3607921face881ba3e026887d8150cca609d517579abe052ac81fc5aeffdbd76",
+                "sha256:51cb66cc54621609dd593d1787f286ee42a5c0adbb4b29abea5a63edc3e03098"
             ],
             "markers": "python_version < '3.8'",
-            "version": "==3.1.0"
+            "version": "==3.4.1"
         }
     }
 }