New vectors

compress.py

@@ -30,15 +30,24 @@ def dequantize_8bit(quantized, min_val, max_val):
 
 def main(args):
     vecs = np.load(args.vectors)
+
+    n, dim = vecs.shape
+    if dim != 300:
+        from sklearn.decomposition import PCA
+        vecs = PCA(n_components=300).fit_transform(vecs)
+
     # vecs /= np.linalg.norm(vecs, axis=1, keepdims=True)
     with open(args.words) as file:
         words = file.readlines()
 
-    good_words = set()
-    print(args.f)
-    for path in args.f:
-        with open(path) as file:
-            good_words |= {line.lower().strip() for line in file}
+    if not args.f:
+        good_words = set(words)
+    else:
+        good_words = set()
+        print(args.f)
+        for path in args.f:
+            with open(path) as file:
+                good_words |= {line.lower().strip() for line in file}
     print(f'{len(good_words)=}')
     print(list(good_words)[:3])
 
@@ -75,7 +84,7 @@ def main(args):
         if merr < best_err:
             best_err = merr
             best_alpha = alpha
-        # print(f"{alpha}, Mean error: {merr}")
+        print(f"{alpha}, Mean error: {merr}")
     print(f"{best_alpha=}")
 
     compressed, min_val, max_val = quantize_8bit(x, best_alpha)

website/game.js

@@ -8,7 +8,8 @@ if (!isIOSVersionAtLeast(16)) {
 // Start heavy promises
 const root = '/website/model';
 const prom = Promise.all([
-   fetchVectors(root + '/vecs.gz'),
+   //fetchVectors(root + '/vecs.gz'),
+   fetchVectors(root + '/angel.gz'),
    fetchWordsGz(root + '/words.gz'),
    fetchWords(root + '/stopwords')
 ]);
@@ -565,29 +566,27 @@ function fetchVectors(path) {
       })
       .then(decompressedBuffer => {
          const dim = 300;
-         //const rows = 20000;
          const rows = 9910;
          const byteArray = new Uint8Array(decompressedBuffer);
-         // console.log(byteArray);
-         const min_val=-2.645588700353074;
-         const max_val=2.6333964024164196;
-         //min=-2.6348934823495345, max=2.6430343918786767
+
+         // Glove:
+         //const min_val=-2.645588700353074;
+         //const max_val=2.6333964024164196;
+
+         // Angel:
+         const min_val=-3.508529352673804;
+         const max_val=4.6301482913369485;
+
+         // Dequantize
          const quantizedMatrix = mlMatrix.Matrix.from1DArray(rows, dim, byteArray);
          let matrix = quantizedMatrix.div(255).mul(max_val - min_val).add(min_val);
 
-         //console.log(matrix);
-         //const norms = matrix.mul(matrix).sum('row').sqrt();
-
+         // Normalize
          for (let i = 0; i < matrix.rows; i++) {
             let row = matrix.getRow(i);
             let norm = Math.sqrt(row.reduce((sum, value) => sum + value * value, 0));
             matrix.setRow(i, row.map(value => value / norm));
          }
-         // console.log("TOP ROW");
-         // console.log(matrix.getRow(0));
-
-
-         // console.log(matrix);
          return matrix;
       })
       .catch(error => console.error('Error loading file:', error));

website/model/stopwords

@@ -100,7 +100,6 @@ crow
 lesbian
 jerk
 breast
-finger
 prick
 trash
 gay
@@ -125,10 +124,8 @@ snatch
 slit
 nipple
 tramp
-meat
 ape
 retard
 bum
-wound
 trey
 sexist

website/styles.css

@@ -71,6 +71,9 @@ h2 {
 ul, h3 {
    margin-bottom: 1rem;
 }
+ul {
+   padding-left: 1rem;
+}
 h3 {
    font-weight: normal;
 }
@@ -475,3 +478,4 @@ body:not(.today) .is-today {
    left: 50%;
    transform: translate(-50%, -110%);
 }
+