[use-qna] use tf.matmul for dot product computation (#886)

* use tf.matMul to do the dot product instead of download to cpu and compute

* fix typo on readme

Author: pyu10055

universal-sentence-encoder/README.md

@@ -125,30 +125,8 @@ use.loadQnA().then(model => {
     * And embed_responses[0] is the embedding for the answer
     * 'I\'m not feeling very well.'
     */
-  const embed_query = embeddings['queryEmbedding'].arraySync();
-  const embed_responses = embeddings['responseEmbedding'].arraySync();
-  // compute the dotProduct of each query and response pair.
-  for (let i = 0; i < input['queries'].length; i++) {
-    for (let j = 0; j < input['responses'].length; j++) {
-      scores.push(dotProduct(embed_query[i], embed_responses[j]));
-    }
-  }
+  const scores = tf.matMul(embeddings['queryEmbedding'],
+      embeddings['responseEmbedding'], false, true).dataSync();
 });
 
-// Calculate the dot product of two vector arrays.
-const dotProduct = (xs, ys) => {
-  const sum = xs => xs ? xs.reduce((a, b) => a + b, 0) : undefined;
-
-  return xs.length === ys.length ?
-    sum(zipWith((a, b) => a * b, xs, ys))
-    : undefined;
-}
-
-// zipWith :: (a -> b -> c) -> [a] -> [b] -> [c]
-const zipWith =
-    (f, xs, ys) => {
-      const ny = ys.length;
-      return (xs.length <= ny ? xs : xs.slice(0, ny))
-          .map((x, i) => f(x, ys[i]));
-    }
 ```

universal-sentence-encoder/demo/index.js

@@ -83,31 +83,15 @@ const initQnA = async () => {
   const model = await use.loadQnA();
   document.querySelector('#loadingQnA').style.display = 'none';
   let result = model.embed(input);
-  const query = result['queryEmbedding'].arraySync();
-  const answers = result['responseEmbedding'].arraySync();
-  for (let i = 0; i < answers.length; i++) {
+  const dp = tf.matMul(result['queryEmbedding'], result['responseEmbedding'],
+      false, true).dataSync();
+  for (let i = 0; i < dp.length; i++) {
     document.getElementById(`answer_${i + 1}`).textContent =
-        `${dotProduct(query[0], answers[i])}`
+        `${dp[i]}`
   }
 };
 init();
 initQnA();
-// zipWith :: (a -> b -> c) -> [a] -> [b] -> [c]
-const zipWith =
-    (f, xs, ys) => {
-      const ny = ys.length;
-      return (xs.length <= ny ? xs : xs.slice(0, ny))
-          .map((x, i) => f(x, ys[i]));
-    }
-
-// dotProduct :: [Int] -> [Int] -> Int
-const dotProduct =
-    (xs, ys) => {
-      const sum = xs => xs ? xs.reduce((a, b) => a + b, 0) : undefined;
-
-      return xs.length === ys.length ? (sum(zipWith((a, b) => a * b, xs, ys))) :
-                                       undefined;
-    }
 
 const renderSentences = () => {
   sentences.forEach((sentence, i) => {

universal-sentence-encoder/demo/package.json

@@ -9,12 +9,12 @@
     "node": ">=8.9.0"
   },
   "dependencies": {
+    "@tensorflow-models/universal-sentence-encoder": "file:../dist",
     "@tensorflow/tfjs-backend-cpu": "^3.3.0",
     "@tensorflow/tfjs-backend-webgl": "^3.3.0",
     "@tensorflow/tfjs-converter": "^3.3.0",
     "@tensorflow/tfjs-core": "^3.3.0",
-    "d3-scale-chromatic": "^1.3.3",
-    "@tensorflow-models/universal-sentence-encoder": "file:../dist"
+    "d3-scale-chromatic": "^1.3.3"
   },
   "scripts": {
     "watch": "cross-env NODE_ENV=development parcel index.html --no-hmr --open --target browser",
@@ -32,6 +32,7 @@
     "@babel/plugin-transform-runtime": "^7.7.6",
     "@babel/polyfill": "^7.10.4",
     "@babel/preset-env": "^7.7.6",
+    "babel-preset-env": "^1.7.0",
     "clang-format": "~1.2.2",
     "cross-env": "^5.2.0",
     "dat.gui": "^0.7.2",