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index.js
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index.js
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/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
import '@tensorflow/tfjs-backend-cpu';
import '@tensorflow/tfjs-backend-webgl';
import * as use from '@tensorflow-models/universal-sentence-encoder';
import * as tf from '@tensorflow/tfjs-core';
import {interpolateReds} from 'd3-scale-chromatic';
const sentences = [
'I like my phone.', 'Your cellphone looks great.', 'How old are you?',
'What is your age?', 'An apple a day, keeps the doctors away.',
'Eating strawberries is healthy.'
];
const init = async () => {
const model = await use.load();
document.querySelector('#loading').style.display = 'none';
renderSentences();
const embeddings = await model.embed(sentences);
const matrixSize = 250;
const cellSize = matrixSize / sentences.length;
const canvas = document.querySelector('canvas');
canvas.width = matrixSize;
canvas.height = matrixSize;
const ctx = canvas.getContext('2d');
const xLabelsContainer = document.querySelector('.x-axis');
const yLabelsContainer = document.querySelector('.y-axis');
for (let i = 0; i < sentences.length; i++) {
const labelXDom = document.createElement('div');
const labelYDom = document.createElement('div');
labelXDom.textContent = i + 1;
labelYDom.textContent = i + 1;
labelXDom.style.left = (i * cellSize + cellSize / 2) + 'px';
labelYDom.style.top = (i * cellSize + cellSize / 2) + 'px';
xLabelsContainer.appendChild(labelXDom);
yLabelsContainer.appendChild(labelYDom);
for (let j = i; j < sentences.length; j++) {
const sentenceI = tf.slice(embeddings, [i, 0], [1]);
const sentenceJ = tf.slice(embeddings, [j, 0], [1]);
const sentenceITranspose = false;
const sentenceJTransepose = true;
const score =
tf.matMul(
sentenceI, sentenceJ, sentenceITranspose, sentenceJTransepose)
.dataSync();
ctx.fillStyle = interpolateReds(score);
ctx.fillRect(j * cellSize, i * cellSize, cellSize, cellSize);
ctx.fillRect(i * cellSize, j * cellSize, cellSize, cellSize);
}
}
};
const initQnA = async () => {
const input = {
queries: ['How are you feeling today?'],
responses: [
'I\'m not feeling very well.', 'Beijing is the capital of China.',
'You have five fingers on your hand.'
]
};
const model = await use.loadQnA();
document.querySelector('#loadingQnA').style.display = 'none';
let result = model.embed(input);
const dp = tf.matMul(result['queryEmbedding'], result['responseEmbedding'],
false, true).dataSync();
for (let i = 0; i < dp.length; i++) {
document.getElementById(`answer_${i + 1}`).textContent =
`${dp[i]}`
}
};
init();
initQnA();
const renderSentences = () => {
sentences.forEach((sentence, i) => {
const sentenceDom = document.createElement('div');
sentenceDom.textContent = `${i + 1}) ${sentence}`;
document.querySelector('#sentences-container').appendChild(sentenceDom);
});
};