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index.js
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index.js
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/**
* @license
* Copyright 2018 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.
* =============================================================================
*/
/**
* The client-side inference part of the date-conversion example.
*
* Based on Python Keras example:
* https://github.com/keras-team/keras/blob/master/examples/addition_rnn.py
*/
import * as tf from '@tensorflow/tfjs';
import * as tfvis from '@tensorflow/tfjs-vis';
import {generateRandomDateTuple, INPUT_FNS, INPUT_LENGTH} from './date_format';
import {runSeq2SeqInference} from './model';
const RELATIVE_MODEL_URL = './model/model.json';
const HOSTED_MODEL_URL =
'https://storage.googleapis.com/tfjs-examples/date-conversion-attention/dist/model/model.json';
const status = document.getElementById('status');
const inputDateString = document.getElementById('input-date-string');
const outputDateString = document.getElementById('output-date-string');
const attentionHeatmap = document.getElementById('attention-heatmap');
const randomButton = document.getElementById('random-date');
let model;
inputDateString.addEventListener('change', async () => {
let inputStr = inputDateString.value.trim().toUpperCase();
if (inputStr.length < 6) {
outputDateString.value = '';
return;
}
if (inputStr.length > INPUT_LENGTH) {
inputStr = inputStr.slice(0, INPUT_LENGTH);
}
try {
const getAttention = true;
const t0 = tf.util.now();
const {outputStr, attention} =
await runSeq2SeqInference(model, inputStr, getAttention);
const tElapsed = tf.util.now() - t0;
status.textContent = `seq2seq conversion took ${tElapsed.toFixed(1)} ms`;
outputDateString.value = outputStr;
const xTickLabels = outputStr.split('').map(
(char, i) => `(${integerToTwoDigitString(i + 1)}) "${char}"`);
const yTickLabels = [];
for (let i = 0; i < INPUT_LENGTH; ++i) {
if (i < inputStr.length) {
yTickLabels.push(`(${integerToTwoDigitString(i + 1)}) "${inputStr[i]}"`);
} else {
yTickLabels.push(`(${integerToTwoDigitString(i + 1)}) ""`);
}
}
await tfvis.render.heatmap(
attentionHeatmap, {
values: attention.squeeze([0]),
xTickLabels,
yTickLabels
}, {
width: 600,
height: 360,
xLabel: 'Output characters',
yLabel: 'Input characters',
colorMap: 'blues'
});
} catch (err) {
outputDateString.value = err.message;
console.error(err);
}
});
randomButton.addEventListener('click', async () => {
const inputFn = INPUT_FNS[Math.floor(Math.random() * INPUT_FNS.length)];
inputDateString.value = inputFn(generateRandomDateTuple());
inputDateString.dispatchEvent(new Event('change'));
});
function integerToTwoDigitString(x) {
const str = `${x / 100}`.substr(2);
return str.length == 1 ? str + '0' : str;
}
async function init() {
try {
status.textContent = `Loading model from ${RELATIVE_MODEL_URL} ...`;
model = await tf.loadLayersModel(RELATIVE_MODEL_URL);
} catch (err) {
// If loading of the local model has failed, try loading from the hosted
// model.
status.textContent = `Loading hosted model from ${HOSTED_MODEL_URL} ...`;
model = await tf.loadLayersModel(HOSTED_MODEL_URL);
}
status.textContent = 'Done loading model.';
model.summary();
const exampleItems = document.getElementsByClassName('input-date-example');
for (const exampleItem of exampleItems) {
exampleItem.addEventListener('click', (event) => {
inputDateString.value = event.srcElement.textContent;
inputDateString.dispatchEvent(new Event('change'));
});
}
inputDateString.dispatchEvent(new Event('change'));
}
init();