/** * @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. * ============================================================================= */ require('@tensorflow/tfjs-node'); const http = require('http'); const socketio = require('socket.io'); const pitch_type = require('./pitch_type'); const sleep = require('./utils').sleep; const TIMEOUT_BETWEEN_EPOCHS_MS = 500; const PORT = 8001; async function run() { const port = process.env.PORT || PORT; const server = http.createServer(); const io = socketio(server); let useTestData = true; server.listen(port, () => { console.log(`Running socket on port: ${port}`); }); io.on('connection', (socket) => { socket.on('test_data', (value) => { useTestData = value === 'true' ? true : false; }); socket.on('predictSample', async (sample) => { console.log('received predict request'); io.emit('predictResult', await pitch_type.predictSample(sample)); }); }); io.emit('accuracyPerClass', await pitch_type.evaluate(useTestData)); await sleep(TIMEOUT_BETWEEN_EPOCHS_MS); let numTrainingIterations = 10; for (var i = 0; i < numTrainingIterations; i++) { console.log(`Training iteration : ${i + 1} / ${numTrainingIterations}`); await pitch_type.model.fitDataset(pitch_type.trainingData, { epochs: 1 }); io.emit('accuracyPerClass', await pitch_type.evaluate(useTestData)); await sleep(TIMEOUT_BETWEEN_EPOCHS_MS); } io.emit('trainingComplete', true); console.log('training complete'); } run();