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train_strike_zone.js
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train_strike_zone.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.
* =============================================================================
*/
require('@tensorflow/tfjs-node');
const argparse = require('argparse');
const sz_model = require('./strike_zone');
async function run(epochCount, savePath) {
sz_model.model.summary();
await sz_model.model.fitDataset(sz_model.trainingData, {
epochs: epochCount,
callbacks: {
onEpochEnd: async (epoch, logs) => {
console.log(`Epoch: ${epoch} - loss: ${logs.loss.toFixed(3)}`);
}
}
});
// Eval against test data:
await sz_model.testValidationData.forEachAsync(data => {
const evalOutput =
sz_model.model.evaluate(data.xs, data.ys, sz_model.TEST_DATA_LENGTH);
console.log(
`\nEvaluation result:\n` +
` Loss = ${evalOutput[0].dataSync()[0].toFixed(3)}; ` +
`Accuracy = ${evalOutput[1].dataSync()[0].toFixed(3)}`);
});
if (savePath !== null) {
await sz_model.model.save(`file://${savePath}`);
console.log(`Saved model to path: ${savePath}`);
}
}
const parser = new argparse.ArgumentParser(
{description: 'TensorFlow.js Strike Zone Training Example', addHelp: true});
parser.addArgument('--epochs', {
type: 'int',
defaultValue: 20,
help: 'Number of epochs to train the model for.'
})
parser.addArgument('--model_save_path', {
type: 'string',
help: 'Path to which the model will be saved after training.'
});
const args = parser.parseArgs();
run(args.epochs, args.model_save_path);