Created
May 15, 2021 00:12
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import tf from '@tensorflow/tfjs'; | |
import fs from 'fs'; | |
const training = JSON.parse(fs.readFileSync('./data/training.json', { encoding: 'utf8'})); | |
const raw_data = training.data | |
const inputs = raw_data.map(d => d[0].reduce((p, c) => [...p, ...c], [])) | |
const labels = raw_data.map(d => d[1].length === 0 ? [-1,-1,-1] : d[1]); | |
const inputTensor = tf.tensor2d(inputs, [inputs.length, 48]); | |
const labelTensor = tf.tensor2d(labels, [inputs.length, 3]); | |
// Create a sequential model | |
const model = tf.sequential(); | |
// Add a single input layer | |
model.add(tf.layers.dense({units: 3, inputShape: [48], useBias: true})); | |
model.compile({ | |
optimizer: tf.train.adam(), | |
loss: tf.losses.absoluteDifference, | |
metrics: ['mse'], | |
}); | |
await model.fit(inputTensor, labelTensor, { | |
batchSize: 5000, | |
epochs: 50, | |
shuffle: true, | |
}); | |
model.predict(tf.tensor2d([inputs[0]])).print(); | |
console.log(inputs[0]) | |
console.log(labels[0]) |
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