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Create a CNN Model in TFJS
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importScripts("https://cdnjs.cloudflare.com/ajax/libs/tensorflow/1.3.2/tf.min.js", "data.js"); | |
class VisionModelWorker { | |
constructor() { | |
this.model = null; // holds tfjs model | |
this.dataBunch = null; // holds the X and y datasets | |
} | |
create() { | |
this.model = tf.sequential(); | |
this.model.add(tf.layers.conv2d({ inputShape: [28, 28, 1], kernelSize: 3, filters: 8, activation: 'relu' })); | |
this.model.add(tf.layers.maxPooling2d({ poolSize: [2, 2] })); | |
this.model.add(tf.layers.conv2d({ filters: 16, kernelSize: 3, activation: 'relu' })); | |
this.model.add(tf.layers.maxPooling2d({ poolSize: [2, 2] })); | |
this.model.add(tf.layers.flatten()); | |
this.model.add(tf.layers.dense({ units: 128, activation: 'relu' })); | |
this.model.add(tf.layers.dense({ units: 10, activation: 'softmax' })); | |
this.model.summary(); | |
} | |
async getData(forceFetch = false) { | |
if (!!this.dataBunch && !forceFetch) { | |
return; | |
} | |
const numClasses = 10; // number of unique digits to classify | |
this.dataBunch = new Data(); | |
await this.dataBunch.fetchDataAndSetupState(); // TODO: need a tf.tidy() around this | |
this.dataBunch.trainY = tf.oneHot(this.dataBunch.trainY, numClasses); | |
this.dataBunch.testY = tf.oneHot(this.dataBunch.testY, numClasses); | |
} | |
} |
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