Aniket Biprojit Chowdhury aniketbiprojit

Using JSDOC-Based TypeScript

WebStorm, Rider
- Partial support, not enough intelli hints
- Toggle on TypeScript language service
VSCode

	import os
	os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'

	import tensorflow as tf

	import tensorflow.keras as keras

	model = keras.models.Sequential([
	keras.layers.Dense(10, tf.nn.softmax, input_shape=(784,),kernel_initializer='zeros')
	])

	// Code from https://stackoverflow.com/questions/25024179/reading-mnist-dataset-with-javascript-node-js
	// Author https://stackoverflow.com/users/254532/lilleman
	// Download files from http://yann.lecun.com/exdb/mnist/

	const fs = require('fs')
	const dataFileBuffer = fs.readFileSync(__dirname + '/train-images-idx3-ubyte')
	const labelFileBuffer = fs.readFileSync(__dirname + '/train-labels-idx1-ubyte')

	const load = () => {
	let pixelValues = []

	const tf = require('@tensorflow/tfjs-node')

	const load_model = async () => {
	const model = await tf.loadLayersModel(
	'file:///path/to/directory/tfjs/model.json'
	)
	model.weights.forEach((w) => {
	console.log(w.name, w.shape)
	})

	const load_data = require('./data_loader')

	const data = load_data()

	const X = data.map((elem) => {
	const key = Object.keys(elem)[0]
	return elem[key].map((val) => val / 255)
	})
	console.log(X[0])
	const arr = Array.apply(null, Array(10)).map(() => 0)

	const run = async (X_tensor,y_tensor,revision) => {
	const model = await load_model()
	model.fit(X_tensor, y_tensor, {
	epochs: 10,
	batchSize: 32,
	callbacks: { onBatchEnd },
	})
	.then((info) => {
	console.log('Final accuracy', info.history.acc)
	})

	const cluster = require('cluster')
	const os = require('os')
	const numCPUs = os.cpus().length

	const tf = require('@tensorflow/tfjs-node')

	if (cluster.isMaster) {
	console.log(X[0])
	console.log(y[0], y[1])

	const { exec } = require('child_process')
	const fs = require('fs')

	model_dirs = fs.readdirSync(`${__dirname}/tfjs-models`)

	if (!fs.existsSync('keras_models')) fs.mkdirSync('keras_models')

	model_dirs.forEach((dir) => {
	exec(
	`tensorflowjs_converter --input_format tfjs_layers_model tfjs-models/${dir}/model.json keras_models/${dir}.h5 --output_format keras_saved_model`