aniketbiprojit

import { BigQuery } from "@google-cloud/bigquery";

export class BigQueryUtils {
  private bigquery: BigQuery;
  private datasetId: string;

  constructor(datasetId: string) {
    this.bigquery = new BigQuery();
    this.datasetId = datasetId;
  }

aniketbiprojit

template <typename T>
std::vector<T> operator+(std::vector<T> v1, std::vector<T> v2)
{
    std::vector<T> v;
    auto itr1 = v1.begin();
    auto itr2 = v2.begin();
    for (; itr1 < v1.end(); itr1++, itr2++)
    {
        v.push_back(*itr1 + *itr2);
    }

aniketbiprojit

template <typename T>
double square(T elem)
{
    return elem * elem;
}

aniketbiprojit

// https://medium.com/@aniketbiprojit/c-expression-templates-for-optimized-compile-time-evaluation-aff817de04ee
double square(int elem){
  return elem*elem;
}

double square(double elem){
  return elem*elem;
}

aniketbiprojit

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

import tensorflow as tf
import tensorflow.keras as keras
# import tensorflow_federated as tff

from tensorflow_federated.python.tensorflow_libs import tensor_utils
from tensorflow_federated.python.learning.framework import optimizer_utils

aniketbiprojit

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`

aniketbiprojit

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])

aniketbiprojit

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)
		})

aniketbiprojit

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)

aniketbiprojit

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)
	})