jthomas

$ emcc -s WASM=1 -s SIDE_MODULE=1 -s EXPORTED_FUNCTIONS="['_add']" -O1 add.c -o add.wasm
$ zip action.zip index.js add.wasm package.json
updating: index.js (deflated 52%)
updating: add.wasm (deflated 7%)
updating: package.json (deflated 15%)
$ ibmcloud wsk action create wasm action.zip --kind nodejs:10
ok: created action wasm
$ ibmcloud wsk action invoke wasm -r -p a 2 -p b 2
{

jthomas

const INDEX_DOCUMENT = 'index.html'
const ERROR_DOCUMENT = '404.html'

addEventListener('fetch', event => {
  event.respondWith(handleRequest(event.request))
})

/**
 * @param {Request} request
 */

jthomas

"use strict";

// What percentage of invocations should randomly fail?
const ERROR_RATE = 0.25

// Random delay to results being returned (0 -> 10 seconds)
const DELAY_MS = Math.random() * 10000

function should_fail () {
  return Math.random() < ERROR_RATE

jthomas

"use strict";

const ERROR_RATE = 0.25

function should_fail () {
  return Math.random() < ERROR_RATE
}

function main(params) {
  if (!params.a || !params.b) throw new Error('Missing input parameters (a or b).')

jthomas

'use strict';
const { Worker, isMainThread, parentPort, workerData } = require('worker_threads');

const min = 2

function generatePrimes(start, range) {
  const primes = []
  let isPrime = true;
  let end = start + range;
  for (let i = start; i < end; i++) {

jthomas

'use strict';

const min = 2

function main(params) {
  const { start, end } = params
  console.log(params)
  const primes = []
  let isPrime = true;
  for (let i = start; i < end; i++) {

jthomas

'use strict';

const { Worker } = require('worker_threads');
const os = require('os')
const threadCount = os.cpus().length

const compute_primes = async (start, range) => {
  return new Promise((resolve, reject) => {
    let primes = []
    console.log(`adding worker (${start} => ${start + range})`)

jthomas

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

const jpeg = require('jpeg-js');

const NUMBER_OF_CHANNELS = 3
const MODEL_PATH = 'mobilenet/model.json'

let mn_model

jthomas

{
  "name": "tf-js",
  "version": "1.0.0",
  "main": "script.js",
  "license": "MIT",
  "dependencies": {
    "@tensorflow-models/mobilenet": "^0.2.2",
    "@tensorflow/tfjs": "^0.12.3",
    "@tensorflow/tfjs-node": "^0.1.9",
    "jpeg-js": "^0.3.4"

jthomas

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