gonzaloruizdevilla

from sklearn.datasets import load_iris
from sklearn.model_selection import train_test_split
from sklearn.neighbors import KNeighborsClassifier
import numpy as np 

gonzaloruizdevilla

private async Task SuccessfulLogin (IDialogContext context, IAwaitable<GetTokenResponse> tokenResponse) {
        var token = await tokenResponse;
        var client = new SimpleGraphClient (token.Token);
        var me = await client.GetMe ();
        await context.PostAsync ($”Login successful — welcome {me.DisplayName}”);
}

public static async Task Signout (IDialogContext context) {
    await context.SignOutUserAsync (ConnectionName);
    await context.PostAsync ($”You have been signed out.”);

gonzaloruizdevilla

[LuisIntent (“adauthentication”)]
public async Task ADAuthentication (IDialogContext context, LuisResult result) {
    context.Call (CreateGetTokenDialog (), SuccessfulLogin);
}

[LuisIntent (“whoami”)]
public async Task WhoAmI (IDialogContext context, LuisResult result) {
    context.Call (CreateGetTokenDialog (), ListMe);
}

gonzaloruizdevilla

[LuisModel("endpointID", "endpointPassword")]    
[Serializable]
 public class LUISDialog : LuisDialog<ProjectCreator> {
     private readonly BuildFormDelegate<ProjectCreator> TouchProject;
     private static string ConnectionName = ConfigurationManager.AppSettings["ConnectionName"];
     public LUISDialog(BuildFormDelegate<ProjectCreator> touchProject) {
            this.TouchProject = touchProject;
     }
}

gonzaloruizdevilla

async function maybeInstantiateStreaming(path, ...opts) {
  // Start the download asap.
  const f = fetch(path);
  try {
    // This will throw either if `instantiateStreaming` is
    // undefined or the `Content-Type` header is wrong.
    return WebAssembly.instantiateStreaming(
      f,
      ...opts
    );

gonzaloruizdevilla

async function run() {
  const {instance} = await WebAssembly.instantiateStreaming(
    fetch("./add.wasm"),
    env: { abort: () => console.log("Abort!") }
  );
  const r = instance.exports.add(1, 2);
  console.log(r);
}
run();

gonzaloruizdevilla

//retrieve image pixels (4 bytes per pixel: RBGA)
const data = imageData.data;
//copy to bytes to shared memory
mem.set(data);

//invoque 'fn'  Wasm filter. We need to inform of the image byte size
const byteSize = data.length;
instance.exports[fn](byteSize, ...args);

//copy the response from the shared memory into the canvas imageData

gonzaloruizdevilla

//A memory created by JavaScript or in WebAssembly code will be accessible and mutable from both JavaScript and WebAssembly.

const memory = new WebAssembly.Memory({ initial:initial * 2 });

//Instantiating Wasm module

const importObject = { env: { memory, abort: () => console.log("Abort!") }};
const {instance} = await WebAssembly.instantiateStreaming(
    fetch("./build/untouched.wasm"),
    importObject

gonzaloruizdevilla

/// <reference path="../node_modules/assemblyscript/dist/assemblyscript.d.ts" />

export function invert(byteSize: i32): i32 {
  for (var i = 0; i < byteSize; i += 4) {
    let pos = i + byteSize; 
    store<u8>(pos, 255 - load<u8>(i));
    store<u8>(pos + 1, 255 - load<u8>(i + 1));
    store<u8>(pos + 2, 255 - load<u8>(i + 2));
    store<u8>(pos + 3, 255);
  }

gonzaloruizdevilla

function invert(data) {
    for (var i = 0; i < data.length; i += 4) {
        data[i]     = 255 - data[i];     
        data[i + 1] = 255 - data[i + 1]; 
        data[i + 2] = 255 - data[i + 2]; 
    }
};

function grayscale(data){
    for (var i = 0; i < data.length; i += 4) {