Layered LSTM Recurrent Neural Network

Overview

Code

let learningRate = 0.01;
const opt_adam = tf.train.adam(learningRate);
model.compile({ optimizer: opt_adam, loss: 'meanSquaredError'});

//run on data
let inputs = [[1,1],[1,1],[1,1],[1,1],[1,1],[1,1],[1,1]];
let outputs = [1,1,1,1,1,1,1];

const xs = tf.tensor2d(inputs, [inputs.length, inputs[0].length]);
const ys = tf.tensor2d(outputs, [outputs.length, 1]).reshape([outputs.length, 1]);

let callback = (epoch,log)=>{};
let epochs = 10;
let batch_size = 1;
const hist = await model.fit(xs, ys,
{ batchSize: batch_size, epochs: epochs, callbacks: {
  onEpochEnd: async (epoch, log) => { callback(epoch, log); }}});