var tf = require('@tensorflow/tfjs');

const express = require('express');
const bodyParser = require('body-parser');

app.use(bodyParser.json());
app.use(bodyParser.urlencoded({ extended: true }));

app.listen(3000, () => console.log('WebService run...'));

const model = tf.sequential();
model.add(tf.layers.dense({units: 10, activation: 'sigmoid',inputShape: [2]}));
model.add(tf.layers.dense({units: 1, activation: 'sigmoid',inputShape: [10]}));

model.compile({loss: 'meanSquaredError', optimizer: 'rmsprop'});

const training_data = tf.tensor2d([[0,0],[0,1],[1,0],[1,1]]);
const target_data = tf.tensor2d([[0],[1],[1],[0]]);

for (let i = 1; i < 100 ; ++i) {
 var h = await model.fit(training_data, target_data, {epochs: 30});
   console.log("Loss after Epoch " + i + " : " + h.history.loss[0]);
}

app.post('/test',function(req,res){
  var data_to_test = req.body.data_to_test;

  console.log("data_to_test= "+data_to_test+);

  var predict = model.predict(data_to_test).print();

  res.end(predict);
});