NatuMyers/tfexample1.html

## tfexample1.html

<html>
   <head>
      <title>Tensor Flow</title>
      <script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@0.6.1"></script>
      <script>
         const nr_epochs=2048;  // higher=better but slower
         var tfinterface;
         const model = tf.sequential();

         function initTF() {

         // 1. TRAINING DATA - learn this 10x table
               const xs = tf.tensor2d([1,2,3,4,5], [5,1]);
               const ys = tf.tensor2d([10,20,30,40,50], [5,1]);


         // 2. ML MODEL - linear regression model
               model.add(tf.layers.dense({units: 1, inputShape: [1]}));
               // Prep for training
               model.compile({loss: 'meanSquaredError', optimizer: 'sgd'});

               // train -- the higher the number the more accurate you'll get (but longer run time)
               tfinterface=model.fit(xs,ys,{epochs: nr_epochs});
         }

         // 3. WRAPPER AROUND PREDICT
         function predict(n) {

               return tfinterface.then(()=> { return model.predict(tf.tensor2d([n],[1,1])); });

         }

         // Helper for form
         function formpredict(v,r) {
            predict(v).then(function(res) {
         //   alert(res.get([0]));
            r.innerHTML=res.get([0]);
            });

         }


      </script>
   </head>

   <!-- HTML -->

   <body onLoad='initTF();'>
      <p>
      <div id='res'>Wait</div>
      <p>
      <form name='iForm' onSubmit='formpredict(this.val.value,document.getElementById("res")); return false;')>
         <script>
            document.getElementById("res").innerHTML="&nbsp;";

         </script>
         Input Number: <input name='val'><input type=submit>
      </form>
   </body>
</html>

	<html>
	<head>
	<title>Tensor Flow</title>
	<script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@0.6.1"></script>
	<script>
	const nr_epochs=2048; // higher=better but slower
	var tfinterface;
	const model = tf.sequential();

	function initTF() {

	// 1. TRAINING DATA - learn this 10x table
	const xs = tf.tensor2d([1,2,3,4,5], [5,1]);
	const ys = tf.tensor2d([10,20,30,40,50], [5,1]);



	// 2. ML MODEL - linear regression model
	model.add(tf.layers.dense({units: 1, inputShape: [1]}));
	// Prep for training
	model.compile({loss: 'meanSquaredError', optimizer: 'sgd'});

	// train -- the higher the number the more accurate you'll get (but longer run time)
	tfinterface=model.fit(xs,ys,{epochs: nr_epochs});
	}

	// 3. WRAPPER AROUND PREDICT
	function predict(n) {

	return tfinterface.then(()=> { return model.predict(tf.tensor2d([n],[1,1])); });

	}

	// Helper for form
	function formpredict(v,r) {
	predict(v).then(function(res) {
	// alert(res.get([0]));
	r.innerHTML=res.get([0]);
	});

	}


	</script>
	</head>

	<!-- HTML -->

	<body onLoad='initTF();'>
	<p>
	<div id='res'>Wait</div>
	<p>
	<form name='iForm' onSubmit='formpredict(this.val.value,document.getElementById("res")); return false;')>
	<script>
	document.getElementById("res").innerHTML=" ";

	</script>
	Input Number: <input name='val'><input type=submit>
	</form>
	</body>
	</html>