kuc-arc-f/tfjs_start3-t1-save.html

## tfjs_start3-t1-save.html
<!--
tensorflow.js のテスト  ,回帰モデル
https://www.tensorflow.org/js/guide/layers_for_keras_users
 2019/10/09: 学習model 保存のサンプル
--->
<!DOCTYPE html>
<html>
<head>
    <title>TensorFlow.js Tutorial</title>
    <!-- Import TensorFlow.js -->
    <script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@1.0.0/dist/tf.min.js"></script>
    <!-- Import tfjs-vis -->
    <script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-vis@1.0.2/dist/tfjs-vis.umd.min.js"></script>
    <!-- chart.js -->

</head>

<body>
<h1>tensorflow.js test</h1>
<hr />
<canvas id="myChart" ></canvas>

</body>
<script>
console.log('Hello TensorFlow, t1-1605');
async function test() {
    // Build and compile model.
    const model = tf.sequential();
    model.add(tf.layers.dense({units: 1, inputShape: [1]}));
    model.compile({optimizer: 'sgd', loss: 'meanSquaredError'});

    // Generate some synthetic data for training.
    const xs = tf.tensor2d([[1], [2], [3], [4]], [4, 1]);
    const ys = tf.tensor2d([[1], [3], [5], [7]], [4, 1]);

    var num_pred = 5;
    await model.fit(xs, ys, {epochs: 10 });
//    model.predict(tf.tensor2d([[5]], [1, 1])).print();
    var model_name = "localstorage://my-model-1"
    await model.save(model_name )

    const load_model = await tf.loadLayersModel(model_name);
    console.log('#load_model');
    load_model.predict(tf.tensor2d([[10]], [1, 1])).print();

}
//
test();

</script>
</html>
	<!--
	tensorflow.js のテスト ,回帰モデル
	https://www.tensorflow.org/js/guide/layers_for_keras_users
	2019/10/09: 学習model 保存のサンプル
	--->
	<!DOCTYPE html>
	<html>
	<head>
	<title>TensorFlow.js Tutorial</title>
	<!-- Import TensorFlow.js -->
	<script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@1.0.0/dist/tf.min.js"></script>
	<!-- Import tfjs-vis -->
	<script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-vis@1.0.2/dist/tfjs-vis.umd.min.js"></script>
	<!-- chart.js -->

	</head>

	<body>
	<h1>tensorflow.js test</h1>
	<hr />
	<canvas id="myChart" ></canvas>

	</body>
	<script>
	console.log('Hello TensorFlow, t1-1605');
	async function test() {
	// Build and compile model.
	const model = tf.sequential();
	model.add(tf.layers.dense({units: 1, inputShape: [1]}));
	model.compile({optimizer: 'sgd', loss: 'meanSquaredError'});

	// Generate some synthetic data for training.
	const xs = tf.tensor2d([[1], [2], [3], [4]], [4, 1]);
	const ys = tf.tensor2d([[1], [3], [5], [7]], [4, 1]);

	var num_pred = 5;
	await model.fit(xs, ys, {epochs: 10 });
	// model.predict(tf.tensor2d([[5]], [1, 1])).print();
	var model_name = "localstorage://my-model-1"
	await model.save(model_name )

	const load_model = await tf.loadLayersModel(model_name);
	console.log('#load_model');
	load_model.predict(tf.tensor2d([[10]], [1, 1])).print();

	}
	//
	test();

	</script>
	</html>