/basic_regression.js
Last active May 24, 2019
Tensorflow.js demo
| const callbacks = { | |
| onEpochEnd: async (epoch, logs) => { | |
| console.log("epoch: " + epoch + JSON.stringify(logs)) | |
| } | |
| }; | |
| // 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]); | |
| // Build and compile model. | |
| async function basicRegression(){ | |
| // Build a sequential model | |
| const model = tf.sequential(); | |
| model.add(tf.layers.dense({units: 1, inputShape: [1]})); | |
| model.add(tf.layers.dense({units: 1, inputShape: [1]})); | |
| model.compile({optimizer: 'sgd', loss: 'meanSquaredError'}); | |
| // Train model with fit(). | |
| await model.fit(xs, ys, {epochs: 100, validationSplit: 0.1, callbacks: callbacks}); | |
| // Run inference with predict(). | |
| model.predict(tf.tensor2d([[5]], [1, 1])).print(); | |
| } | |
| // Create a basic regression model | |
| basicRegression(); |
| <html lang="en"> | |
| <head> | |
| <meta charset="UTF-8"> | |
| <meta name="viewport" content="width=device-width, initial-scale=1.0"> | |
| <meta http-equiv="X-UA-Compatible" content="ie=edge"> | |
| <!-- load Tensorflow.js --> | |
| <script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@1.0.0/dist/tf.min.js"></script> | |
| </head> | |
| <body> | |
| <h1>Tensorflow.js Core API</h1> | |
| <!-- <script src="index.js"></script> --> | |
| <script type="text/javascript"> | |
| </script> | |
| </body> | |
| </html> |
| <html lang="en"> | |
| <head> | |
| <meta charset="UTF-8"> | |
| <meta name="viewport" content="width=device-width, initial-scale=1.0"> | |
| <meta http-equiv="X-UA-Compatible" content="ie=edge"> | |
| <!-- load Tensorflow.js --> | |
| <script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@1.0.0/dist/tf.min.js"></script> | |
| </head> | |
| <body> | |
| <h1>Tensorflow.js Core API</h1> | |
| <!-- <script src="index.js"></script> --> | |
| <script type="text/javascript"> | |
| const a = tf.tensor([1, 2, 3, 4]); | |
| const b = tf.tensor([10, 20, 30, 40]); | |
| const y = a.add(b); // equivalent to tf.add(a, b) | |
| const z = a.mul(b); // equivalent to tf.mul(a, b) | |
| y.print(); | |
| z.print(); | |
| </script> | |
| </body> | |
| </html> |
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