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| <!DOCTYPE html> | |
| <html lang="en"> | |
| <head> | |
| <meta charset="UTF-8"> | |
| <meta name="viewport" content="width=device-width, initial-scale=1.0"> | |
| <script src="https://cdnjs.cloudflare.com/ajax/libs/brython/3.8.8/brython.js" integrity="sha256-rA89wPrTJJQFWJaZveKW8jpdmC3t5F9rRkPyBjz8G04=" crossorigin="anonymous"></script> | |
| <script src="https://cdnjs.cloudflare.com/ajax/libs/brython/3.8.8/brython_stdlib.js" integrity="sha256-Gnrw9tIjrsXcZSCh/wos5Jrpn0bNVNFJuNJI9d71TDs=" crossorigin="anonymous"></script> |
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| import tensorflow as tf | |
| import numpy as np | |
| import uuid | |
| x = tf.placeholder(shape=[None, 3], dtype=tf.float32) | |
| nn = tf.layers.dense(x, 3, activation=tf.nn.sigmoid) | |
| nn = tf.layers.dense(nn, 5, activation=tf.nn.sigmoid) | |
| encoded = tf.layers.dense(nn, 2, activation=tf.nn.sigmoid) | |
| nn = tf.layers.dense(encoded, 5, activation=tf.nn.sigmoid) | |
| nn = tf.layers.dense(nn, 3, activation=tf.nn.sigmoid) |