TensorFlow 1.x Deep Learning Cookbook

How to do it...

1. Like always, the first step is to import the necessary modules--TensorFlow, numpy to manipulate input data, matplotlib to plot, and so on:

import tensorflow as tfimport numpy as npfrom tensorflow.examples.tutorials.mnist import input_dataimport matplotlib.pyplot as pltimport math%matplotlib inline

2. Load the data from TensorFlow examples. We have used the standard MNIST database for illustration in all the recipes of this chapter to provide you with a benchmark between different autoencoders.

mnist = input_data.read_data_sets("MNIST_data/")trX, trY, teX, teY = mnist.train.images, mnist.train.labels, mnist.test.images, mnist.test.labels

3. Next, we define the main component of this recipe--the DenoisingAutoEncoder class. The ...