Variational autoencoder in Keras

In Keras, building the variational autoencoder is much easier and with lesser lines of code. The Keras variational autoencoders are best built using the functional style. So far we have used the sequential style of building the models in Keras, and now in this example, we will see the functional style of building the VAE model in Keras. The steps to build a VAE in Keras are as follows:

  1. Define the hyper-parameters and the number of neurons in the hidden layers and the latent variables layer:
import kerasfrom keras.layers import Lambda, Dense, Input, Layerfrom keras.models import Modelfrom keras import backend as K learning_rate = 0.001batch_size = 100n_batches = int(mnist.train.num_examples/batch_size)# number ...

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