Python: Advanced Guide to Artificial Intelligence

Variational autoencoder in TensorFlow

Variational autoencoders are the modern generative version of autoencoders. Let's build a variational autoencoder for the same preceding problem. We will test the autoencoder by providing images from the original and noisy test set.

We will use a different coding style to build this autoencoder for the purpose of demonstrating the different styles of coding with TensorFlow:

1. Start by defining the hyper-parameters:

learning_rate = 0.001n_epochs = 20batch_size = 100n_batches = int(mnist.train.num_examples/batch_size)# number of pixels in the MNIST image as number of inputsn_inputs = 784n_outputs = n_inputs

2. Next, define a parameter dictionary to hold the weight and bias parameters: 

params={}

3. Define ...