<reponame>rparkin1/VAE
network_architecture = \
    dict(n_hidden_recog_1=500, # 1st layer encoder neurons
         n_hidden_recog_2=500, # 2nd layer encoder neurons
         n_hidden_gener_1=500, # 1st layer decoder neurons
         n_hidden_gener_2=500, # 2nd layer decoder neurons
         n_input=784, # MNIST data input (img shape: 28*28)
         n_z=2)  # dimensionality of latent space

vae_2d = train(network_architecture, training_epochs=75)
network_architecture = \
    dict(n_hidden_recog_1=500, # 1st layer encoder neurons
         n_hidden_recog_2=500, # 2nd layer encoder neurons
         n_hidden_gener_1=500, # 1st layer decoder neurons
         n_hidden_gener_2=500, # 2nd layer decoder neurons
         n_input=784, # MNIST data input (img shape: 28*28)
         n_z=2)  # dimensionality of latent space

vae_2d = train(network_architecture, training_epochs=75)
# 1st layer encoder neurons # 2nd layer encoder neurons # 1st layer decoder neurons # 2nd layer decoder neurons # MNIST data input (img shape: 28*28) # dimensionality of latent space