Deep Convolutional GAN with TensorFlow and Keras

Note

You can follow along with the code in the Jupyter notebook ch-14b_DCGAN.

In DCGAN, both the discriminator and generator are implemented using a Deep Convolutional Network:

1. In this example, we decided to implement the generator as the following network:

Generator:
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
g_in (Dense)                 (None, 3200)              822400    
_________________________________________________________________
g_in_act (Activation)        (None, 3200)              0         
_________________________________________________________________
g_in_reshape (Reshape)       (None, 5, 5, 128)         0         
_________________________________________________________________
g_0_up2d (UpSampling2D)      (None, 10, 10, 128)       0         
_________________________________________________________________...