Generative Adversarial Networks Cookbook

Building the DCGAN structure

1. First, as we did in an earlier neural network model, we need to instantiate the Sequential model type and add the first dense layer, as follows:

def dc_model(self):    model = Sequential()    model.add(Dense(256*8*8,activation=LeakyReLU(0.2),    input_dim=self.LATENT_SPACE_SIZE))    model.add(BatchNormalization()

This first dense layer represents the input layer with a LeakyReLU activation. Also, notice that the input is the latent space size. The first number in the dense layer is the number of filters initialized; however, in the future, you may want to experiment with changing the network's starting value. The paper here starts with 1,024 filters, but starting out with more can help the GAN's convergence.

2. Next, we need ...