Designing the discriminator module

Next, we continue our journey designing the discriminator module, which will be responsible for telling the real images from the fake ones supplied by the generator module we just designed. The concept behind the architecture is quite similar to that of the generator, with some key differences. The discriminator network receives images of a 32 x 32 x 3 dimension, which it then transforms into various representations as information propagates through deeper layers, until the dense classification layer is reached, equipped with one neuron and a sigmoid activation function. It has one neuron, since we are dealing with the binary classification task of distinguishing fake from real. The sigmoid function ensures a probabilistic output between 0 and 1, indicating how fake or real the network thinks a given image may be. Do also note the inclusion of...