Advanced Deep Learning with Python

Implementing DCGAN

In this section, we'll implement DCGAN, which generates new MNIST images. This example will serve as a blueprint for all GAN implementations in upcoming sections. Let's get started:

1. Let's start by importing the necessary modules and classes:

import matplotlib.pyplot as pltimport numpy as npfrom tensorflow.keras.datasets import mnistfrom tensorflow.keras.layers import \    Conv2D, Conv2DTranspose, BatchNormalization, Dropout, Input,    Dense, Reshape, Flattenfrom tensorflow.keras.layers import LeakyReLUfrom tensorflow.keras.models import Sequential, Modelfrom tensorflow.keras.optimizers import Adam

2. Implement the build_generator function. We'll follow the guidelines that were outlined at the beginning of this section—upsampling ...