Overview: Implementing Our First GAN

In this chapter, we will learn the basics of implementing and training GAN models for image synthesis. We will learn to implement a generator and discriminator in a GAN. We will then learn to implement our loss function and use it to train our GAN framework. We will also learn to visualize the samples from our first GAN. We will focus on the well-known CIFAR-10 dataset with 60,000 32 by 32 color images in 10 classes.

Topics covered in this chapter

The following topics will be covered in this chapter:

• Imports

• Implementing the generator and the discriminator

• Auxiliary functions

• Training our GAN