Quiz: Building Our First GAN with PyTorch

In this chapter, we used PyTorch to train a GAN model for generating interesting samples. We introduced a classic and well-performing GAN model called DCGAN to generate 2D images. We learned about the core architecture design of GAN models for generating image data and better understood the relationship between latent vectors and generated samples. We dealt with the MNIST dataset and two huge datasets in the CelebA and LSUN datasets. We also consumed a large number of computing cycles.

Test your understanding

You can attempt the quiz below to test your understanding: