Vanilla GAN

The vanilla GAN will consist of a repeating block architecture similar to the one presented in the original paper. We’ll try to replicate the task of generating MNIST digits using our network.

The overall GAN setup can be seen in the figure below. The figure outlines a generator model with a noise vector $z$ as input and repeating blocks that transform and scale up the vector to the required dimensions. Each block consists of a dense layer followed by LeakyReLU activation and a batch-normalization layer. We simply reshape the output from the final block to transform it into the required output image size.