In this section, we will provide you with an overview of the various choices you can make when it comes to designing the architecture of GAN models, and even deep learning models in general. It is always okay to directly borrow the model architectures you see in papers. It is also imperative to know how to adjust a model and create a brand new model from scratch, according to the practical problems at hand. Other factors, such as GPU memory capacity and expected training time, should also be considered when we design our models. We will talk about the following:
- Overall model architecture design
- Choosing a convolution operation method
- Choosing a downsampling operation method
