Code implementation – GAN

Building the GAN is a core step with every one of these architectures—we have to be somewhat careful with CycleGAN because it's one of the first times we are going to develop a multilevel model. The GAN model will have six models in adversarial training mode—let's build it!

Getting ready

Every recipe is going to demonstrate the structure that you should have in your directory. This ensures that you've got the right files at each step of the way:

├── data
│   ├── 
├── docker
│   ├── build.sh
│   ├── clean.sh
│   └── Dockerfile
├── README.md
├── run.sh
├── scripts
│   └── create_data.sh
├── src
│   ├── generator.py
│   ├── discriminator.py
│   ├── gan.py

How to do it...

The code is quite simple but the power of Keras really shines here—we are able to place six separate models into adversarial training in under 50 lines of code.

These are the steps for this:

1. Make sure to get your imports for the implementation phase of the code:

#!/usr/bin/env python3
import sys
import numpy...