Code implementation – discriminator

The discriminator in SimGAN is a fairly simple Convolutional Neural Network (CNN) with a small twist at the end—it outputs the likelihood of simulated and real. In this section, we'll also make use of a function from the loss class we built earlier.

Getting ready

We've built a set of loss functions and the generator class, so now it's time to build the discriminator class. You should see the following structure in your directory:

├── data
├── docker
│   ├── build.sh
│   ├── clean.sh
│   ├── Dockerfile
│   └── kaggle.json
├── imgs
│   ├── create_token.png
│   ├── kaggle_signup.png
│   ├── MyAccount.png
│   ├── refiner_network_training.png
│   └── simGAN_network.png
├── out
│   └── Generator_Model.png
├── README.md
├── run.sh
└── src
 ├── discriminator.py
 ├── generator.py
 ├── loss.py

How to do it...

The discriminator is very similar to other discriminators we've built in previous chapters. In this case, we're essentially building a CNN with a slightly different...