Now that we've built the infrastructure, we can develop the training methodology in the train script. In this section, we'll also create the run python
and shell scripts that will be used for running everything in the Docker environment.
We're almost at the end! So, make sure you have every one of the following directories and files in your $HOME
directory:
├── data ├── docker │ ├── build.sh │ ├── clean.sh │ ├── Dockerfile │ └── kaggle.json ├── out │ ├── GAN_Model.png │ └── Generator_Model.png ├── README.md ├── run.sh └── src ├── discriminator.py ├── gan.py ├── generator.py ├── loss.py ├── run.py └── train.py
The training script will read in data, process the data for input into the networks, and then train the simGAN model.