Generative Adversarial Networks on MNIST dataset using pytorch. This code is tested on python 3.7. For training tips and network architecture on GANs I took the help from here
- Download dataset using download_dataset.sh. Rest of the code assumes the dataset is present in data directory
This downloads the dataset from the official site, unzips it and writes all the image files in the format counter-label.jpg With counter varying from 00000 to 60000 and label varying from 1 to 9
- Run training using src/main.py. You need to give a unique id to your run with option --uid UNIQUE_ID
