My implementation of GAN, DCGAN, cGAN.
Install dependencies
# clone project
git clone https://github.com/phamgialinhlx/GANs
cd GANs
# [OPTIONAL] create conda environment
conda create -n gan python=3.8 -y
conda activate gan
# install pytorch according to instructions
# https://pytorch.org/get-started/
# install requirements
pip install -r requirements.txtTrain model with default configuration
# train on CPU
python src/train_gan.py trainer=cpu
# train on GPU (default)
python src/train_gan.py You can override any parameter from command line like this
# train on FashionMNIST dataset
python src/train_gan.py datamodule=fashion_mnist
# use cGAN model
python src/train_gan.py model=cgan
# use DCGAN model with small architecture (image size: 28 x 28)
python src/train_gan.py model=small_dcgan Unconditional generation
Conditional generation
