This is a project for experiments with GAN's Pytorch implementation Gan's are trained on toy datasets: gaussian grid, gaussian circle, gaussian spiral There are spectral normalization and gradient penalty options with different loss configurations Implemented WGAN-div, LSGAN, original GAN and relativistic GAN Also there is code for visualizing gan training Explore src/toygan.py for more details Spectral normalization in discriminator with gradient penalty. Same with layer normalization in generator
