This repository provides a complete implementation of GigaGAN, a cutting-edge GAN architecture for image generation. It includes the main generator-discriminator training code along with 1k to 4k upsampler modules. The implementation incorporates techniques from the author’s lightweight GAN work for faster convergence and improved stability, including skip layer excitation and reconstruction auxiliary loss in the discriminator.