This is an implementation of Vector Quantized Generative Adversarial Networks (VQGAN) which is a generative model for images which was proposed in Taming Transformers for High-Resolution Image Synthesis. The first stage is to train a variation on VQVAE which uses a discriminator and perceptual loss to retain perceptual quality. The second stage employs the uses a transformer to perform sequence perdiction on the quantized latent representation of the image, after it has been trained the transformer can be prompted with an SOS token to generate a new image.
