- Allow image_folder_dataset to normalize inbound images
- ExtensibleTrainer can denormalize images on the output path
- Support .webp - an output from LSUN
- Support logistic GAN divergence loss
- Support stylegan2 TF weight extraction for discriminator
- New injector that produces latent noise (with separated paths)
- Modify FID evaluator to be operable with rosinality-style GANs
For massive upscales (ex: 8x), corruption does almost nothing when applied
at the HQ level. This patch adds support to perform corruption at a specified
intermediary scale. The dataset downscales to this level, performs the corruption,
then downscales the rest of the way to get the LQ image.
