Hi, recently I read a paper named “Large Scale GAN Training for High Fidelity Natural Image Synthesis”, where the scale and bias value are not learned by training, but come from Generation Conditions (Class label embedding and Noise z).
However, I didn’t find any cues to implement this trick/architecture after reading Pytorch documentation about Batchnorm. Do I need to implement it from scratch?
Thanks in advance :>