I was looking at cycleGAN’s implementation in PyTorch by the author of the paper. In the code author chained the parameters of both generators and passed them to Adam optimizer. I don’t understand the intuition behind training both networks with single optimizer. Shouldn’t we use different optimizers for different networks ? Where am I wrong ?