Judging Generator Performance by Seeing D(G(z))

[ardianumam]

Hi,

Thanks much for creating this repo, it's really useful. I'm curious about this quoted line below, why does D(G(z)) that is close to 0 mean that generator successfully fools the Discriminator? Is it that what we want is maximizing D(G(z)) to be as close as 1, i.e., generator successfully generates fake image (label =0) and the discriminator predicts it as real image (label=1, by having D(G(z)) close to 1)?

gan-pytorch/train.py

Line 142 in 4b38951

# If the value of this probability is close to 0, then it means that the generator has