Hi, thank you very much for this wonderful example for implementing GAN using Keras.
I have one question, based on what I understood from the theory that there are three stages GAN should be train with:
training D for ground truth data as input with label 1 as output
training D using G output as an input and label 0 as output
same as (2) but with freezing D weights and label 1 as D output
my question is: I didn't see any freezing step in your code. So, is that deferent way of implementation? or I miss something?
Thanks again
Hi, thank you very much for this wonderful example for implementing GAN using Keras. I have one question, based on what I understood from the theory that there are three stages GAN should be train with: