[Project] Balancing the strengths of a generator and discriminator?
In my DCGAN I have 3 hidden layers for both G and D. Previously I would generate images of 64×64 but decided to double that for 128 x 128. I went ahead and also doubled the inputs and outputs of both D and G.
On the first epoch the Discriminator became exremely weak and is not able to distinguish any of the generated images from fake. Could of any of you neural net boys guide me to a place where I can find out how to balance them out?