We define G that generates fake data , and D that measures the probability of either f(x) or f(G(z)) from the real data as  Because G(z) continuously changes during the training, f of traditional GAN also changes.
we define C ∈ R |D| that computes domaincategory of f(x) as where W c is a weight matrix and b c is a bias vector.