The loss of the discriminator network depends on how it performs on real images and how it performs on fake images generated by the generator network. The loss can be defined as: 

loss = maximize log(D(x)) + log(1-D(G(z)))

So, we need to train the discriminator with real images and the fake images generated by the generator network.