Does Discriminator in GAN Train only on Real Data or it also Trains on Fake Generated Data I have been studying GANs and I got confused in the training phase from the discriminator. Which I think only trains on Real data, not on the generated data which then helps in distinguishing or classifying whether the input is real or fake. I need to confirm that is true what I am thinking or if it does train on fake data generated by the generator as well.

The input to the complete GAN is only the real data, so the complete GAN only trains on the real data.
But the discriminator part of the GAN learns to distinguish between the generated and real data, so it also trains on the generated data.
Imagine the generator does a really bad job in learning to fool the discriminator, e.g. it is only creating complete random data or constant data. Then clearly the discriminator would not become good at detecting the real data and the whole GAN would not work. So the quality of the generator influences the evolution of the discriminator, which shows that the discriminator learns from the generated data, too.
