Say I have a NN that generates images. The input of the NN is random noise and the category of the image I want to generate. Now, I have a different program that tells what category of the image actually gets generated or how far the generated image is from the desired category. Can I use this information to train the NN in some way?
(It’s not GAN. It’s different in two ways. There are no “real” inputs compared to generated ones. The discriminator (or evaluator) is not a NN and has nothing to do with tensors.)