Hi . Thanks for the wonderful explanation. I am new in GAN. And I have a question.
When I train cycleGAN, I found that the discriminator loss decreases and converges, but the generator loss always change not much. So, How to judge whether cycleGAN converges?
Many GAN losses do not converge at all (exception: WGAN) due to the nature of minimax optimization. Your loss curves look quite normal.
Can you tell me what does GAN loss exploding signify and when does that happen?
Sometimes GAN loss might explode if you have an unusual training input (e.g., a white image). But it should be fine as long as the loss is reasonable for most of the times.
Most helpful comment
Many GAN losses do not converge at all (exception: WGAN) due to the nature of minimax optimization. Your loss curves look quite normal.