r/MachineLearning - [D] CycleGAN implementation just learning identity mapping

Hi, don't know where else to ask but I just don't know what else I could try out with my code. I'm trying to reimplement CycleGAN in a Jupyter notbook and (for me) the code looks good, but somehow my generators just learn to map an input to itself (so what I put into it comes out at the other end). What's odd is that the GAN loss is going up, which is probably why the generators don't learn anything meaningful other than the identity mapping. I also got the feeling that my discriminators just learn to distinguish fake from real images, but nothing about horses or zebras. I would be so happy if somebody could give me a hint.