Hi. I am on the latest version of PyTorch, and also on the latest version of CUDA drivers, yet the problem still exists.
My environment is pretty common (ubuntu, 2080ti, etc), and the code I provided to reproduce this bug is pretty simple to run (less than 5 seconds including copy-paste the code to a terminal and see the result), also one can easily remove all the “spectral_norm” in the provided code and see that the problem still there.
I actually think this is a pretty big bug since I cannot take advantage of multi-GPU training if my network is designed in this multi-branch way. I am also curious why such a bug is not raising more attention.  It makes me assume this is an issue caused by my side. If it is indeed so, could you please help me verify it by testing the provided code and let me know if it works just fine on your side?