Hi,
I think the problem in both cases is that these would correspond to very large convolutions.
Also there are known issues (https://github.com/pytorch/pytorch/issues/32370 25) with cudnn conv3d so might want to try to disable it with torch.backends.cudnn.enabled=False or try the benchmark mode to allow it to discover better algorithms with torch.backends.cudnn.benchmark=True.