Hi :),
I’m not sure not anyone else has already noticed (or am I the only one?), but I sometimes get NaNs in torch.randn().
This then leads to nans in the batch norm etc.
Am I doing sth wrong ? Right now I simply fixed it with a while loop that checks if there are any nans in the tensor (but I think there should be a better solution).