The training loss looks alright. I used the provided shapes to check the input and target and think y = (y.long()).view(-1) should be unnecessary. Could you verify it?
The test loss might be alright. I’m not too familiar with your use case, but note that you are not applying the normalization. You’ve added the noise addition inside your loop, which should be fine, but I’m not sure, if you need the normalization in your test loop. If so, consider writing it as another class method you could call similar to model.transmitter.


Not sure about it and it should be use case dependent.


Also looks alright.


What kind of issues are you seeing using PyTorch?
Is this regarding using the GPU or some other errors?