Hi all,
I have a class that represents a shallow neural network (just one layer), which is why I have implemented that layer by myself via matrix multiplications (i.e., without using any of the nn.linear or other preimplemented layers). I have implemented this directly in a loss function and have therefore no forward method. The network trains as expected, but are there any disadvantages or pitfalls when not overwriting that forward method (my class inherits from nn.Module)?