I have not gotten an answer for that question yet; I also noticed in the linear function Linear(in_features=1000, out_features=1, bias=True: Is there a way I can modify in_features to 4 assuming that I need to do this to fix the dimension error I'm facing.
I'm having trouble determining what the shape of the Tensor would be for DeepESN, GroupedDeepESN, or just ESNBase; I want to use a basic ESN implementation to classify network attacks. I posted a help topic on stackoverflow regarding an error I was facing that's related to the shape of my data: https://stackoverflow.com/questions/73674841/how-do-i-resolve-the-error-indexerror-dimension-out-of-range-expected-to-be-i
I have not gotten an answer for that question yet; I also noticed in the linear function
Linear(in_features=1000, out_features=1, bias=True: Is there a way I can modifyin_featuresto4assuming that I need to do this to fix the dimension error I'm facing.