This fixed the bug I was having. Thank you.
I noticed that I have a hard time with recursive neural networks - more specifically, with the dimensions of the tensors they expect as input and output. I was reading Dive into Deep Learning, Section 9.7. and it does a great job of explaining the theory behind encoders, decoders and the like. However, I found it lacking in explaining why the dimensions of inputs and outputs are the way they are.
Is there any resource you could recommend to me that focuses on understanding the input and output shapes of various models that are based on GRUs or LSTMs?
Thank you in advance!