I am training RNN network.
The network relies on a “hidden” RNN state variable that is saved from cycle to cycle.
I guess when it uses loss.backward(), it will backpropagate through N, where N is the number of cycles since the hidden RNN state has been initiated.
Is it possible to just have the loss.backward() work on the last cycle, even if I don’t reinitialize the hidden state variable.