Hello,
I would like to implement a new torch.autograd.Function where the gradient is closely related to an intermediate result. Is there a way to store the intermediate result for the backward pass to avoid having to compute it again? (Similar to save_for_backward, but that explicitly isn’t it…)
Thank you
Thomas