I have read this part in the docs. For fear that I might have misunderstood it, I feel I need to ask: Does this feature mean to reduce memory usage by not saving some intermiddle results of the forward path and recompute them when needed in the backward path? If so, would you please show us some example of how to use it in the training process ?