Thank you very much.
I have realized that when I saw the code:
https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function 7
In the forward procedure,



def forward(ctx, i):
    result = i.exp()
    ctx.save_for_backward(result)
    return result




it saves the results for backward and the memory footprint is reused.