Hi.
I have a short question about “torch.nn.L1Loss()”.
As we know, it is not possible to differentiate |x| when x is zero (because the derivative of |x| is x/|x|).
However, when I used torch.nn.L1Loss() with network, loss.backward() worked…
How is it possible?
Also, would you explain how it is possible to calculate gradient of L1 Loss in pytorch when x is zero?
Thanks.