I want to implement my custom convolution function using nn.functional.conv2d because forward & backward nn.functional.conv2d’s calculation is optimized in GPU.
Specifically, I want to modify backward method in nn.functional.conv2d.
After calculating gradient (e.g. grad_input, grad_weight), for example, I want to return output with exp():
return grad_input.exp(), grad_weight.exp()
Is there any method?