Confused about custom autograd

I have a custom layer which has no parameters, yet processes the input in a complicated way.
In LuaTorch, I just need to write updateOutput and updateGradInput.

In Pytorch, I do the similar thing in myFunc(inherited from torch.autograd.Function).
As long as I just need to obey It should return as many Variable s as there were inputs, with each of them containing the gradient w.r.t. its corresponding input., then it works well no matter how I process the input data?

correct. For an example, you can look here: http://pytorch.org/docs/master/notes/extending.html