Hi,
It might create the the autograd state for Tensors that don’t need it. But it won’t cause any problem no.
If you define a custom autograd.Function, you can use it as any other function: The inputs should have requires_grad=True during the forward if you want to be able to backprop. The grad_output given to your custom backward will have requires_grad=True if you asked for create_graph=True when calling backward and Tensors require gradients.