pytorch

e9d9151e - [aot autograd] avoid cloning some inputs unnecessarily when they dont require grad (#96342)

[aot autograd] avoid cloning some inputs unnecessarily when they dont require grad (#96342) When constructing the joint graph, we normally have to clone any inputs that are mutated, so that we can pass in the original, pre-mutation inputs as leaves to autograd. Previously, we were doing this for all mutated inputs - but we only need to do it for inputs that require gradients and participate in autograd. Hopefully this should speed up code like batch norm - I think before this we were unnecessarily cloning the running stats during training. Pull Request resolved: https://github.com/pytorch/pytorch/pull/96342 Approved by: https://github.com/albanD, https://github.com/ezyang