Set requires_gradient to help autodiff to prune unneeded gradients (#54374)
Summary:
Fixes https://github.com/pytorch/pytorch/issues/54040
`prim::RequiresGradCheck` guarantees that requires_grad properties
of input tensors will match the profiled, otherwise a fallback path
will be triggered. This allow us to prune off gradients in backward
graph for inputs that don't need gradients. We transfer requires_grad
properties from inputs to the `prim::DifferentiableGraph` onto inputs to the
differentiable graph. Autodiff will inspect these properties and prune
off gradients that aren't required
Pull Request resolved: https://github.com/pytorch/pytorch/pull/54374
Reviewed By: H-Huang
Differential Revision: D27369251
Pulled By: Krovatkin
fbshipit-source-id: 2bce7a2d7f2ec091db9bf4c4b91d8b29edd5be11
