pytorch

37bf6c13 - Register DefaultBackend implementations for functional/inplace structured operators (#53037)

Register DefaultBackend implementations for functional/inplace structured operators (#53037) Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/53037 As remarked in #52277 it is easy to give an (inefficient, due to extra redispatches) DefaultBackend implementation of foo and foo_ in terms of foo_out. This patch enables code generation for DefaultBackend in these cases by default for all structured kernels. You can see the payoff in MSNPU extension: it only has to register a kernel for add.out, and it gets add and add_ kernels automatically. The actual code changes are very modest: - When DefaultBackend, call the dispatched (not direct native::) functions to allocate tensors, change device guard, etc - Don't call impl() for DefaultBackend (as it doesn't exist); instead, directly generate a call to at::foo_out to do the actual work. - Do NOT generate DefaultBackend implementation for foo_out. Actually, there is a case to be made for this being a good idea with more infra; see comments inside. Signed-off-by: Edward Z. Yang <ezyang@fb.com> Test Plan: Imported from OSS Reviewed By: bdhirsh Differential Revision: D26731225 Pulled By: ezyang fbshipit-source-id: 939da7cb69f694722ec293e5e42e74a755dd0985