pytorch

aacdf291 - [JIT] Make aot autograd decompositions usable in JIT, add script for serializing the decompositions (#73938)

[JIT] Make aot autograd decompositions usable in JIT, add script for serializing the decompositions (#73938) Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/73938 This is a first step in porting and making usable all of the decompositions defined in [functorch](https://github.com/pytorch/functorch/blob/main/functorch/_src/decompositions.py#L349) in core and in JIT as well as C++. The decompositions are defined in python, scripted and inlined, and then serialized as C++ code which TorchScript can parse. The workflow is edit python decomposition file then run [tools/codegen/decompositions/gen_jit_decompositions.py](https://github.com/pytorch/pytorch/pull/73938/files#diff-6adef2116be233c3524e3b583e373ab0ffc9169beb6c1f6d96b5d0385e75afa1). Decompositions are mapped to their corresponding aten schemas via the schema in their python def. This allows multiple decompositions for an overloaded op like `aten.var` (shown here in the example). This is just a first PR, i'm sure there will be many follows ups such as: - making these runnable in C++ with simple executor - porting over more decompositions from AOT Autograd - Using opinfos / more robust testing - Categorizing decompositions - Hooking in decompositions at various points of JIT execution Test Plan: Imported from OSS Reviewed By: gchanan Differential Revision: D34938126 Pulled By: eellison fbshipit-source-id: 9559a7cb731982e3a726f2f95af498b84fb09c13 (cherry picked from commit a4e0e748791e378e7e12a9dd0b63fb3c62dc1890)