[8/N] Nnapi backend delegation preprocess: New refactored design (#62225)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/62225
Rewrote the preprocess function for Android NNAPI delegate.
Previously, `preprocess()` called `convert_model_to_nnapi()` using Pybind and returned a NnapiModule that is serialized for mobile. Now, `preprocess()` calls a sub-function of `convert_model_to_nnapi()` and returns several preprocessed items (that were previously components of NnapiModule).
Dictionary returned contains:
"shape_compute_module": torch::jit::Module,
"ser_model": torch::Tensor,
"weights": List[torch.Tensor],
"inp_mem_fmts": List[int],
"out_mem_fmts": List[int]
**Purpose and Future:**
The purpose of these changes are to move more implementation from bytecode and Torchscript to the delegate API, since bytecode is less efficient.
Now, only the shape computation uses bytecode. In the future, shape computation will be moved out of Torchscript as well.
**nnapi_backend_preprocess.cpp:** preprocess implementation
**prepare.py**: refactored a portion of `convert_model_to_nnapi()` to `process_for_nnapi()`, so preprocess can get components of NnapiModule
**Test:**
Ran `python test/test_jit.py TestNnapiBackend` and `python test/test_nnapi.py` on OSS successfully
ghstack-source-id: 134444190
Test Plan: Ran `python test/test_jit.py TestNnapiBackend` and `python test/test_nnapi.py` on OSS successfully
Reviewed By: raziel
Differential Revision: D29922279
fbshipit-source-id: cadcf8908d8a745dc7abbe286e97d6ead937d4ab
