Torch deploy for fx.grapm_module with non-torch dependencie (#61680)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/61680
This diff enables torch deploy for fx.graph_module with non-torch dependencies . Here are the issues currently preventing this and are fixed in this change:
- Pickle is used as an internal format to transmit objects between interpreters. It needs to serialize python code, but to be able to get the source code for imports from python_code.globals it needs access to the PackageImporter. Currently a regular _reduce_ function is used which doesn't have the notion of custom importer.
- When deserializing pickled objects on an interpreter, it is passing empty globals to exec, thus it will not be able to resolve non-torch imports located in the package. We need to be able to point exec to our custom PackageImporter.
- Subclasses extending fx.graph_module should be able to optionally provide their own Tracer (extending fx.Tracer).
As a solution a new reducer is introduced (_reduce_deploy_) for torch deploy workflow. Reducer will be registered in _deploy.py (entry point for C++ torch deploy API) when saving the object transmitting it between interpreters. It allows us to pass a proper PackageImporter for each interpreter for pickling/unpickling fx.graph_module. It also defines an api for passing custom fx.Tracer when needed.
Test Plan:
Added UT to cover changes.
```
buck test //caffe2/torch/csrc/deploy:test_deploy
```
```
buck test caffe2/test:fx
```
Reviewed By: suo
Differential Revision: D29690088
fbshipit-source-id: 3a8dbe02d5d7e085534aa61b7773c86f0f8c19b0
