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Summary:
Adds support for `__getstate__` and `__setstate__` on modules that are called as part of export (`torch.save()`) and import (`torch.jit.load`).
* `__getstate__` and `__setstate__` must be TorchScript functions with the signatures `() -> T` and `(T) -> None` respectively
* The results of `__getstate__` are stored using the pickler in `states.pkl` with one for each module in definition order (`__getstate__` returns `None` by default if an imlpementation is not provided)
* This prevents sharing between `__getstate__` and attributes, but this should be fine since their use is mostly unrelated (attributes are for storing values to be used in script methods, `__getstate__` for running arbitrary computations during import)
Follow up
* Somehow replacing `__getstate__`/`__setstate__` with a `ScriptMethodStub` makes `MyScriptModule().__getstate__()` call `ScriptModule.__getstate__()` when used in Python. This should be fixed so semantics in Python are preserved, but it doesn't affect the typical usage.
](https://our.intern.facebook.com/intern/diff/15287161/)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/20242
Pulled By: driazati
Differential Revision: D15287161
fbshipit-source-id: b3f5f33ab74a21a89e6d15460af63aff75cab2d8
Caffe2
Caffe2 is a lightweight, modular, and scalable deep learning framework. Building on the original Caffe, Caffe2 is designed with expression, speed, and modularity in mind.
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