Summary:
Methods like `module.named_modules()` returns a container of `shared_ptr<nn::Module>`. Currently the `nn::Module` base class does not have Python bindings. This PR fixes this, and adds more unit tests.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/15193
Differential Revision: D13458713
Pulled By: goldsborough
fbshipit-source-id: 4091fe1b96a1be8db14c6a4307fbacc2b41ff6fe
Summary:
This PR enables C++ frontend modules to be bound into Python and added as submodules of Python modules. For this, I added lots of pybind11 bindings for the `torch::nn::Module` class, and modified the `torch.nn.Module` class in Python to have a new Metaclass that makes `isinstance(m, torch.nn.Module)` return true when `m` is a C++ frontend module. The methods and fields of C++ modules are bound in such a way that they work seamlessly as submodules of Python modules for most operations (one exception I know of: calling `.to()` ends up calling `.apply()` on each submodule with a Python lambda, which cannot be used in C++ -- this may require small changes on Python side).
I've added quite a bunch of tests to verify the bindings and equality with Python. I think I should also try out adding a C++ module as part of some large PyTorch module, like a WLM or something, and see if everything works smoothly.
The next step for inter-op across our system is ScriptModule <-> C++ Frontend Module inter-op. I think this will then also allow using C++ frontend modules from TorchScript.
apaszke zdevito
CC dzhulgakov
Pull Request resolved: https://github.com/pytorch/pytorch/pull/13481
Differential Revision: D12981996
Pulled By: goldsborough
fbshipit-source-id: 147370d3596ebb0e94c82cec92993a148fee50a7
