Summary:
The use case for making this PR is the following bug :
(with F = torch.nn.functional)
`F.max_pool2d.__module__` is `torch._jit_internal`
`F.max_pool2d.__name__` is `fn`
With this PR you get:
`F.max_pool2d.__module__` is `torch.nn.functional`
`F.max_pool2d.__name__` is `max_pool2d`
Pull Request resolved: https://github.com/pytorch/pytorch/pull/16922
Differential Revision: D14020053
Pulled By: driazati
fbshipit-source-id: c109c1f04640f3b2b69bc4790b16fef7714025dd
Summary:
Adds a decorator `torch.jit.ignore` for Python functions that tells the compiler to skip over these Python values, putting a `prim::Error` in their place which always throws an exception when run.
This lets you have Python-only code in your model in an explicit way, which is useful for debugging, and still be able to save/load the model.
Fixes#15815
Pull Request resolved: https://github.com/pytorch/pytorch/pull/16055
Differential Revision: D13797286
Pulled By: driazati
fbshipit-source-id: 29d36776608ec101649a702952fc6ff3c27655b1
Summary:
Adds `List` to eval environment for type lines and allows `List` to be used on PythonOps (follows the same style as the `Tuple` code), fixes#15661
Pull Request resolved: https://github.com/pytorch/pytorch/pull/15721
Differential Revision: D13578540
Pulled By: driazati
fbshipit-source-id: fce54dc3c0931d8b017b2e3483f0ac53826dda94
Summary:
Allows 2 functions that are boolean dispatched to have no docstrings (the only case that will fail now is if both functions have docstrings)
Fixes#15281
Pull Request resolved: https://github.com/pytorch/pytorch/pull/15306
Differential Revision: D13494884
Pulled By: driazati
fbshipit-source-id: 65fec39ae03a7d6a68ad617c9b270faeb1617930
Summary:
This PR adds a polyfill for `typing.List` for Python versions that don't
support `typing` as a builtin. It also moves the type defintions from
`annotations.py` so that they can be used in `torch.nn`.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/14482
Differential Revision: D13237570
Pulled By: driazati
fbshipit-source-id: 6575b7025c2d98198aee3b170f9c4323ad5314bd
Summary:
This PR allows to overload functions based on the value of a parameter (so long as it is a constant). See max_pool1d for an example usage.
This is the first step in enabling the use of max_pool functions for the standard library that can return `Tensor` or `Tuple[Tensor, Tensor]` based on the `return_indices` flag. This will give the JIT identical results to the Python versions of the functions.
Fixes#14081
Pull Request resolved: https://github.com/pytorch/pytorch/pull/14425
Differential Revision: D13222104
Pulled By: driazati
fbshipit-source-id: 8cb676b8b13ebcec3262234698edf4a7d7dcbbe1
Summary:
This PR allows to overload functions based on the value of a parameter (so long as it is a constant). See `max_pool1d` for an example usage.
This is the first step in enabling the use of `max_pool` functions for the standard library that can return `Tensor` or `Tuple[Tensor, Tensor]` based on the `return_indices` flag. This will give the JIT identical results to the Python versions of the functions.
Depends on #14232 for `Optional[BroadcastingList[T]]`
Pull Request resolved: https://github.com/pytorch/pytorch/pull/14081
Differential Revision: D13192228
Pulled By: driazati
fbshipit-source-id: fce33c400c1fd06e59747d98507c5fdcd8d4c113
Summary:
`inspect.stack()` calls are slow since they access a bunch of extra info about the frame. This PR instead uses `inspect.currentframe()` and goes up the stack until it reaches the correct frame. [Context](stackoverflow.com/questions/17407119/python-inspect-stack-is-slow)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/12859
Differential Revision: D10509912
Pulled By: driazati
fbshipit-source-id: b85325adf1b3c85a1a3a82e96e567b8be498531b
Summary:
Adds support for weak script modules created that get compiled to `ScriptModule`s once added as a submodule of a `ScriptModule`:
```python
weak_module
class Test(torch.nn.Module):
...
weak_script_method
def forward(self, x):
...
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/12682
Differential Revision: D10458626
Pulled By: driazati
fbshipit-source-id: 10ae23cb83cdafc4646cee58f399e14b2e60acd4
Summary:
* Moves `weak_script` annotation to `torch/_jit_internal.py` folder to resolve dependency issue between `torch.jit` and `torch.nn`
* Add `torch._jit.weak_script` to `tanhshrink` and `softsign`, their tests now pass instead of giving an `unknown builtin op` error
* Blacklist converted `torch.nn.functional` functions from appearing in the builtin op list if they don't actually have corresponding `aten` ops
Pull Request resolved: https://github.com/pytorch/pytorch/pull/12723
Differential Revision: D10452986
Pulled By: driazati
fbshipit-source-id: c7842bc2d3ba0aaf7ca6e1e228523dbed3d63c36
