Summary:
I accidentally removed this in a merge, breaking a test. Fix for master
Pull Request resolved: https://github.com/pytorch/pytorch/pull/24003
Differential Revision: D16707108
Pulled By: eellison
fbshipit-source-id: 8b59f46e7932b88a7ae246a261c4daf17f23995f
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/23886
This is a series of PRs that will allow us to support adding [padding to conv](https://github.com/pytorch/pytorch/pull/22484) and also reduce the friction of adding method overloads that was brought up in https://github.com/pytorch/pytorch/pull/23266.
Support for overloaded functions following the specification in [PEP 484](https://www.python.org/dev/peps/pep-0484/#function-method-overloading).
The usage is:
```
torch.jit.overload
def add(x: int, y: int) -> int: ...
torch.jit.overload
def add(x: float, y: float) -> float: ...
def add:
return x + y
```
Follow up PRs:
- Add same API for methods
- A couple of cleanups for functions:
- don't require default params specified on the overload as well
- potentially error if invocation could be matched to multiple overloads. now it just chooses the first one, mypy does the same thing currently
Test Plan: Imported from OSS
Differential Revision: D16694863
Pulled By: eellison
fbshipit-source-id: f94f2933bc1c97fa58f31846acfe962b0630068c
Summary:
Before calling `__setstate__` when loading a module, we need to disable
the optimizer since the module's type does not match the values on the
stack (all the tensors will be `UndefinedTensor`)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/23698
Pulled By: driazati
Differential Revision: D16690935
fbshipit-source-id: 71e2238fd25cd16271af478ef21a3cf4e514a462
Summary:
formatting in advance of pr that touches this file bc there is a lot of formatting noise :'(
Pull Request resolved: https://github.com/pytorch/pytorch/pull/23840
Differential Revision: D16659311
Pulled By: eellison
fbshipit-source-id: 7dedaccf9b9c455f97efdcce1c58515eb155d261
Summary:
This fixes up the test suite (mostly just adding `ignore` decorations
to tests that need to call Python function) so that it all passes with
recursive script enabled.
The main user-facing result of this change is that Python functions are
compiled without any decorators, so non-TorchScriptable code must be
decorated with `torch.jit.ignore` (or
`torch.jit.ignore(drop_on_export=True` to maintain the functionality of
the current `ignore`)
Details can be found in #20939
](https://our.intern.facebook.com/intern/diff/16277608/)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/22887
Pulled By: driazati
Differential Revision: D16277608
fbshipit-source-id: 0abd0dc4291cf40651a1719bff813abb2b559640
Summary:
The error for `test_error_stack_module`:
```
Traceback (most recent call last):
File "../test.py", line 35, in <module>
scripted = torch.jit.script(M())
File "/home/davidriazati/other/pytorch/torch/jit/__init__.py", line 1119, in script
return _convert_to_script_module(obj)
File "/home/davidriazati/other/pytorch/torch/jit/__init__.py", line 1825, in _convert_to_script_module
raise e
RuntimeError:
d(int x) -> int:
Expected a value of type 'int' for argument 'x' but instead found type 'str'.
:
at ../test.py:11:12
def c(x):
return d("hello") + d(x)
~ <--- HERE
'c' is being compiled since it was called from 'b'
at ../test.py:14:12
def b(x):
return c(x)
~~~ <--- HERE
'b' is being compiled since it was called from 'forward'
at ../test.py:22:16
def forward(self, x):
return b(x)
~~~ <--- HERE
'forward' is being compiled since it was called from 'forward'
at ../test.py:31:20
def forward(self, x):
return x + self.submodule(x)
~~~~~~~~~~~~~~~~ <--- HERE
```
This also unifies our error reporting in the front end with `ErrorReport`
TODO
* Include module names in message, #22207 should make this easy
](https://our.intern.facebook.com/intern/diff/16060781/)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/22280
Pulled By: driazati
Differential Revision: D16060781
fbshipit-source-id: c42968b53aaddb774ac69d5abbf7e60c23df8eed
Summary:
The code in `python_sugared_value.cpp` to recursively compile methods
was not being tested, so this adds a test for it and fixes some errors
in it
It was necessary to disable any hooks set since (at least in our tests) they would try to export
a half-finished graph since they were being called on recursively
compiled methods
Pull Request resolved: https://github.com/pytorch/pytorch/pull/21862
Differential Revision: D15860314
Pulled By: driazati
fbshipit-source-id: e8afe9d4c75c345b6e1471072d67c5e335b61337
Summary:
Resolves https://github.com/pytorch/lockdown/issues/18
This implements NamedTuple by taking advantage of the existing `names` field in `TupleType`.
TODO: This currently doesn't retain the NamedTuple-ness through serialization. Discussed with suo offline, we can probably make a way to define an anonymous NamedTuple in script (e.g. `NamedTuple('Foo', [('a', int), ('b', float), ('c', List[float])])` and serialize that
TODO: implement support for calling the constructor with kwargs
Pull Request resolved: https://github.com/pytorch/pytorch/pull/21428
Differential Revision: D15741564
Pulled By: jamesr66a
fbshipit-source-id: c077cbcea1880675ca6deb340a9ec78f824a136c
Summary:
- [x] Add tests after https://github.com/pytorch/pytorch/pull/20256 is merged
- Support exporting ScriptModule with inputs/outputs of arbitrarily constructed tuples.
- Moved the assigning of output shapes to after graph conversion to ONNX is completed. By then all tuples in the IR has already been lowered by the pass ```_jit_pass_lower_all_tuples```. If assigning output shapes is required to happen before that, we'll need to hand parse the tuple structures in the graph, and repeat the same logic in ```_jit_pass_lower_all_tuples```. Handling inputs is easier because all tuple information is encoded within the input tensor type.
- Swap the order of ```_jit_pass_lower_all_tuples``` and ```_jit_pass_erase_number_types```. Ops like ```prim::TupleIndex``` relies on index being a scalar. ```_jit_pass_erase_number_types``` will convert these kind of scalars to tensors.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/20784
Reviewed By: zrphercule
Differential Revision: D15484171
Pulled By: houseroad
fbshipit-source-id: 4767a84038244c929f5662758047af6cb92228d3
Summary:
This makes file-line reporting also work for things loaded using `torch.jit.load()` as well as the string frontend (via `CompilationUnit`)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/21217
Differential Revision: D15590838
Pulled By: jamesr66a
fbshipit-source-id: 6b6a12574bf9eca0b83f24f0b50535fda5863243
Summary:
Following on #19747, this implements most of the `torch.jit.script()` changes laid out in #20939.
Still to do:
* Accessing a method from Python does not add it as a `ScriptMethod` (so only `export`ed methods and `forward` are compiled)
* Calling a method other than `forward` on a submodule doesn't work
](https://our.intern.facebook.com/intern/diff/15560490/)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/20708
Pulled By: driazati
Differential Revision: D15560490
fbshipit-source-id: cc7ef3a1c2772eff9beba5f3e66546d2b7d7198a
Summary:
Following on #19747, this implements most of the `torch.jit.script()` changes laid out in #20939.
Still to do:
* Accessing a method from Python does not add it as a `ScriptMethod` (so only `export`ed methods and `forward` are compiled)
* Calling a method other than `forward` on a submodule doesn't work
](https://our.intern.facebook.com/intern/diff/15546045/)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/20708
Pulled By: driazati
Differential Revision: D15546045
fbshipit-source-id: c2c8fe179088ffbdad47198e799a456560655b86
