For me, this manifested as the test failing when my folder
had a hyphen in it. But this should fix it once and for
all.
Signed-off-by: Edward Z. Yang <ezyangfb.com>
Pull Request resolved: https://github.com/pytorch/pytorch/pull/75564
Approved by: https://github.com/suo
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/74353
Repatched `d00de0d43598522b8f6ab2de553b6aaf6768faa5` by Nora Belrose (norabelrose). With following changes:
* Register fake source of generated methods in linecache so that inspect.get_source will succeed.
* this patching is only triggered if the given dataclass passed to torch.jit.script previously. Effectively we make this feature opt-in.
## Original Summary:
Fixes#72901.
Since we can't get access to the source code for synthesized magic methods on dataclasses, we have to synthesize our own versions. torch/jit/_dataclass_impls.py has the code that does this.
What's supported
Synthesized __init__, __eq__, and the comparison magic methods when order=True is set on the dataclass decorator
Default values for fields
__post_init__, including using InitVar fields inside of __post_init__, on Python 3.8+
Overriding __eq__ or any of the comparison magic methods to provide your own implementation
What's not supported
Default factory initializers for fields
Frozen dataclasses
InitVar on Python 3.7
__repr__ and __hash__ (these are actually implemented, but the TorchScript interpreter won't call them)
Using the != operator on dataclasses inside TorchScript; this is because TorchScript requires that you implement __ne__ to use this operator, whereas in regular Python the != operator will resolve to the negation of whatever is returned by __eq__ if there's no __ne__. Dataclasses don't actually synthesize an __ne__ method for this reason. I've been toying with different ways to fix this but != is not working in this PR at the moment.
Test Plan:
unittest
Also run previously failed test:
```
buck test mode/dev-nosan //fblearner/flow/projects/fluent2/definition/transformers/contrib/faim/test:tests -- --exact 'fblearner/flow/projects/fluent2/definition/transformers/contrib/faim/test:tests - test_mixmatch_multiclass (fblearner.flow.projects.fluent2.definition.transformers.contrib.faim.test.faim_mixmatch_test.TestFaimTransformerMixMatch)'
```
passes
Differential Revision: D35206262
Pull Request resolved: https://github.com/pytorch/pytorch/pull/74889
Approved by: https://github.com/zhxchen17
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/74353
Repatched `d00de0d43598522b8f6ab2de553b6aaf6768faa5` by Nora Belrose (norabelrose). With following changes:
* Register fake source of generated methods in linecache so that inspect.get_source will succeed.
* this patching is only triggered if the given dataclass passed to torch.jit.script previously. Effectively we make this feature opt-in.
## Original Summary:
Fixes#72901.
Since we can't get access to the source code for synthesized magic methods on dataclasses, we have to synthesize our own versions. torch/jit/_dataclass_impls.py has the code that does this.
What's supported
Synthesized __init__, __eq__, and the comparison magic methods when order=True is set on the dataclass decorator
Default values for fields
__post_init__, including using InitVar fields inside of __post_init__, on Python 3.8+
Overriding __eq__ or any of the comparison magic methods to provide your own implementation
What's not supported
Default factory initializers for fields
Frozen dataclasses
InitVar on Python 3.7
__repr__ and __hash__ (these are actually implemented, but the TorchScript interpreter won't call them)
Using the != operator on dataclasses inside TorchScript; this is because TorchScript requires that you implement __ne__ to use this operator, whereas in regular Python the != operator will resolve to the negation of whatever is returned by __eq__ if there's no __ne__. Dataclasses don't actually synthesize an __ne__ method for this reason. I've been toying with different ways to fix this but != is not working in this PR at the moment.
Test Plan:
unittest
Also run previously failed test:
```
buck test mode/dev-nosan //fblearner/flow/projects/fluent2/definition/transformers/contrib/faim/test:tests -- --exact 'fblearner/flow/projects/fluent2/definition/transformers/contrib/faim/test:tests - test_mixmatch_multiclass (fblearner.flow.projects.fluent2.definition.transformers.contrib.faim.test.faim_mixmatch_test.TestFaimTransformerMixMatch)'
```
passes
Reviewed By: zhxchen17
Differential Revision: D34808842
fbshipit-source-id: 02f807cff1ea99e606333960225c71a239743a4b
(cherry picked from commit ec885a2bc04f9e5f65838fa5704d9a05815ebd37)
Summary:
Original commit changeset: f5a792555c88
Original Phabricator Diff: D34398107 (d00de0d435)
Backing out as this broke fluent2 tests
Test Plan: sandcastle
Reviewed By: qihqi
Differential Revision: D34597363
fbshipit-source-id: 26bbe64b981aeb53b901cda61557614d9f28700e
(cherry picked from commit f17adfed8125ef84efaf2c8923c11a751eb7fb98)
Summary:
Fixes https://github.com/pytorch/pytorch/issues/72901.
Since we can't get access to the source code for synthesized magic methods on dataclasses, we have to synthesize our own versions. `torch/jit/_dataclass_impls.py` has the code that does this.
What's supported
- Synthesized `__init__`, `__eq__`, and the comparison magic methods when `order=True` is set on the dataclass decorator
- Default values for fields
- `__post_init__`, including using `InitVar` fields inside of `__post_init__`, on Python 3.8+
- Overriding `__eq__` or any of the comparison magic methods to provide your own implementation
What's not supported
- Default factory initializers for fields
- Frozen dataclasses
- `InitVar` on Python 3.7
- `__repr__` and `__hash__` (these are actually implemented, but the TorchScript interpreter won't call them)
- Using the `!=` operator on dataclasses inside TorchScript; this is because TorchScript requires that you implement `__ne__` to use this operator, whereas in regular Python the `!=` operator will resolve to the negation of whatever is returned by `__eq__` if there's no `__ne__`. Dataclasses don't actually synthesize an `__ne__` method for this reason. I've been toying with different ways to fix this but `!=` is not working in this PR at the moment.
qihqi
Pull Request resolved: https://github.com/pytorch/pytorch/pull/73066
Reviewed By: mrshenli
Differential Revision: D34398107
Pulled By: qihqi
fbshipit-source-id: f5a792555c88f3631f97837a96687e4890660a32
(cherry picked from commit ea7f077dc49a4ee75ca0d1409aedd85228952881)
Summary:
**Summary**: This commit solves the first part of https://github.com/pytorch/pytorch/issues/52306, which disallows type annotations on instance attributes inside any method other than the constructor.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/67051
Test Plan:
Added test to test_types.py.
**Reviewers**: Zhengxu Chen
**Subscribers**: Zhengxu Chen, Yanan Cao, Peng Wu, Yining Lu
**Tasks**: T103941984
**Tags**: pytorch
**Fixes** https://github.com/pytorch/pytorch/issues/52306
Reviewed By: zhxchen17
Differential Revision: D31843527
Pulled By: andrewor14
fbshipit-source-id: 624879ae801621e367c59228be8b0581ecd30ef4
Summary:
This PR is created to replace https://github.com/pytorch/pytorch/pull/53180 PR stack, which has all the review discussions. Reason for needing a replacement is due to a messy Sandcastle issue.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/64234
Reviewed By: gmagogsfm
Differential Revision: D30656444
Pulled By: ansley
fbshipit-source-id: 77536c8bcc88162e2c72636026ca3c16891d669a
Summary:
Creates a helper function to refine the types into a torchScript compatible format in the monkeytype config for profile directed typing
Pull Request resolved: https://github.com/pytorch/pytorch/pull/62444
Reviewed By: malfet
Differential Revision: D30548159
Pulled By: nikithamalgifb
fbshipit-source-id: 7c09ce5f5e043d069313b87112837d7e226ade1f
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/59956
Issue #50175. Basically two things need to be checked and are lacking currently:
1. Overload declarations should always have a single `pass` statement as the body.
2. There should be always an implementation provided for decls which doesn't
have the torch.jit._overload decorator. So in this case we need to check
whether we are actually compiling a function body with decorator ahead.
Test Plan:
python test/test_jit.py TestScript.test_function_overloads
Imported from OSS
Reviewed By: gmagogsfm
Differential Revision: D29106555
fbshipit-source-id: 2d9d7df2fb51ab6db0e1b726f9644e4cfbf733d6
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/55172
Description:
This is part 1 of series of PRs for supporting torch.jit.ignore as context manager. Following features are implemented in this PR:
- Unique name for the registered function under torch.jit.frontend module. The unique name is generated based on the file name and line number of context manager
- Forcing user to explicitly annotate the input and outputs.
- No side effects are considered.
Test Plan: Imported from OSS
Reviewed By: gmagogsfm
Differential Revision: D27895283
Pulled By: tugsbayasgalan
fbshipit-source-id: 5d36d9aa5d457055a6bb1676f264647a745ec36a
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/52881
**This PR adds:**
1. logic to parse complex constants (complex literals of the form `bj`)
2. logic to parse complex lists
3. support for complex constructors: `complex(tensor/int/float/bool, tensor/int/float/bool)`
4. Limited operator support
- `add`, `sub`, `mul`, `torch.tensor`, `torch.as_tensor`
**Follow-up work:**
1. Add complex support for unary and other registered ops.
2. support complex constructor with string as input (this is supported in Python eager mode).
3. Test all emitXYZ for all XYZ in `ir_emitter.cpp` (currently only emitConst, emitValueToTensor are tested). e.g., test loops etc.
4. onnx doesn't support complex tensors, so we should error out with a clear and descriptive error message.
Test Plan: Imported from OSS
Reviewed By: bdhirsh
Differential Revision: D27245059
Pulled By: anjali411
fbshipit-source-id: af043b5159ae99a9cc8691b5a8401503fa8d6f05
Summary:
Currentlt classmethods are compiled the same way as methods - the first argument is self.
Adding a fake statement to assign the first argument to the class.
This is kind of hacky, but that's all it takes.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/49967
Reviewed By: gchanan
Differential Revision: D25841378
Pulled By: ppwwyyxx
fbshipit-source-id: 0f3657b4c9d5d2181d658f9bade9bafc72de33d8
Summary:
========
Fixes #{42915}
This commit adds support for Bitwise Shorthands in TorchScript, i.e : |=,&=,^=,<<=,>>=,**=
Testing:
======
This commit also adds test for the above fix in test_jit.py
The test can be invoked by
pytest -k augassign test/test_jit.py
Here is a snapshot of the testing:
<img width="1238" alt="image" src="https://user-images.githubusercontent.com/70345919/93105141-8f9f5300-f663-11ea-836b-3b52da6d2be5.png">
Pull Request resolved: https://github.com/pytorch/pytorch/pull/44621
Reviewed By: mrshenli
Differential Revision: D23906344
Pulled By: nikithamalgifb
fbshipit-source-id: 4c93a7430a625f698b163609ccec15e51417d564
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/48876
**Summary**
This commit adds support for `del` statements with multiple targets.
Targets are deleted left-to-right just like Python.
**Test Plan**
This commit updates the `TestBuiltins.test_del_multiple_operands` unit
test to actually test that multiple deletion works instead of asserting
that an error is thrown.
**Fixes**
This commit fixes#48635.
Test Plan: Imported from OSS
Reviewed By: ZolotukhinM
Differential Revision: D25386285
Pulled By: SplitInfinity
fbshipit-source-id: c0fbd8206cf98b2bd1b695d0b778589d58965a74
Summary:
In 3.9, `ast.Index` and `ast.ExtSlice` are deprecated, so:
- `ast.parse('img[3]', model='eval')` evaluates to
`Expression(body=Subscript(value=Name(id='img'), slice=Constant(value=3)))` by 3.9,
but was previously evaluated to `Expression(body=Subscript(value=Name(id='img'), slice=Index(value=Num(n=3))))`
- and `ast.parse('img[..., 10:20]', mode='eval')` is evaluated to
`
Subscript(value=Name(id='img'),slice=Tuple(elts=[Constant(value=Ellipsis),Slice(lower=Constant(value=10), upper=Constant(value=20))]))
`
, but was evaluated to
`
Subscript(value=Name(id='img'), slice=ExtSlice(dims=[Index(value=Ellipsis()), Slice(lower=Num(n=10), upper=Num(n=20), step=None)]))
`
Fixes https://github.com/pytorch/pytorch/issues/48674
Pull Request resolved: https://github.com/pytorch/pytorch/pull/48676
Reviewed By: seemethere, gmagogsfm
Differential Revision: D25261323
Pulled By: malfet
fbshipit-source-id: cc818ecc596a062ed5f1a1d11d3fdf0f22bf7f4a
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/45908
As per subj, existing logging does not explain the cause of the error
Test Plan: unit tests pass.
Reviewed By: SplitInfinity
Differential Revision: D23609965
fbshipit-source-id: 818965176f7193c62035e3d2f0547bb525fea0fb
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/45261
**Summary**
This commit enables `unused` syntax for ignoring
properties. Inoring properties is more intuitive with this feature enabled.
`ignore` is not supported because class type properties cannot be
executed in Python (because they exist only as TorchScript types) like
an `ignored` function and module properties that cannot be scripted
are not added to the `ScriptModule` wrapper so that they
may execute in Python.
**Test Plan**
This commit updates the existing unit tests for class type and module
properties to test properties ignored using `unused`.
Test Plan: Imported from OSS
Reviewed By: navahgar, Krovatkin, mannatsingh
Differential Revision: D23971881
Pulled By: SplitInfinity
fbshipit-source-id: 8d3cc1bbede7753d6b6f416619e4660c56311d33
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/45098
**Summary**
This commit adds support for default arguments in methods of class
types. Similar to how default arguments are supported for regular
script functions and methods on scripted modules, default values are
retrieved from the definition of a TorchScript class in Python as Python
objects, converted to IValues, and then attached to the schemas of
already compiled class methods.
**Test Plan**
This commit adds a set of new tests to TestClassType to test default
arguments.
**Fixes**
This commit fixes#42562.
Test Plan: Imported from OSS
Reviewed By: gmagogsfm
Differential Revision: D23844769
Pulled By: SplitInfinity
fbshipit-source-id: ceedff7703bf9ede8bd07b3abcb44a0f654936bd
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/42390
**Summary**
This commit extends support for properties to include
ScriptModules.
**Test Plan**
This commit adds a unit test that has a ScriptModule with
a user-defined property.
`python test/test_jit_py3.py TestScriptPy3.test_module_properties`
Test Plan: Imported from OSS
Reviewed By: eellison, mannatsingh
Differential Revision: D22880298
Pulled By: SplitInfinity
fbshipit-source-id: 74f6cb80f716084339e2151ca25092b6341a1560
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/41371
**Summary**
This commit enables the use of `torch.no_grad()` in a with item of a
with statement within JIT. Note that the use of this context manager as
a decorator is not supported.
**Test Plan**
This commit adds a test case to the existing with statements tests for
`torch.no_grad()`.
**Fixes**
This commit fixes#40259.
Test Plan: Imported from OSS
Reviewed By: gmagogsfm
Differential Revision: D22649519
Pulled By: SplitInfinity
fbshipit-source-id: 7fa675d04835377666dfd0ca4e6bc393dc541ab9
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/42389
**Summary**
This commit adds support for properties to TorchScript classes,
specifically for getters and setters. They are implemented essentially
as pointers to the methods that the corresponding decorators decorate,
which are treated like regular class methods. Deleters for properties
are considered to be out of scope (and probably useless for TorchScript
anyway).
**Test Plan**
This commit adds a unit test for a class with a property that has both
getter and setter and one that has only a getter.
`python test/test_jit.py TestClassType.test_properties`
Test Plan: Imported from OSS
Reviewed By: eellison, ppwwyyxx
Differential Revision: D22880232
Pulled By: SplitInfinity
fbshipit-source-id: 4828640f4234cb3b0d4f3da4872a75fbf519e5b0
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/42611
**Summary**
This commit modifies the Python frontend to ignore static functions on
Torchscript classes when compiling them. They are currently included
along with methods, which causes the first argument of the
staticfunction to be unconditionally inferred to be of the type of the
class it belongs to (regardless of how it is annotated or whether it is
annotated at all). This can lead to compilation errors depending on
how that argument is used in the body of the function.
Static functions are instead imported and scripted as if they were
standalone functions.
**Test Plan**
This commit augments the unit test for static methods in `test_class_types.py`
to test that static functions can call each other and the class
constructor.
**Fixes**
This commit fixes#39308.
Test Plan: Imported from OSS
Reviewed By: ZolotukhinM
Differential Revision: D22958163
Pulled By: SplitInfinity
fbshipit-source-id: 45c3c372792299e6e5288e1dbb727291e977a2af
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/40902
See the bottom of this stack for context.
Test Plan: Imported from OSS
Reviewed By: eellison
Differential Revision: D22360210
Pulled By: suo
fbshipit-source-id: 4275127173a36982ce9ad357aa344435b98e1faf
Summary:
**Summary**
This commit adds support for with statements to PyTorch JIT. Each
of the with items in a with statement is represented in the JIT IR
as a pair of `prim::Enter` and `prim::Exit` nodes that call the
`__enter__` and `__exit__` methods defined on the context manager objects
returned by the expressions in the with item.
**Testing**
This commit adds unit tests for with statements with named with items,
nameless with items, and with statements that encounter exceptions.
```
$ python test/test_jit.py TestWith.test_with_as
Fail to import hypothesis in common_utils, tests are not derandomized
.
----------------------------------------------------------------------
Ran 1 test in 0.430s
OK
```
```
$ python test/test_jit.py TestWith.test_with_no_as
Fail to import hypothesis in common_utils, tests are not derandomized
.
----------------------------------------------------------------------
Ran 1 test in 0.264s
OK
```
```
$ python test/test_jit.py TestWith.test_with_exceptions
Fail to import hypothesis in common_utils, tests are not derandomized
Couldn't download test skip set, leaving all tests enabled...
.
----------------------------------------------------------------------
Ran 1 test in 1.053s
OK
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/34705
Differential Revision: D22095945
Pulled By: SplitInfinity
fbshipit-source-id: f661565a834786725259b8ea014b4d7532f9419d
Summary:
Fix https://github.com/pytorch/pytorch/issues/38336
Add %= support in TorchScript. It's now possible to do something like:
```py
torch.jit.script
def mm(a,b):
a %= b
return a
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/38983
Differential Revision: D21803523
Pulled By: SplitInfinity
fbshipit-source-id: 3437860d06d32e26ca9a5497099148c1f1616c5b
Summary:
**Summary**
This commit enables the use of `torch.jit.unused` on methods of TorchScript classes.
This attribute is honoured by replacing the body of any method
marked as unused in the parsed AST for the class with `raise Exception(...)`.
**Test Plan**
This commit adds a unit test `TestClassType.test_unused_method` that
tests this feature.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/38522
Differential Revision: D21733818
Pulled By: SplitInfinity
fbshipit-source-id: 771872359dad70fac4aae83b6b5f17abb6329890
Summary:
**Summary**
This commit removes a print statement added in https://github.com/pytorch/pytorch/issues/37994 that appears to
be for debugging and was most likely not intended to be commited.
**Test Plan**
Continuous integration.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/38524
Differential Revision: D21587268
Pulled By: SplitInfinity
fbshipit-source-id: 6bdcdce647c45f5c0a2ba179a3545a1c0cae1492
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/35618
Python 2 has reached end-of-life and is no longer supported by PyTorch.
Python 3 always uses true division.
Test Plan: CI
Differential Revision: D20842884
Pulled By: dreiss
fbshipit-source-id: 522e34bb584d4bdb01c9c40eb267955062a57774
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/37994
Before, reassigning a method in a module (like `forward = _forward`)
didn't work, because we look at the function object's name for our def
name when building AST. Mkae that overrideable to handle cases like
reassignment
Test Plan: Imported from OSS
Differential Revision: D21444535
Pulled By: suo
fbshipit-source-id: 4f045f18b5a146edc8005689af525d7d7ed8dd5f
Summary:
del in python supports multiple operands, but PyTorch c++ frontend doesn't support that. To be consistent across different frontends, we decided to throw an exception when finding del with multiple operands inside torchscript.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/38089
Test Plan: Unit tests in test/jit/test_builtins.py
Differential Revision: D21478900
Pulled By: SplitInfinity
fbshipit-source-id: 1cbd61301680c5d6652ef104996178cefcdd3716
Summary:
Also move the ignores for imports to the bottom in `mypy.ini`, those are much less interesting - start with the stuff people want to work on.
Second commit tests the instructions: remove an ignore, fix the issue.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/37594
Differential Revision: D21434858
Pulled By: ezyang
fbshipit-source-id: 4f1a6868cdb4cb59d072bcf105f48c3a5ba3ff98
Summary:
We used to only support indexing through
- numbers like `x[0, 1]`
- tuple like `x[(0, 1)]`
- tensor like `x[torch.tensor([0, 1])]`
This PR adds support for indexing through list which is equivalent to tensor.
- `x[[0, 1, 5]]`
- `x[[0, 1], [0, 1]]`
- `x[[[0, 1], [0, 1]], [[0, 1], [0, 1]]]`
Note for `x[[0, 1, 5]]` we had a bug in AST conversion code so we used to treat it like `x[0, 1, 5]` which means it might accidentally run and produce wrong result(fixes https://github.com/pytorch/pytorch/issues/37286 fixes https://github.com/pytorch/pytorch/issues/18616), now that it's fixed we probably want to mark it as BC breaking.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/37848
Reviewed By: suo
Differential Revision: D21409840
Pulled By: ailzhang
fbshipit-source-id: 6f2d962885c6dc009cb384d98be1822f5ca7a189
