This PR is part of a series attempting to re-submit https://github.com/pytorch/pytorch/pull/134592 as smaller PRs.
In jit tests:
- Add and use a common raise_on_run_directly method for when a user runs a test file directly which should not be run this way. Print the file which the user should have run.
- Raise a RuntimeError on tests which have been disabled (not run)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/154725
Approved by: https://github.com/clee2000
The `usort` config in `pyproject.toml` has no effect due to a typo. Fixing the typo make `usort` do more and generate the changes in the PR. Except `pyproject.toml`, all changes are generated by `lintrunner -a --take UFMT --all-files`.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/127126
Approved by: https://github.com/kit1980
The `usort` config in `pyproject.toml` has no effect due to a typo. Fixing the typo make `usort` do more and generate the changes in the PR. Except `pyproject.toml`, all changes are generated by `lintrunner -a --take UFMT --all-files`.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/127126
Approved by: https://github.com/kit1980
ghstack dependencies: #127122, #127123, #127124, #127125
Summary:
In fbcode, aten and jit ops can get registered in different orders depending on build mode. In dev mode, aten is registered first; in opt mode, jit is registered first.
This causes problems in torch.ops.aten.* calls; these calls use `torch._C._jit_get_operation`, which selects an overload based on the inputs to the call. It searches through the overloads for the op with the given name, and chooses the first one that matches the input types. "First" depends on whether aten or jit ops were registered first - e.g. in `test_both_scalars_cuda` in opt mode, it chooses `add.complex` and returns a complex value.
We also saw this issue in https://github.com/pytorch/pytorch/pull/103576.
This PR sorts the list of overloads first, putting the aten ops first.
Differential Revision: D48304930
Pull Request resolved: https://github.com/pytorch/pytorch/pull/107138
Approved by: https://github.com/ezyang, https://github.com/eellison
Applies the remaining flake8-comprehension fixes and checks. This changes replace all remaining unnecessary generator expressions with list/dict/set comprehensions which are more succinct, performant, and better supported by our torch.jit compiler. It also removes useless generators such as 'set(a for a in b)`, resolving it into just the set call.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/94676
Approved by: https://github.com/ezyang
Summary:
Python's function parsing from the `ast` module records the line number of the function definition, not the first decorator. So this diff fixes crashes like this:
```
IndexError: vector::_M_range_check: __n (which is 10) >= this->size() (which is 8)
```
Test Plan: New unit test
Differential Revision: D40726352
Pull Request resolved: https://github.com/pytorch/pytorch/pull/87804
Approved by: https://github.com/tugsbayasgalan, https://github.com/davidberard98
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 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.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/74889
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: D35206262
Pulled By: qihqi
Pull Request resolved: https://github.com/pytorch/pytorch/pull/76771
Approved by: https://github.com/seemethere
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/74785
Fix for https://github.com/facebookresearch/torchdynamo/issues/93
Because the constructor follow a non-standard input schema (variadic integers), they are handled specially in ir_emitter.
Test Plan: Imported from OSS
Reviewed By: ejguan
Differential Revision: D35362762
Pulled By: eellison
fbshipit-source-id: 960badf08ba2ab0818af5fd331aff3542051250f
(cherry picked from commit bd579dead5a5206fc6e5b535ecf4f99ae67ee135)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/74768
As commented in code:
```
// Empty List Literals that are not assigned to variables
// may match to any list type in schema matching,
// but still default to List[Tensor] if assigned to a variable
// or returned from a function
// Restricting empty list matching to temporary values
// avoids difficult to handle cases such as
// a = []
// b = a
// if cond:
// b.append(2)
// else:
// a.append("hi")
// This is also the same behavior that C++ allows with {}
// (cannot assign to a variable typed as auto)
```
Fix for https://github.com/facebookresearch/torchdynamo/issues/95
Test Plan: Imported from OSS
Reviewed By: ejguan
Differential Revision: D35362760
Pulled By: eellison
fbshipit-source-id: da23e8889312001b60d64a1758da5c578b6fe5ea
(cherry picked from commit 75682f17204d6d444e7e7144472c6e833150c601)
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:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65966
ghstack-source-id: 141594521
Support exportation of "interface methods" from submodule to a mobile module. "Interface methods" are defined as methods which might be dynamically called in a module therefore need to be exported anyway, like virtual functions in C++.
Before this change the algorithm of exportation is a simple iteration through all toplevel methods. Now since we have indirect calls, we need to recursively walkthrough the call graph to find all potentially used methods, which means the order we export methods might break in old runtimes, to guarantee forward compatibility we need to export toplevel methods first, then extra methods, in this order toplevel methods will always be found first.
NOTE that interface methods exportations are disabled by default in this diff. We need to call torch._C._enable_mobile_interface_call_export to actaully enable it.
Test Plan: buck test mode/dev //caffe2/test:jit -- --exact 'caffe2/test:jit - test_export_opnames_interface (jit.test_misc.TestMisc)'
Reviewed By: qihqi, iseeyuan
Differential Revision: D31326155
fbshipit-source-id: 5be7234cca07691f62648a85133b6db65e427b53
Summary:
As this diff shows, currently there are a couple hundred instances of raw `noqa` in the codebase, which just ignore all errors on a given line. That isn't great, so this PR changes all existing instances of that antipattern to qualify the `noqa` with respect to a specific error code, and adds a lint to prevent more of this from happening in the future.
Interestingly, some of the examples the `noqa` lint catches are genuine attempts to qualify the `noqa` with a specific error code, such as these two:
```
test/jit/test_misc.py:27: print(f"{hello + ' ' + test}, I'm a {test}") # noqa E999
test/jit/test_misc.py:28: print(f"format blank") # noqa F541
```
However, those are still wrong because they are [missing a colon](https://flake8.pycqa.org/en/3.9.1/user/violations.html#in-line-ignoring-errors), which actually causes the error code to be completely ignored:
- If you change them to anything else, the warnings will still be suppressed.
- If you add the necessary colons then it is revealed that `E261` was also being suppressed, unintentionally:
```
test/jit/test_misc.py:27:57: E261 at least two spaces before inline comment
test/jit/test_misc.py:28:35: E261 at least two spaces before inline comment
```
I did try using [flake8-noqa](https://pypi.org/project/flake8-noqa/) instead of a custom `git grep` lint, but it didn't seem to work. This PR is definitely missing some of the functionality that flake8-noqa is supposed to provide, though, so if someone can figure out how to use it, we should do that instead.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/56272
Test Plan:
CI should pass on the tip of this PR, and we know that the lint works because the following CI run (before this PR was finished) failed:
- https://github.com/pytorch/pytorch/runs/2365189927
Reviewed By: janeyx99
Differential Revision: D27830127
Pulled By: samestep
fbshipit-source-id: d6dcf4f945ebd18cd76c46a07f3b408296864fcb
Summary:
1. move module related stuff to test_module_container
2. created test_types for types and annotation
3. created test_misc for the rest
Pull Request resolved: https://github.com/pytorch/pytorch/pull/55560
Reviewed By: VitalyFedyunin
Differential Revision: D27650911
Pulled By: walterddr
fbshipit-source-id: d895a7da9e9c3d25a662a37faf4daabc276b9c1a
