a1dad2f2d2
[BE][Ez]: Autotype torch/profiler with ruff ANN ( #157923 )
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Apply ruff autotyping fixes to add annotations to torch profiler
Pull Request resolved: https://github.com/pytorch/pytorch/pull/157923
Approved by: https://github.com/albanD , https://github.com/sraikund16
2025-07-09 22:07:50 +00:00
30293319a8
[BE][Easy][19/19] enforce style for empty lines in import segments in torch/[o-z]*/ ( #129771 )
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See https://github.com/pytorch/pytorch/pull/129751#issue-2380881501 . Most changes are auto-generated by linter.
You can review these PRs via:
```bash
git diff --ignore-all-space --ignore-blank-lines HEAD~1
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/129771
Approved by: https://github.com/justinchuby , https://github.com/janeyx99
2024-08-01 17:07:14 +00:00
8db9dfa2d7
Flip default value for mypy disallow_untyped_defs [9/11] ( #127846 )
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See #127836 for details.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/127846
Approved by: https://github.com/ezyang
ghstack dependencies: #127842 , #127843 , #127844 , #127845
2024-06-08 18:50:06 +00:00
3bf922a6ce
Apply UFMT to low traffic torch modules ( #106249 )
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Signed-off-by: Edward Z. Yang <ezyang@meta.com >
Pull Request resolved: https://github.com/pytorch/pytorch/pull/106249
Approved by: https://github.com/Skylion007
2023-07-29 23:37:30 +00:00
5bbec680d7
Fix usages of contextmanager without finally ( #96170 )
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Pull Request resolved: https://github.com/pytorch/pytorch/pull/96170
Approved by: https://github.com/ngimel , https://github.com/malfet
2023-03-08 20:59:27 +00:00
8fce9a09cd
[BE]: pyupgrade Python to 3.8 - imports and object inheritance only ( #94308 )
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Apply parts of pyupgrade to torch (starting with the safest changes).
This PR only does two things: removes the need to inherit from object and removes unused future imports.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/94308
Approved by: https://github.com/ezyang , https://github.com/albanD
2023-02-07 21:10:56 +00:00
f20e4eab7b
Fix ITT unit-tests if PyTorch is compiled with USE_ITT=OFF ( #86199 )
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Fixes https://github.com/pytorch/pytorch/pull/84848#discussion_r986329680
@malfet @slgong-fb
Pull Request resolved: https://github.com/pytorch/pytorch/pull/86199
Approved by: https://github.com/malfet
2022-10-04 21:57:05 +00:00
80b8886223
add itt unit test and docstrings ( #84848 )
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Add unit tests and docstrings corresponding to PR https://github.com/pytorch/pytorch/pull/63289
UT:
1. `test_profiler_emit_itt` in `test/test_autograd.py`. This test is merely intended to catch if emit_itt breaks on construction.
2. Test `torch.profiler.itt` functions in `test/test_itt.py`
3. Only testing that emit_itt runs when `record_shapes` option is enabled in `test/test_profiler.py`.
Docstring:
1. add ITT related info into `docs/source/bottleneck.rst`
4. add `torch.profiler.itt` functions to `docs/source/profiler.rst`
5. add docstring to `torch.profiler.itt` functions in `torch/profiler/itt.py`
Pull Request resolved: https://github.com/pytorch/pytorch/pull/84848
Approved by: https://github.com/malfet
2022-09-28 01:39:58 +00:00
357b7d589c
Fix docstring inconsistencies: string -> str, boolean -> bool ( #82410 )
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### Description
Throughout the PyTorch docs and codebase, the `string` type in docstrings is referred to by two separate names. This leads to inconsistent docs, like you can see here: https://pytorch.org/docs/stable/generated/torch.nn.Conv3d.html#torch.nn.Conv3d
This PR fixes this issue by ensuring that all mentions of the string type in docstrings, are using the same format that Sphinx generates hyperlinks for.
### Testing
No testing should be required for this change
Pull Request resolved: https://github.com/pytorch/pytorch/pull/82410
Approved by: https://github.com/jbschlosser
2022-07-28 21:29:57 +00:00
3c7044728b
Enable Intel® VTune™ Profiler's Instrumentation and Tracing Technology APIs (ITT) to PyTorch ( #63289 )
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More detailed description of benefits can be found at #41001 . This is Intel's counterpart of NVidia’s NVTX (https://pytorch.org/docs/stable/autograd.html#torch.autograd.profiler.emit_nvtx ).
ITT is a functionality for labeling trace data during application execution across different Intel tools.
For integrating Intel(R) VTune Profiler into Kineto, ITT needs to be integrated into PyTorch first. It works with both standalone VTune Profiler [(https://www.intel.com/content/www/us/en/developer/tools/oneapi/vtune-profiler.html ](https://www.intel.com/content/www/us/en/developer/tools/oneapi/vtune-profiler.html )) and Kineto-integrated VTune functionality in the future.
It works for both Intel CPU and Intel XPU devices.
Pitch
Add VTune Profiler's ITT API function calls to annotate PyTorch ops, as well as developer customized code scopes on CPU, like NVTX for NVidia GPU.
This PR rebases the code changes at https://github.com/pytorch/pytorch/pull/61335 to the latest master branch.
Usage example:
```
with torch.autograd.profiler.emit_itt():
for i in range(10):
torch.itt.range_push('step_{}'.format(i))
model(input)
torch.itt.range_pop()
```
cc @ilia-cher @robieta @chaekit @gdankel @bitfort @ngimel @orionr @nbcsm @guotuofeng @guyang3532 @gaoteng-git
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63289
Approved by: https://github.com/malfet
2022-07-13 13:50:15 +00:00
1454515253
Revert "Enable Intel® VTune™ Profiler's Instrumentation and Tracing Technology APIs (ITT) to PyTorch ( #63289 )"
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This reverts commit f988aa2b3ff77d5aa010bdaae4e52c6ee345c04d.
Reverted https://github.com/pytorch/pytorch/pull/63289 on behalf of https://github.com/malfet due to broke trunk, see f988aa2b3f
2022-06-30 12:49:41 +00:00
f988aa2b3f
Enable Intel® VTune™ Profiler's Instrumentation and Tracing Technology APIs (ITT) to PyTorch ( #63289 )
...
More detailed description of benefits can be found at #41001 . This is Intel's counterpart of NVidia’s NVTX (https://pytorch.org/docs/stable/autograd.html#torch.autograd.profiler.emit_nvtx ).
ITT is a functionality for labeling trace data during application execution across different Intel tools.
For integrating Intel(R) VTune Profiler into Kineto, ITT needs to be integrated into PyTorch first. It works with both standalone VTune Profiler [(https://www.intel.com/content/www/us/en/developer/tools/oneapi/vtune-profiler.html ](https://www.intel.com/content/www/us/en/developer/tools/oneapi/vtune-profiler.html )) and Kineto-integrated VTune functionality in the future.
It works for both Intel CPU and Intel XPU devices.
Pitch
Add VTune Profiler's ITT API function calls to annotate PyTorch ops, as well as developer customized code scopes on CPU, like NVTX for NVidia GPU.
This PR rebases the code changes at https://github.com/pytorch/pytorch/pull/61335 to the latest master branch.
Usage example:
```
with torch.autograd.profiler.emit_itt():
for i in range(10):
torch.itt.range_push('step_{}'.format(i))
model(input)
torch.itt.range_pop()
```
cc @ilia-cher @robieta @chaekit @gdankel @bitfort @ngimel @orionr @nbcsm @guotuofeng @guyang3532 @gaoteng-git
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63289
Approved by: https://github.com/malfet
2022-06-30 05:14:03 +00:00
