8fa81a6066
Enable misc-use-internal-linkage check and apply fixes ( #148948 )
...
Enables clang-tidy rule [`misc-use-internal-linkage`](https://clang.llvm.org/extra/clang-tidy/checks/misc/use-internal-linkage.html ). This new check was introduced in Clang-Tidy 18 and is available due to recent update of Clang-Tidy 19.
The check marks functions and variables used only in the translation unit as static. Therefore undesired symbols are not leaked into other units, more link time optimisations are possible and the resulting binaries may be smaller.
The detected violations were mostly fixed by using static. In other cases, the symbols were indeed consumed by others files, then their declaring headers were included. Still some declarations were wrong and have been fixed.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/148948
Approved by: https://github.com/Skylion007
2025-03-12 14:22:56 +00:00
4a019047ad
Enable nested namespace check in clang-tidy ( #118506 )
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It is time to enable nested namespaces in the code.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/118506
Approved by: https://github.com/albanD
2024-01-31 00:32:35 +00:00
77f2883c41
[Reland2] fix missing-prototypes warnings in torch_cpu (Part 4) ( #102228 )
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This PR relands the changes introduced in PR https://github.com/pytorch/pytorch/pull/100849 . The old PR turnd nnc_* functions into static. We now add declarations for them and hope that inter builds will pass.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/102228
Approved by: https://github.com/albanD
2023-06-02 22:04:44 +00:00
32ce06a5ab
Revert "[Reland] fix missing-prototypes warnings in torch_cpu (Part 4) ( #101949 )"
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This reverts commit 4f2c007a1b5170c2aa0d47e388ff9e07c7a7d354.
Reverted https://github.com/pytorch/pytorch/pull/101949 on behalf of https://github.com/osalpekar due to As noted in @izaitsevfb's comment, we are still seeing linker errors, this time due to `nnc_prepacked_linear_clamp_run` being made a static function. ([comment](https://github.com/pytorch/pytorch/pull/101949#issuecomment-1560226880 ))
2023-05-23 22:53:47 +00:00
4f2c007a1b
[Reland] fix missing-prototypes warnings in torch_cpu (Part 4) ( #101949 )
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This PR relands the changes introduced in PR #100849 . The old PR turnd nnc_aten_embedding into a static function, however, it is actually used in torch/csrc/jit/tensorexpr/operators/misc.cpp.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/101949
Approved by: https://github.com/albanD
2023-05-22 10:53:07 +00:00
498c34e8e8
Revert " fix missing-prototypes warnings in torch_cpu (Part 4) ( #100849 )"
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This reverts commit c2f28d1c1df0db78f2951e4df5dde264f80f07eb.
Reverted https://github.com/pytorch/pytorch/pull/100849 on behalf of https://github.com/izaitsevfb due to fails internal Meta builds, including fbcode and android, see D46009888: ld.lld: error: undefined symbol: nnc_aten_embedding ([comment](https://github.com/pytorch/pytorch/pull/100849#issuecomment-1555105800 ))
2023-05-19 19:05:15 +00:00
c2f28d1c1d
fix missing-prototypes warnings in torch_cpu (Part 4) ( #100849 )
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This PR fixes more missing-prototypes violations in the torch_cpu source following PRs #100053 , #100147 and #100245
Pull Request resolved: https://github.com/pytorch/pytorch/pull/100849
Approved by: https://github.com/albanD
2023-05-18 03:49:45 +00:00
b8f14b7877
[Profiler][Minor] Group and consolidate stub APIs ( #85510 )
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There is a concept in profiler of a stub that wraps a profiling API. It was introduced for CUDA profiling before Kineto, and ITT has adopted it to call into VTune APIs. However for the most part we don't really interact with them when developing the PyTorch profiler.
Thus it makes sense to unify the fallback registration mechanism and create a subfolder to free up real estate in the top level `torch/csrc/profiler` directory.
Differential Revision: [D39108647](https://our.internmc.facebook.com/intern/diff/D39108647/ )
Pull Request resolved: https://github.com/pytorch/pytorch/pull/85510
Approved by: https://github.com/aaronenyeshi
2022-10-14 05:38:46 +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
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
