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Author SHA1 Message Date
cyyever
456c87c8a2 [8/N] Fix extra warnings brought by clang-tidy-17 (#139151) 
Fixes #ISSUE_NUMBER

Pull Request resolved: https://github.com/pytorch/pytorch/pull/139151
Approved by: https://github.com/ezyang

Co-authored-by: Aaron Gokaslan <aaronGokaslan@gmail.com>
 2024-10-30 14:20:08 +00:00
Edward Yang
b14269dcfb Make Context to be Device-agnostic Step by Step (1/N) (#136519) (#138155) 
Summary:
- make init to be device-agnostic and move it to AcceleratorHooksInterface
- refactoring context related to device initialization

Original pull request: https://github.com/pytorch/pytorch/pull/136519

Test Plan: contbuild & OSS CI, see 4a8e49389c

Reviewed By: malfet

Differential Revision: D64471142

Pull Request resolved: https://github.com/pytorch/pytorch/pull/138155
Approved by: https://github.com/malfet, https://github.com/bobrenjc93
 2024-10-17 20:58:56 +00:00
PyTorch MergeBot
d4d687ffb2 Revert "Make Context to be Device-agnostic Step by Step (1/N) (#136519)" 
This reverts commit 4a8e49389c.

Reverted https://github.com/pytorch/pytorch/pull/136519 on behalf of https://github.com/clee2000 due to breaking internal tests related to MITA, @ezyang has a forward fix? ([comment](https://github.com/pytorch/pytorch/pull/136519#issuecomment-2414588302))
 2024-10-15 17:19:16 +00:00
FFFrog
4a8e49389c Make Context to be Device-agnostic Step by Step (1/N) (#136519) 
----

- make init to be device-agnostic and move it to AcceleratorHooksInterface
- refactoring context related to device initialization

Pull Request resolved: https://github.com/pytorch/pytorch/pull/136519
Approved by: https://github.com/ezyang, https://github.com/EikanWang, https://github.com/guangyey
 2024-10-13 12:38:02 +00:00
PyTorch MergeBot
079f909263 Revert "Make Context to be Device-agnostic Step by Step (1/N) (#136519)" 
This reverts commit be0b75256a.

Reverted https://github.com/pytorch/pytorch/pull/136519 on behalf of https://github.com/jovianjaison due to this pr is causing errors internally ([comment](https://github.com/pytorch/pytorch/pull/136519#issuecomment-2405781093))
 2024-10-10 18:32:17 +00:00
Jin Zhou
5516ac5c21 [ROCm] Tunableop record untuned (#128813) 
When enable tunableop, It is easy to have OOM since APP usually needs large video memory size, such as running a LLM for inference.  So we need a offline mode to tune the GEMMs. This PR provide an offline mode for tunableOp:

- record untuned GEMMs to file.

- a python API named tune_gemm_in_file is added to read the untuned file and tune the GEMMs in file

Pull Request resolved: https://github.com/pytorch/pytorch/pull/128813
Approved by: https://github.com/jeffdaily, https://github.com/hongxiayang, https://github.com/naromero77amd

Co-authored-by: Nikita Shulga <2453524+malfet@users.noreply.github.com>
 2024-10-09 21:59:03 +00:00
FFFrog
be0b75256a Make Context to be Device-agnostic Step by Step (1/N) (#136519) 
- make init to be device-agnostic and move it to AcceleratorHooksInterface
- refactoring context related to device initialization

Pull Request resolved: https://github.com/pytorch/pytorch/pull/136519
Approved by: https://github.com/ezyang, https://github.com/EikanWang, https://github.com/guangyey
 2024-10-09 02:13:36 +00:00
eellison
8893881867 Invalidate StorageImpl instances when tensor is overwritten with cudagraphs (#125264) 
Fixes #104435

Pull Request resolved: https://github.com/pytorch/pytorch/pull/125264
Approved by: https://github.com/ezyang

Co-authored-by: eellison <elias.ellison@gmail.com>
 2024-10-09 00:05:52 +00:00
cyy
a2396b2dd8 [2/N] Fix extra warnings brought by clang-tidy-17 (#137459) 
Follows #137407

Pull Request resolved: https://github.com/pytorch/pytorch/pull/137459
Approved by: https://github.com/Skylion007
 2024-10-08 19:05:02 +00:00
albanD
88e54de219 More nogil unsafe API fix (#137142) 
Cover the PyDict APIs and confirms no update needed for PyModule one.
The rest was already covered in https://github.com/pytorch/pytorch/pull/136899

Pull Request resolved: https://github.com/pytorch/pytorch/pull/137142
Approved by: https://github.com/eqy, https://github.com/Skylion007
 2024-10-04 21:56:34 +00:00
Jeff Daily
c7b0d4b148 raw_alloc ignores PYTORCH_NO_CUDA_MEMORY_CACHING (#131114) 
raw_alloc is used by cudnn, miopen, thrust, and tunableop.  Without this PR, the env var for disabling the caching allocator will only partially work.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/131114
Approved by: https://github.com/eqy, https://github.com/houseroad, https://github.com/albanD

Co-authored-by: Nichols A. Romero <nick.romero@amd.com>
 2024-10-04 15:36:29 +00:00
PyTorch MergeBot
0d1701f310 Revert "raw_alloc ignores PYTORCH_NO_CUDA_MEMORY_CACHING (#131114)" 
This reverts commit 7001907480.

Reverted https://github.com/pytorch/pytorch/pull/131114 on behalf of https://github.com/PaliC due to failing internal builds ([comment](https://github.com/pytorch/pytorch/pull/131114#issuecomment-2390615007))
 2024-10-03 06:22:55 +00:00
Jeff Daily
7001907480 raw_alloc ignores PYTORCH_NO_CUDA_MEMORY_CACHING (#131114) 
raw_alloc is used by cudnn, miopen, thrust, and tunableop.  Without this PR, the env var for disabling the caching allocator will only partially work.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/131114
Approved by: https://github.com/eqy, https://github.com/houseroad, https://github.com/albanD

Co-authored-by: Nichols A. Romero <nick.romero@amd.com>
 2024-10-02 16:27:15 +00:00
Jack Taylor
a15774563b [ROCm] Enable ROCm support for inductor's dynamic_rblock_scaling (#129663) 
As of ROCm 6.1 [hipDeviceProp_t::regsPerMultiprocessor](https://rocm.docs.amd.com/projects/HIP/en/latest/doxygen/html/structhip_device_prop__t.html#a7390d5b180d63978c81aa971060270b4) is now available allowing us to enable this attribute on ROCm.
```
>>> torch.cuda.get_device_properties(0)
_CudaDeviceProperties(name='AMD Instinct MI250X/MI250', major=9, minor=0, gcnArchName='gfx90a:sramecc+:xnack-', total_memory=65520MB, multi_processor_count=104)
>>> torch.cuda.get_device_properties(0).regs_per_multiprocessor
65536
```

With https://github.com/triton-lang/triton/pull/3962we can extract n_regs and n_spells from a triton binary with AMD backend allowing us to enable inductor's dynamic_rblock_scaling on ROCm initially implemented in https://github.com/pytorch/pytorch/pull/115094

Leaving this in draft until following PRs have landed:
- https://github.com/pytorch/pytorch/pull/129361 to bump the triton commit pin
- https://github.com/pytorch/pytorch/pull/128449 to allow us to grab warp_size from device properties instead of hard coding 64 on ROCm.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/129663
Approved by: https://github.com/jansel, https://github.com/shunting314
 2024-09-13 16:45:39 +00:00
Yu, Guangye
6c1da66407 [Reland] Refactor caching device allocator utils (#130923) 
# Motivation
Following [[RFC] Intel GPU Runtime Upstreaming for Allocator ](https://github.com/pytorch/pytorch/issues/116322), this PR aims to refactor caching device allocator utils to improve code reuse usage.
This is the first PR, we could prepare some follow-up PRs continuing to refactor the device caching allocator.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/130923
Approved by: https://github.com/EikanWang, https://github.com/gujinghui, https://github.com/albanD, https://github.com/eqy
 2024-09-07 11:14:17 +00:00
PyTorch MergeBot
e55c0f59e5 Revert "[Reland] Refactor caching device allocator utils (#130923)" 
This reverts commit 9809080b9e.

Reverted https://github.com/pytorch/pytorch/pull/130923 on behalf of https://github.com/kit1980 due to breaking internal builds - Error: Relocation overflow has occured ([comment](https://github.com/pytorch/pytorch/pull/130923#issuecomment-2332640961))
 2024-09-05 21:16:14 +00:00
Yu, Guangye
9809080b9e [Reland] Refactor caching device allocator utils (#130923) 
# Motivation
Following [[RFC] Intel GPU Runtime Upstreaming for Allocator ](https://github.com/pytorch/pytorch/issues/116322), this PR aims to refactor caching device allocator utils to improve code reuse usage.
This is the first PR, we could prepare some follow-up PRs continuing to refactor the device caching allocator.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/130923
Approved by: https://github.com/EikanWang, https://github.com/gujinghui, https://github.com/albanD, https://github.com/eqy
 2024-09-04 05:31:08 +00:00
Natalia Gimelshein
c25b64a057 expose host_emptyCache to python, fix a bug in freeing cudaHostRegist… (#134919) 
…ered memory

Fixes #ISSUE_NUMBER

Pull Request resolved: https://github.com/pytorch/pytorch/pull/134919
Approved by: https://github.com/eqy
 2024-09-01 09:07:25 +00:00
Natalia Gimelshein
29b7852dc1 drop gil in couple places (leads to deadlocks) (#134910) 
Per title

Pull Request resolved: https://github.com/pytorch/pytorch/pull/134910
Approved by: https://github.com/eqy
 2024-09-01 00:05:53 +00:00
Syed Tousif Ahmed
4655eb3ee2 Uses MemPoolContext to route allocations from CUDACachingAllocator (#134685) 
Re-open of https://github.com/pytorch/pytorch/pull/133599 that was mistakenly closed by issuing `ghstack land`
Pull Request resolved: https://github.com/pytorch/pytorch/pull/134685
Approved by: https://github.com/ezyang
 2024-08-29 03:56:31 +00:00
PyTorch MergeBot
2c88a923a7 Revert "Refactor caching device allocator utils (#130923)" 
This reverts commit c45ca8092d.

Reverted https://github.com/pytorch/pytorch/pull/130923 on behalf of https://github.com/ZainRizvi due to Sorry but this appears to be causing internal tests to fail with errors like `error: no type named 'DeviceStats' in namespace 'xxx::xxx:xxxAllocator'; did you mean 'DeviceStatus'?` ([comment](https://github.com/pytorch/pytorch/pull/130923#issuecomment-2315730155))
 2024-08-28 15:56:08 +00:00
Yu, Guangye
c45ca8092d Refactor caching device allocator utils (#130923) 
# Motivation
Following [[RFC] Intel GPU Runtime Upstreaming for Allocator ](https://github.com/pytorch/pytorch/issues/116322), this PR aims to refactor caching device allocator utils to improve code reuse usage.
This is the first PR, we could prepare some follow-up PRs continuing to refactor the device caching allocator.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/130923
Approved by: https://github.com/EikanWang, https://github.com/gujinghui, https://github.com/albanD, https://github.com/eqy
 2024-08-28 01:35:23 +00:00
Jesse Cai
255cd75a97 [sparse] Add cuSPARSELt as a backend (#128534) 
Summary:

This PR adds in cuSPARSELt as a backend to PyTorch.

It is now possible to see if cuSPARSELt is available and the version if
it is with
```
torch.backends.cusparselt.is_available()
torch.backends.cusparselt.version()
```

Test Plan:
```
python test/test_sparse_semi_structured.py -k test_cusparselt_backend
```

Reviewers:

Subscribers:

Tasks:

Tags:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/128534
Approved by: https://github.com/cpuhrsch, https://github.com/eqy, https://github.com/syed-ahmed
 2024-08-21 22:06:07 +00:00
Mikayla Gawarecki
018e48c337 [Reland] Add wrappers for synchronous GPUDirect Storage APIs (#133489) 
Reland #130633

USE_CUFILE turned off by default in this version
Pull Request resolved: https://github.com/pytorch/pytorch/pull/133489
Approved by: https://github.com/albanD
 2024-08-15 17:11:52 +00:00
Jez Ng
260e7cb143 Make CUDA device properties's __repr__ output actually printable (#132863) 
Previously we would write the UUID bytes directly, leading to 'invalid
UTF-8 sequence' errors.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/132863
Approved by: https://github.com/Skylion007, https://github.com/eqy
 2024-08-07 21:08:43 +00:00
Nicolas Macchioni
527f104a69 add L2 cache size to device properties (#132819) 
Fixes #ISSUE_NUMBER

Pull Request resolved: https://github.com/pytorch/pytorch/pull/132819
Approved by: https://github.com/eellison
 2024-08-07 04:55:06 +00:00
PyTorch MergeBot
e191b83462 Revert "Add wrappers for synchronous GPUDirect Storage APIs (#130633)" 
This reverts commit 709ddf7a9d.

Reverted https://github.com/pytorch/pytorch/pull/130633 on behalf of https://github.com/clee2000 due to still failing internally D60265673 ([comment](https://github.com/pytorch/pytorch/pull/130633#issuecomment-2253239607))
 2024-07-26 18:08:20 +00:00
Mikayla Gawarecki
709ddf7a9d Add wrappers for synchronous GPUDirect Storage APIs (#130633) 
Based in part on https://github.com/NVIDIA/apex/pull/1774

Differential Revision: [D60155434](https://our.internmc.facebook.com/intern/diff/D60155434)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/130633
Approved by: https://github.com/albanD
 2024-07-25 22:23:38 +00:00
Aaron Enye Shi
fddb1bcdea [CCA][Memory Snapshot] Move user_defined annotations to Native Caching Allocator (#130964) 
Summary: Instead of embedding the user_defined TraceEntry inside of device_traces, which causes issues when some threads may not have the proper device id set, save them into an external_annotations field by using a RingBuffer<AnnotationEntry> called annotation_buffer owned by the NativeCachingAllocator.

Test Plan: CI, resnet run, and FBR model.

Differential Revision: D59703213

Pulled By: aaronenyeshi

Pull Request resolved: https://github.com/pytorch/pytorch/pull/130964
Approved by: https://github.com/zdevito
 2024-07-25 14:06:52 +00:00
PyTorch MergeBot
e4b5645f83 Revert "Add wrappers for synchronous GPUDirect Storage APIs (#130633)" 
This reverts commit 5b5e0698a5.

Reverted https://github.com/pytorch/pytorch/pull/130633 on behalf of https://github.com/clee2000 due to breaking a lot of jobs and build rules internally D60085885, possibly needs to update some bazel build? ([comment](https://github.com/pytorch/pytorch/pull/130633#issuecomment-2245806738))
 2024-07-23 17:19:34 +00:00
Mikayla Gawarecki
5b5e0698a5 Add wrappers for synchronous GPUDirect Storage APIs (#130633) 
Based in part on https://github.com/NVIDIA/apex/pull/1774

Pull Request resolved: https://github.com/pytorch/pytorch/pull/130633
Approved by: https://github.com/albanD
 2024-07-22 14:51:24 +00:00
PyTorch MergeBot
7c299b46ca Revert "Invalidate StorageImpl instances when tensor is overwritten with cudagraphs (#125264)" 
This reverts commit 8390843eba.

Reverted https://github.com/pytorch/pytorch/pull/125264 on behalf of https://github.com/izaitsevfb due to breaks internal tests ([comment](https://github.com/pytorch/pytorch/pull/125264#issuecomment-2240516202))
 2024-07-19 22:58:51 +00:00
PyTorch MergeBot
5f981388ec Revert "[ROCm] Enable ROCm support for inductor's dynamic_rblock_scaling (#129663)" 
This reverts commit d7a78ec8b9.

Reverted https://github.com/pytorch/pytorch/pull/129663 on behalf of https://github.com/atalman due to Breaks internal builds ([comment](https://github.com/pytorch/pytorch/pull/129663#issuecomment-2240011143))
 2024-07-19 19:46:26 +00:00
Jack Taylor
d7a78ec8b9 [ROCm] Enable ROCm support for inductor's dynamic_rblock_scaling (#129663) 
As of ROCm 6.1 [hipDeviceProp_t::regsPerMultiprocessor](https://rocm.docs.amd.com/projects/HIP/en/latest/doxygen/html/structhip_device_prop__t.html#a7390d5b180d63978c81aa971060270b4) is now available allowing us to enable this attribute on ROCm.
```
>>> torch.cuda.get_device_properties(0)
_CudaDeviceProperties(name='AMD Instinct MI250X/MI250', major=9, minor=0, gcnArchName='gfx90a:sramecc+:xnack-', total_memory=65520MB, multi_processor_count=104)
>>> torch.cuda.get_device_properties(0).regs_per_multiprocessor
65536
```

With https://github.com/triton-lang/triton/pull/3962we can extract n_regs and n_spells from a triton binary with AMD backend allowing us to enable inductor's dynamic_rblock_scaling on ROCm initially implemented in https://github.com/pytorch/pytorch/pull/115094

Leaving this in draft until following PRs have landed:
- https://github.com/pytorch/pytorch/pull/129361 to bump the triton commit pin
- https://github.com/pytorch/pytorch/pull/128449 to allow us to grab warp_size from device properties instead of hard coding 64 on ROCm.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/129663
Approved by: https://github.com/jansel, https://github.com/shunting314
 2024-07-19 09:45:03 +00:00
Syed Tousif Ahmed
38b7d89aa4 Uses context pointer for deleter to enable multiple CUDAPluggableAllocator usage (#130472) 
We should be able to create multiple CUDAPluggableAllocators in the same pytorch program (see https://github.com/pytorch/pytorch/issues/124807, https://github.com/pytorch/pytorch/pull/125722 for context). When mixing CUDAPluggableAllocators in the same pytorch program, we need to make sure that the deleter passed in through the CUDAPluggableAllocator gets "attached" to the data_ptr and persist until program exit (when it's called to free the memory).

Currently, CUDAPluggableAllocator maintains a global `current_custom_allocator`. When creating the `DataPtr`, `raw_deleter` attaches `custom_raw_deleter` to the DataPtr which calls  `current_custom_allocator->raw_delete(...)`. This approach is fine when using only one allocator, however for multiple allocator use case, DataPtr would be using the deleter of whatever is in the `current_custom_allocator`. For example, if allocation 1 was done with `cudaMalloc` and allocation 2 was done with `ncclMemAlloc`, and if `current_custom_allocator` is currently pointing to the CUDAPluggableAllocator with `ncclMemAlloc` - when cleaning up the allocation 1, we'd be using `ncclMemFree` instead of `cudaFree`.

In this PR, we solve the above problem by remembering the `free_fn_` using a deleter context. Hence, there is no need to go through an allocator object to find the deleter.

CC: @zdevito @ptrblck @eqy
Pull Request resolved: https://github.com/pytorch/pytorch/pull/130472
Approved by: https://github.com/eqy, https://github.com/ezyang
 2024-07-18 11:33:21 +00:00
Yu, Guangye
f2552dcc3d refactor cached tensor more generic (#129359) 
# Motivation
solve https://github.com/pytorch/pytorch/issues/129027 to refactor cached tensor to be generic.

# Additional Context
No API name change. It is only decoupling with CUDA build option.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/129359
Approved by: https://github.com/eqy, https://github.com/EikanWang, https://github.com/albanD
 2024-07-17 03:00:08 +00:00
Isuru Fernando
8390843eba Invalidate StorageImpl instances when tensor is overwritten with cudagraphs (#125264) 
Fixes #104435

Pull Request resolved: https://github.com/pytorch/pytorch/pull/125264
Approved by: https://github.com/ezyang
 2024-07-16 14:29:29 +00:00
PyTorch MergeBot
78799e82b0 Revert "Invalidate StorageImpl instances when tensor is overwritten with cudagraphs (#125264)" 
This reverts commit 1bc390c5f5.

Reverted https://github.com/pytorch/pytorch/pull/125264 on behalf of https://github.com/jithunnair-amd due to test test/inductor/test_cudagraph_trees.py::CudaGraphTreeTests::test_fallback_to_eager_if_recompiling_too_many_times is failing https://github.com/pytorch/pytorch/actions/runs/9933628108/job/27477785946 1bc390c5f5. Test was introduced by fa5f572748 which is before the merge base ([comment](https://github.com/pytorch/pytorch/pull/125264#issuecomment-2229508737))
 2024-07-15 21:59:46 +00:00
Isuru Fernando
1bc390c5f5 Invalidate StorageImpl instances when tensor is overwritten with cudagraphs (#125264) 
Fixes #104435

Pull Request resolved: https://github.com/pytorch/pytorch/pull/125264
Approved by: https://github.com/ezyang
 2024-07-15 04:16:17 +00:00
Ramana Cherukuri
f6a0be5023 Add warpSize to Device properties (#128449) 
Adding warp_size to CudaDeviceProperties.

>>> import torch
>>> prop = torch.cuda.get_device_properties(torch.cuda.current_device())
>>> prop.warp_size
64
>>>

@jeffdaily @pruthvistony @jithunnair-amd @ROCmSupport

Co-authored-by: Jithun Nair <37884920+jithunnair-amd@users.noreply.github.com>
Pull Request resolved: https://github.com/pytorch/pytorch/pull/128449
Approved by: https://github.com/eqy, https://github.com/jataylo, https://github.com/jithunnair-amd, https://github.com/malfet
 2024-07-01 09:13:32 +00:00
Jeff Daily
169b4ca07e add uuid in cudaDeviceProperties (#125083) 
Replaces #99967.

Fixes #99903.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/125083
Approved by: https://github.com/pruthvistony, https://github.com/albanD, https://github.com/eqy, https://github.com/malfet
 2024-06-27 23:53:13 +00:00
Aaron Enye Shi
f42d5b6dca [Memory Snapshot] Make recordAnnotations callback initialize lazily (#129242) 
Summary: Make the recordAnnotations' Record function callback lazily initialize when record memory history starts. This will help reduce the impact on Time To First Batch metric.

Test Plan: CI and ran locally.

Differential Revision: D58875576

Pulled By: aaronenyeshi

Pull Request resolved: https://github.com/pytorch/pytorch/pull/129242
Approved by: https://github.com/zdevito
 2024-06-22 04:05:55 +00:00
Aaron Enye Shi
b5d541609d [Memory Snapshot] Add recordAnnotations to capture record_function annotations (#129072) 
Summary:
Add new traceEvents into Memory Snapshot for record_function annotations. These will capture both the profiler's step annotation as well as user annotations.

Test Plan:
CI

Pulled By:
aaronenyeshi

Differential Revision: D55941362

Pull Request resolved: https://github.com/pytorch/pytorch/pull/129072
Approved by: https://github.com/zdevito
 2024-06-19 18:05:41 +00:00
Jeff Daily
0e7bd7fedd [ROCm] TunableOp improvements (#124362) 
- use less memory; smaller default hipblaslt workspace size
- options to avoid cache effects
  - icache flush option
  - rotating buffers during tuning
- python APIs
- unit tests

Pull Request resolved: https://github.com/pytorch/pytorch/pull/124362
Approved by: https://github.com/xw285cornell
 2024-06-03 22:30:11 +00:00
PyTorch MergeBot
718bb9016f Revert "[Memory Snapshot] Add recordAnnotations to capture record_function annotations (#124179)" 
This reverts commit 187aeaeabf.

Reverted https://github.com/pytorch/pytorch/pull/124179 on behalf of https://github.com/clee2000 due to test_tensorexpr.py::TestTensorExprFuser::test_simple_add is causing a segfault https://github.com/pytorch/pytorch/actions/runs/9097383783/job/25007155440 187aeaeabf, test was skipped due to bad TD ([comment](https://github.com/pytorch/pytorch/pull/124179#issuecomment-2112948246))
 2024-05-15 16:11:47 +00:00
Aaron Enye Shi
187aeaeabf [Memory Snapshot] Add recordAnnotations to capture record_function annotations (#124179) 
Summary: Add new traceEvents into Memory Snapshot for record_function annotations. These will capture both the profiler's step annotation as well as user annotations.

Test Plan:
CI

New Snapshot Generated:
devvm2184.cco0.facebook.com.Apr_19_13_27_14.3072800.snapshot.pickle

Snippet of Snapshot device_traces show `ProfilerStep#0`, and `## forward ##` annotations:
```
[[{'action': 'user_defined',
   'addr': 0,
   'size': 0,
   'stream': 0,
   'time_us': 1713558427168556,
   'frames': [{'name': 'START', 'filename': 'ProfilerStep#0', 'line': 0}]},
  {'action': 'user_defined',
   'addr': 0,
   'size': 0,
   'stream': 0,
   'time_us': 1713558427168738,
   'frames': [{'name': 'END', 'filename': 'ProfilerStep#0', 'line': 0}]},
  {'action': 'user_defined',
   'addr': 0,
   'size': 0,
   'stream': 0,
   'time_us': 1713558427168865,
   'frames': [{'name': 'START', 'filename': 'ProfilerStep#1', 'line': 0}]},
  {'action': 'user_defined',
   'addr': 0,
   'size': 0,
   'stream': 0,
   'time_us': 1713558427168920,
   'frames': [{'name': 'START', 'filename': '## forward ##', 'line': 0}]},
  {'action': 'alloc',
   'addr': 140166073581568,
   'size': 3211264,
   'stream': 0,
   'time_us': 1713558427172978,
   'frames': [{'name': '_conv_forward',
     'filename': '/mnt/xarfuse/uid-416185/235d4caf-seed-nspid4026531836_cgpid32884718-ns-4026531840/torch/nn/modules/conv
```

Differential Revision: D55941362

Pulled By: aaronenyeshi

Pull Request resolved: https://github.com/pytorch/pytorch/pull/124179
Approved by: https://github.com/zdevito
 2024-05-15 14:19:40 +00:00
Richard Barnes
ed327876f5 [codemod] c10:optional -> std::optional (#126135) 
Generated by running the following from PyTorch root:
```
find . -regex ".*\.\(cpp\|h\|cu\|hpp\|cc\|cxx\)$" | grep -v "build/" | xargs -n 50 -P 4 perl -pi -e 's/c10::optional/std::optional/'
```

`c10::optional` is just an alias for `std::optional`. This removes usages of that alias in preparation for eliminating it entirely.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/126135
Approved by: https://github.com/Skylion007, https://github.com/malfet, https://github.com/albanD, https://github.com/aaronenyeshi
 2024-05-14 19:35:51 +00:00
PyTorch MergeBot
6fd745255e Revert "add uuid in cudaDeviceProperties (#125083)" 
This reverts commit 3f36145db2.

Reverted https://github.com/pytorch/pytorch/pull/125083 on behalf of https://github.com/izaitsevfb due to Fails internal builds with: no member named 'uuid' in 'hipDeviceProp_t' ([comment](https://github.com/pytorch/pytorch/pull/125083#issuecomment-2103315320))
 2024-05-09 19:52:45 +00:00
Jeff Daily
3f36145db2 add uuid in cudaDeviceProperties (#125083) 
Replaces #99967.

Fixes #99903.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/125083
Approved by: https://github.com/pruthvistony, https://github.com/albanD, https://github.com/eqy
 2024-05-08 19:15:55 +00:00
PyTorch MergeBot
5fd0b6e5f7 Revert "add uuid in cudaDeviceProperties (#125083)" 
This reverts commit f35fe4eaf1.

Reverted https://github.com/pytorch/pytorch/pull/125083 on behalf of https://github.com/clee2000 due to test_uuid is flaky.  ex https://github.com/pytorch/pytorch/actions/runs/8988855916/job/24692369523 https://hud.pytorch.org/flakytest?name=test_uuid&suite=TestCuda&file=%25&limit=300 ([comment](https://github.com/pytorch/pytorch/pull/125083#issuecomment-2099029993))
 2024-05-07 18:16:27 +00:00