[WIP] Upstream push 0627 #80355

jjsjann123 · 2022-06-27T16:28:41Z

Syncing nvfuser devel branch to upstream master. https://github.com/csarofeen/pytorch/

Code changes includes:

TransformPropagator refactor: switched to Dijkstra instead of exhaustive enumeration on all possible paths to reduce compilation time on transform propagation;
Indexing refactor: remove reference tensor creation in all tensor indexing logic (THD #1690)
(more) generic grouped grid reduction kernel;
Minor parser/fuser patches:
1. zero-dim tensor reduction support
2. no-op binary removal within fused graph
3. expand supported in fusion

Squashed commits to WAR github API
Commits that's actually in this PR from the devel branch:

a054b3efcf5af58ea518de283f55aaf9fe06ff5f Refactor TransormPropagator to allow specifying a position and propagating to part of the DAG (#1775)
d67e1cda9b802036841a371318014a818a849b0a Indexing refactor stage 1: remove reference tensor creation in all tensor indexing logic (#1690)
1b6529956a1ace220898ad09dde0bf85e49827f7 Issue 1770 (#1774)
35b04276b648c9b55cdb6a67f3889f54e745c3d2 Avoid compilation errors like below: (#1773)
452c77326a340d2a4130b7802f4f319aec60e72a Ignore reductions of zero-dim tensors per PyTorch conventions (#1771)
31d6c56d88afba09ac53b2d5dd3493d625f8cd57 TransformPropagator refactor (#1769)
570c5a84b91a3cf67207331be9650d26a2d37e3d Merge pull request #1767 from csarofeen/upstream_merge_0621
9d6c3d84be86da643df6fd51695543938111f20d merging upstream 61305cd638b6fcd73a0b66b4cde7014fecb9e8ce
0ed815f76b08f285bda855dd500692ff10a8abce New TransformPropagator algorithm (#1763)
6c195200c0a92fb0f38c833431a8940ed07569b9 no-op binary removal (#1764)
ec7fa4187c177186527409dfc5c7b1754d30bc92 Proper propagation of IterType (#1762)
b263562dbc3c865007ad7d7d42a58a20be8d7922 Fix dimensionality check (#1759)
2d6343f6cc1e47b63ef20a50d1446f6480736478 More generic grouped grid reduction kernel (#1740)
64e2b56df2c8b9fd22a362d9cc05974a8607ef3d [nvfuser] prevent spamming warning message (#77777) (#1758)
0c431624ff15b6458b9f9b674a3852373fc426b1 [nvFuser] Improving bitwise ops support (#77158) (#1757)
b93a14777fde3b9b39684b9cf1715651a806b281 Parser expand (#1754)

RUN_TORCHBENCH: nvfuser

facebook-github-bot · 2022-06-27T16:28:50Z

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❌ 1 New Failures

As of commit bb73c20 (more details on the Dr. CI page):

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1/1 failures introduced in this PR

🕵️ 1 new failure recognized by patterns

The following CI failures do not appear to be due to upstream breakages

TorchBench CI (pytorch-linux-py3.7-cu102) / run-torchbench (1/1)

Step: "Run TorchBench" (full log | diagnosis details | 🔁 rerun)

2022-07-12T05:54:14.8977292Z ##[error]Process completed with exit code 128.

b93a14777fde3b9b39684b9cf1715651a806b281 Parser expand (#1754)

RUN_TORCHBENCH: nvfuser
2022-07-12T05:54:14.8813995Z PR_BASE_SHA: d321be6
2022-07-12T05:54:14.8814335Z PR_HEAD_SHA: bb73c20
2022-07-12T05:54:14.8814632Z TORCHBENCH_BRANCH: main
2022-07-12T05:54:14.8814997Z ##[endgroup]
2022-07-12T05:54:14.8850545Z ~/pytorch ~/nvme/pytorch-org-runner/_work/pytorch/pytorch
2022-07-12T05:54:14.8957340Z fatal: Not a valid commit name bb73c20
2022-07-12T05:54:14.8977292Z ##[error]Process completed with exit code 128.
2022-07-12T05:54:14.9036372Z Post job cleanup.
2022-07-12T05:54:15.0015597Z [command]/usr/bin/git version
2022-07-12T05:54:15.0058492Z git version 2.23.3
2022-07-12T05:54:15.0093059Z [command]/usr/bin/git config --local --name-only --get-regexp core.sshCommand
2022-07-12T05:54:15.0152924Z [command]/usr/bin/git submodule foreach --recursive git config --local --name-only --get-regexp 'core.sshCommand' && git config --local --unset-all 'core.sshCommand' || :
2022-07-12T05:54:15.0646526Z Entering 'submodules/FAMBench'
2022-07-12T05:54:15.0728952Z Entering 'submodules/FAMBench/FBGEMM'
2022-07-12T05:54:15.0810986Z Entering 'submodules/FAMBench/FBGEMM/third_party/asmjit'
2022-07-12T05:54:15.0895128Z Entering 'submodules/FAMBench/FBGEMM/third_party/cpuinfo'
2022-07-12T05:54:15.0978918Z Entering 'submodules/FAMBench/FBGEMM/third_party/googletest'


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jjsjann123 · 2022-06-27T18:52:21Z

hmmm, the win error looks nasty. https://pipelines.actions.githubusercontent.com/serviceHosts/7d146c05-69c3-4c20-a0e7-818111670117/_apis/pipelines/1/runs/2090862/signedlogcontent/40?urlExpires=2022-06-27T17%3A32%3A49.9990256Z&urlSigningMethod=HMACV1&urlSignature=ZEbsHmbmDmbJ%2B8x8xw6QAV1HmLCDqH3R38WG5ENxSWU%3D

2022-06-27T17:12:48.3910454Z C:\Program Files (x86)\Microsoft Visual Studio\2019\BuildTools\VC\Tools\MSVC\14.28.29333\include\xmemory(701): error C2280: 'std::pair<const torch::jit::fuser::cuda::VectorOfUniqueEntries<torch::jit::fuser::cuda::IterDomain *,std::hash<torch::jit::fuser::cuda::IterDomain *>> *const ,torch::jit::fuser::cuda::ComputeAtMap::DoubleBufferIndicesPtr>::pair(const std::pair<const torch::jit::fuser::cuda::VectorOfUniqueEntries<torch::jit::fuser::cuda::IterDomain *,std::hash<torch::jit::fuser::cuda::IterDomain *>> *const ,torch::jit::fuser::cuda::ComputeAtMap::DoubleBufferIndicesPtr> &)': attempting to reference a deleted function

pytorch-bot · 2022-06-30T00:37:00Z

We have recently simplified the CIFlow labels and ciflow/slow is no longer in use.
You can use any of the following

ciflow/trunk (.github/workflows/trunk.yml): all jobs we run per-commit on master
ciflow/periodic (.github/workflows/periodic.yml): all jobs we run periodically on master
ciflow/android (.github/workflows/run_android_tests.yml): android build and test
ciflow/nightly (.github/workflows/nightly.yml): all jobs we run nightly
ciflow/binaries: all binary build and upload jobs
ciflow/binaries_conda: binary build and upload job for conda
ciflow/binaries_libtorch: binary build and upload job for libtorch
ciflow/binaries_wheel: binary build and upload job for wheel

jjsjann123 · 2022-06-30T14:54:25Z

hmmmm. expand is patched here: csarofeen#1790.
I'm waiting on CI to finish before cherry-picking that and reverting the expand disablement.

jjsjann123 · 2022-06-30T23:11:15Z

@davidberard98 is there something wrong with the torchbench? The log seems to be complaining about commit name
fatal: Not a valid commit name 1fa9cac858f5cdcdd12b8c460a62a221a0aa752f

davidberard98 · 2022-06-30T23:13:24Z

unfortunately I think you don't have permissions to run torchbench on PRs, I can see if I can get it to run

davidberard98 · 2022-07-01T03:00:35Z

@jjsjann123 can you comment on expand enablement here, do you think there's any risk there? Since expand is a view op, and we had issues with view ops last time?

facebook-github-bot · 2022-07-01T03:00:57Z

@davidberard98 has imported this pull request. If you are a Meta employee, you can view this diff on Phabricator.

davidberard98 · 2022-07-01T03:02:57Z

@jjsjann123 we probably need another rebase in order to skip over the macos-11-py3-x86-64 test failure

jjsjann123 · 2022-07-05T21:14:37Z

Apparently viable/strict is too old.. I'll rebase again....

davidberard98 · 2022-07-05T21:21:36Z

@jjsjann123 looks like viable/strict is only 5 hrs old on https://hud.pytorch.org/metrics ?

jjsjann123 · 2022-07-05T22:37:33Z

I saw these warning:
::error::Your PR is based on a version of master that is too old for our CI to work. Please rebase your PR on latest master and resubmit.

But looking at the full log, I also noticed this vvv. So it looked like a real thing. Let me fix it.

/var/lib/jenkins/workspace/torch/csrc/jit/codegen/cuda/maxinfo_propagator.h:40:10:error: ‘struct torch::jit::fuser::cuda::MaxInfoSpanningTree::Selector’ has virtual functions and accessible non-virtual destructor [-Werror=non-virtual-dtor]
   40 |   struct Selector {
      |          ^~~~~~~~
/var/lib/jenkins/workspace/torch/csrc/jit/codegen/cuda/maxinfo_propagator.h:46:10:error: ‘struct torch::jit::fuser::cuda::MaxInfoSpanningTree::Propagator’ has virtual functions and accessible non-virtual destructor [-Werror=non-virtual-dtor]
   46 |   struct Propagator {
      |          ^~~~~~~~~~
In file included from /var/lib/jenkins/workspace/torch/csrc/jit/codegen/cuda/compute_at.cpp:9:
/var/lib/jenkins/workspace/torch/csrc/jit/codegen/cuda/transform_replay.h:159:25:error: base class ‘struct torch::jit::fuser::cuda::MaxInfoSpanningTree::Propagator’ has accessible non-virtual destructor [-Werror=non-virtual-dtor]
  159 | class TORCH_CUDA_CU_API TransformPropagator
      |                         ^~~~~~~~~~~~~~~~~~~
/var/lib/jenkins/workspace/torch/csrc/jit/codegen/cuda/transform_replay.h:159:25:error: ‘class torch::jit::fuser::cuda::TransformPropagator’ has virtual functions and accessible non-virtual destructor [-Werror=non-virtual-dtor]

facebook-github-bot · 2022-07-06T01:15:39Z

@davidberard98 has imported this pull request. If you are a Meta employee, you can view this diff on Phabricator.

torch/csrc/jit/codegen/cuda/maxinfo_propagator.h

jjsjann123 · 2022-07-06T19:56:05Z

This one looks promising. @davidberard98 should we start importing it?

facebook-github-bot · 2022-07-06T20:22:26Z

@davidberard98 has imported this pull request. If you are a Meta employee, you can view this diff on Phabricator.

jjsjann123 · 2022-07-08T19:11:23Z

bumping threads~

davidberard98 · 2022-07-11T23:29:53Z

@jjsjann123 5-6% regression on autogen-40 and autogen-43, see https://github.com/pytorch/pytorch/runs/7223997510?check_suite_focus=true

Not sure if this is significant or just random, but they do both look like they are pretty similar benchmarks (native_batch_norm + pointwise)

https://github.com/pytorch/benchmark/blob/main/userbenchmark/nvfuser/ir.py

Also depending on your judgement of whether or not this regression is okay could you rebase one more time?

jjsjann123 · 2022-07-12T05:24:28Z

@jjsjann123 5-6% regression on autogen-40 and autogen-43, see https://github.com/pytorch/pytorch/runs/7223997510?check_suite_focus=true

Not sure if this is significant or just random, but they do both look like they are pretty similar benchmarks (native_batch_norm + pointwise)

https://github.com/pytorch/benchmark/blob/main/userbenchmark/nvfuser/ir.py

Also depending on your judgement of whether or not this regression is okay could you rebase one more time?

Neat!

I mean, regression is bad, but it's nice that we are catching them with easy repros! Let met see if I can repro them locally and I can open issues internally to track it, so our next perf tuning would hopefully fix those.
^^^ I think that'll be our approach for minor regression moving forward.

jjsjann123 · 2022-07-12T05:49:59Z

@pytorchbot rebase

* Fix div(scalar, tensor) * lintrunner: clang-format

… on move assignment operator

Caching strides along with sizes. This is to support current expand, which introduces non-contiguous output tensor

This reverts commit e0ebfc1.

pytorchmergebot · 2022-07-12T05:51:21Z

Successfully rebased upstream_push_0627 onto refs/remotes/origin/master, please pull locally before adding more changes (for example, via git checkout upstream_push_0627 && git pull --rebase)

jjsjann123 · 2022-07-12T17:35:08Z

XLA failure seems unrelated. Is this one good to be merged? @davidberard98

re: regression on microbenchmark, haven't forgot about that, but it would be easier for me to repro after the merge (comparing perf across a single commit is easier) 😉 Will do it after the merge.

facebook-github-bot · 2022-07-12T17:47:52Z

@davidberard98 has imported this pull request. If you are a Meta employee, you can view this diff on Phabricator.

davidberard98

LGTM! But I'm going to merge it via the internal workflow, so don't use pytorchbot to merge.

facebook-github-bot · 2022-07-13T19:31:33Z

@pytorchbot merge

(Initiating merge automatically since Phabricator Diff has merged)

pytorchmergebot · 2022-07-13T19:34:26Z

@pytorchbot successfully started a merge job. Check the current status here

github-actions · 2022-07-13T19:35:27Z

Hey @jjsjann123.
You've committed this PR, but it does not have both a 'release notes: ...' and 'topics: ...' label. Please add one of each to the PR. The 'release notes: ...' label should represent the part of PyTorch that this PR changes (fx, autograd, distributed, etc) and the 'topics: ...' label should represent the kind of PR it is (not user facing, new feature, bug fix, perf improvement, etc). The list of valid labels can be found here for the 'release notes: ...' and here for the 'topics: ...'.
For changes that are 'topic: not user facing' there is no need for a release notes label.

Summary: Syncing nvfuser devel branch to upstream master. https://github.com/csarofeen/pytorch/ Code changes includes: - TransformPropagator refactor: switched to Dijkstra instead of exhaustive enumeration on all possible paths to reduce compilation time on transform propagation; - Indexing refactor: remove reference tensor creation in all tensor indexing logic (#1690) - (more) generic grouped grid reduction kernel; - Minor parser/fuser patches: 1. zero-dim tensor reduction support 3. no-op binary removal within fused graph 4. expand supported in fusion Squashed commits to WAR github API Commits that's actually in this PR from the devel branch: ``` a054b3e Refactor TransormPropagator to allow specifying a position and propagating to part of the DAG (#1775) d67e1cd Indexing refactor stage 1: remove reference tensor creation in all tensor indexing logic (#1690) 1b65299 Issue 1770 (#1774) 35b0427 Avoid compilation errors like below: (#1773) 452c773 Ignore reductions of zero-dim tensors per PyTorch conventions (#1771) 31d6c56 TransformPropagator refactor (#1769) 570c5a8 Merge pull request #1767 from csarofeen/upstream_merge_0621 9d6c3d8 merging upstream 61305cd 0ed815f New TransformPropagator algorithm (#1763) 6c19520 no-op binary removal (#1764) ec7fa41 Proper propagation of IterType (#1762) b263562 Fix dimensionality check (#1759) 2d6343f More generic grouped grid reduction kernel (#1740) 64e2b56 [nvfuser] prevent spamming warning message (#77777) (#1758) 0c43162 [nvFuser] Improving bitwise ops support (#77158) (#1757) b93a147 Parser expand (#1754) ``` RUN_TORCHBENCH: nvfuser Pull Request resolved: #80355 Reviewed By: qihqi Differential Revision: D37573400 Pulled By: davidberard98 fbshipit-source-id: 52ab68d89ec01ef61f69f5abeb18c9d3a312aa64

jjsjann123 · 2022-07-15T19:11:16Z

@jjsjann123 5-6% regression on autogen-40 and autogen-43, see https://github.com/pytorch/pytorch/runs/7223997510?check_suite_focus=true

Not sure if this is significant or just random, but they do both look like they are pretty similar benchmarks (native_batch_norm + pointwise)

https://github.com/pytorch/benchmark/blob/main/userbenchmark/nvfuser/ir.py

Also depending on your judgement of whether or not this regression is okay could you rebase one more time?

FYI, running the microbenchmark locally seems to indicate that benchmark results are a little bit flaky.
I don't see real issues or changes to generated code.

Looks like our kernel time varies a little bit, which is not surprising for a small kernel running < 20 us:

kernel1 run in 0.016384 ms, achieved: 612.813 GB/s      total time: 0.016384     total buffer:10040320
kernel1 run in 0.017408 ms, achieved: 576.765 GB/s      total time: 0.017408     total buffer:10040320
kernel1 run in 0.016384 ms, achieved: 612.813 GB/s      total time: 0.016384     total buffer:10040320
kernel1 run in 0.017408 ms, achieved: 576.765 GB/s      total time: 0.017408     total buffer:10040320
kernel1 run in 0.016384 ms, achieved: 612.813 GB/s      total time: 0.016384     total buffer:10040320
kernel1 run in 0.017408 ms, achieved: 576.765 GB/s      total time: 0.017408     total buffer:10040320
kernel1 run in 0.018432 ms, achieved: 544.722 GB/s      total time: 0.018432     total buffer:10040320
kernel1 run in 0.022528 ms, achieved: 445.682 GB/s      total time: 0.022528     total buffer:10040320
kernel1 run in 0.017408 ms, achieved: 576.765 GB/s      total time: 0.017408     total buffer:10040320
kernel1 run in 0.017408 ms, achieved: 576.765 GB/s      total time: 0.017408     total buffer:10040320
kernel1 run in 0.017408 ms, achieved: 576.765 GB/s      total time: 0.017408     total buffer:10040320

Also, autogen-40 & autogen-43 are just PW kernels, (even though there's batch_norm in it, it's running in inference mode.

davidberard98 · 2022-07-15T20:25:55Z

@jjsjann123 thanks for investigating! Figured it was worth flagging since both microbenchmarks looked similar and both were performing badly... but if your tests don't repro any issue or any kernel changes then it's probably fine.

upstream fixes cherry-picked from pytorch#80355

Syncing nvfuser devel branch to upstream master. https://github.com/csarofeen/pytorch/ Code changes includes: - TransformPropagator refactor: switched to Dijkstra instead of exhaustive enumeration on all possible paths to reduce compilation time on transform propagation; - Indexing refactor: remove reference tensor creation in all tensor indexing logic (#1690) - (more) generic grouped grid reduction kernel; - Minor parser/fuser patches: 1. zero-dim tensor reduction support 3. no-op binary removal within fused graph 4. expand supported in fusion Squashed commits to WAR github API Commits that's actually in this PR from the devel branch: ``` a054b3efcf5af58ea518de283f55aaf9fe06ff5f Refactor TransormPropagator to allow specifying a position and propagating to part of the DAG (#1775) d67e1cda9b802036841a371318014a818a849b0a Indexing refactor stage 1: remove reference tensor creation in all tensor indexing logic (#1690) 1b6529956a1ace220898ad09dde0bf85e49827f7 Issue 1770 (#1774) 35b04276b648c9b55cdb6a67f3889f54e745c3d2 Avoid compilation errors like below: (#1773) 452c77326a340d2a4130b7802f4f319aec60e72a Ignore reductions of zero-dim tensors per PyTorch conventions (#1771) 31d6c56d88afba09ac53b2d5dd3493d625f8cd57 TransformPropagator refactor (#1769) 570c5a84b91a3cf67207331be9650d26a2d37e3d Merge pull request #1767 from csarofeen/upstream_merge_0621 9d6c3d84be86da643df6fd51695543938111f20d merging upstream 61305cd638b6fcd73a0b66b4cde7014fecb9e8ce 0ed815f76b08f285bda855dd500692ff10a8abce New TransformPropagator algorithm (#1763) 6c195200c0a92fb0f38c833431a8940ed07569b9 no-op binary removal (#1764) ec7fa4187c177186527409dfc5c7b1754d30bc92 Proper propagation of IterType (#1762) b263562dbc3c865007ad7d7d42a58a20be8d7922 Fix dimensionality check (#1759) 2d6343f6cc1e47b63ef20a50d1446f6480736478 More generic grouped grid reduction kernel (#1740) 64e2b56df2c8b9fd22a362d9cc05974a8607ef3d [nvfuser] prevent spamming warning message (#77777) (#1758) 0c431624ff15b6458b9f9b674a3852373fc426b1 [nvFuser] Improving bitwise ops support (#77158) (#1757) b93a14777fde3b9b39684b9cf1715651a806b281 Parser expand (#1754) ``` RUN_TORCHBENCH: nvfuser Pull Request resolved: pytorch/pytorch#80355 Approved by: https://github.com/davidberard98

Syncing nvfuser devel branch to upstream master. https://github.com/csarofeen/pytorch/ Code changes includes: - TransformPropagator refactor: switched to Dijkstra instead of exhaustive enumeration on all possible paths to reduce compilation time on transform propagation; - Indexing refactor: remove reference tensor creation in all tensor indexing logic (#1690) - (more) generic grouped grid reduction kernel; - Minor parser/fuser patches: 1. zero-dim tensor reduction support 3. no-op binary removal within fused graph 4. expand supported in fusion Squashed commits to WAR github API Commits that's actually in this PR from the devel branch: ``` 2848a5f Refactor TransormPropagator to allow specifying a position and propagating to part of the DAG (#1775) 97d3b84 Indexing refactor stage 1: remove reference tensor creation in all tensor indexing logic (#1690) c8b4f42 Issue 1770 (#1774) 35b04276b648c9b55cdb6a67f3889f54e745c3d2 Avoid compilation errors like below: (#1773) 0773c33 Ignore reductions of zero-dim tensors per PyTorch conventions (#1771) 074d078 TransformPropagator refactor (#1769) 3e9637b Merge pull request #1767 from csarofeen/upstream_merge_0621 690900a merging upstream 61305cd638b6fcd73a0b66b4cde7014fecb9e8ce 86fc20a New TransformPropagator algorithm (#1763) 073e521 no-op binary removal (#1764) dfaca9a Proper propagation of IterType (#1762) 4bc0e6b Fix dimensionality check (#1759) 7ec1263 More generic grouped grid reduction kernel (#1740) bf9c6c6 [nvfuser] prevent spamming warning message (#77777) (#1758) 6f631a8 [nvFuser] Improving bitwise ops support (#77158) (#1757) 921efc8 Parser expand (#1754) ``` RUN_TORCHBENCH: nvfuser Pull Request resolved: pytorch/pytorch#80355 Approved by: https://github.com/davidberard98

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jjsjann123 force-pushed the upstream_push_0627 branch 2 times, most recently from f48d7b3 to 5caf4a2 Compare June 27, 2022 18:44

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torch/csrc/jit/codegen/cuda/maxinfo_propagator.h Outdated Show resolved Hide resolved

jjsjann123 requested a review from davidberard98 July 11, 2022 15:59

jjsjann123 and others added 10 commits July 12, 2022 05:51

fixing msvc build issue

5b08f6c

Fix FusionMaxRootDomainInfoSpanningTreePrintTwice_CUDA (pytorch#1781)

eded9c5

Fix div(Val, TensorView) (pytorch#1778)

3938ec0

* Fix div(scalar, tensor) * lintrunner: clang-format

clangformat / tidy

5323412

dropping const on member variable to avoid defaulted-function-deleted…

5f3ed24

… on move assignment operator

expand/expand_as disabled

8c4b103

Output allocate patch (pytorch#1790)

4f43903

Caching strides along with sizes. This is to support current expand, which introduces non-contiguous output tensor

Revert "expand/expand_as disabled"

effb6d4

This reverts commit e0ebfc1.

non-virtual destructor warning

e24fa8b

removing RootIDInfo for meta internal build failure

bb73c20

pytorchmergebot force-pushed the upstream_push_0627 branch from 5b25761 to bb73c20 Compare July 12, 2022 05:51

davidberard98 approved these changes Jul 12, 2022

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pytorchmergebot added the Merged label Jul 13, 2022

pytorchmergebot closed this in 8d753c8 Jul 13, 2022

jjsjann123 deleted the upstream_push_0627 branch July 14, 2022 06:32

jjsjann123 mentioned this pull request Jul 18, 2022

Upstream ci build fixes csarofeen/pytorch#1842

Merged

jjsjann123 added a commit to csarofeen/pytorch that referenced this pull request Jul 18, 2022

Upstream ci build fixes (#1842)

942be5b

upstream fixes cherry-picked from pytorch#80355

atalman mentioned this pull request Feb 19, 2024

[RFC] Intel GPU ATen Operations Upstreaming Options #119682

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[WIP] Upstream push 0627 #80355

[WIP] Upstream push 0627 #80355

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TorchBench CI (pytorch-linux-py3.7-cu102) / run-torchbench (1/1)

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[WIP] Upstream push 0627 #80355

[WIP] Upstream push 0627 #80355

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jjsjann123 commented Jun 27, 2022 • edited

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TorchBench CI (pytorch-linux-py3.7-cu102) / run-torchbench (1/1)

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