[Intel GPU] Enable fp64 GEMM #140677
[Intel GPU] Enable fp64 GEMM #140677
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/140677
Note: Links to docs will display an error until the docs builds have been completed. ✅ You can merge normally! (3 Unrelated Failures)As of commit b358c61 with merge base 880e176 ( FLAKY - The following jobs failed but were likely due to flakiness present on trunk:
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| @@ -8,6 +8,7 @@ | |||
| #include <Utils.h> | |||
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| #include <oneapi/dnnl/dnnl.hpp> | |||
| #include "c10/core/ScalarType.h" | |||
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| #include "c10/core/ScalarType.h" | |
| #include <c10/core/ScalarType.h> |
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Thanks for suggestions, the code is changed here
| TORCH_CHECK( | ||
| 8000 false, "Double and complex datatype matmul is not supported in oneDNN"); | ||
| if (self.is_complex()) { | ||
| AT_ERROR("Complex datatype matmul is not supported in oneDNN"); |
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AT_ERROR has been deprecated.
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Thanks for suggestion, AT_ERROR in file is changed to TORCH_CHECK
| if (self.is_complex() || self.scalar_type() == ScalarType::Double) { | ||
| TORCH_CHECK( | ||
| false, "Double and complex datatype matmul is not supported in oneDNN"); | ||
| if (self.is_complex()) { |
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`TORCH_CHECK(!self.is_complex(), "error message");
| // complex case | ||
| if (mat1.is_complex()) { | ||
| AT_ERROR("Complex datatype matmul is not supported in oneDNN"); | ||
| } |
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| // complex case | |
| if (mat1.is_complex()) { | |
| AT_ERROR("Complex datatype matmul is not supported in oneDNN"); | |
| } | |
| // complex case | |
| TORCH_CHECK(!mat1.is_complex(), "Complex datatype matmul is not supported in oneDNN"); |
| @@ -277,73 +280,6 @@ Tensor baddbmm( | |||
| return r; | |||
| } | |||
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| Tensor& addbmm_out( | |||
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Does Intel GPU not support addbmm_out?
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We does not need to write these glue codes, as cuda/cpu/xpu share an entry at natives_functions.yaml. They share same implementation(like op_stub or composite cases) in at::native::addbmm_out, the implementation in addbmm is general as it do the job by calling addmm which we have codes.
| @@ -93,9 +94,13 @@ Tensor& addmm_out( | |||
| } | |||
| } else { | |||
| if (alpha.to<float>() == 1.f && beta_ == 1.f) { | |||
| bias = self; | |||
| bias = is_inplace ? self.clone() : self; | |||
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It would be better to add some comments to elaborate on why the clone is required here.
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Sure, the comments is added here
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You don't need to clone if #144759 is merged. We should use post sum instead of post binary in this case
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@pytorchbot merge |
Merge startedYour change will be merged once all checks pass (ETA 0-4 Hours). Learn more about merging in the wiki. Questions? Feedback? Please reach out to the PyTorch DevX Team |
Merge failedReason: 1 jobs have failed, first few of them are: xpu / linux-jammy-xpu-2025.0-py3.9 / test (default, 2, 4, linux.idc.xpu) Details for Dev Infra teamRaised by workflow job |
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@pytorchbot rebase -b main |
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@pytorchbot started a rebase job onto refs/remotes/origin/main. Check the current status here |
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Successfully rebased |
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@guangyey There should be some new skipped uts were added, but this PR fixs them. I retriggered ci and wait for all fixed uts shown in CI results. After that, I will fix them at single commit. |
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@pytorchbot merge |
Merge startedYour change will be merged once all checks pass (ETA 0-4 Hours). Learn more about merging in the wiki. Questions? Feedback? Please reach out to the PyTorch DevX Team |
Pull Request resolved: #140677 Approved by: https://github.com/guangyey, https://github.com/EikanWang, https://github.com/desertfire
Pull Request resolved: #140677 Approved by: https://github.com/guangyey, https://github.com/EikanWang, https://github.com/desertfire
Pull Request resolved: pytorch#140677 Approved by: https://github.com/guangyey, https://github.com/EikanWang, https://github.com/desertfire
Stack from ghstack (oldest at bottom):
cc @jgong5 @mingfeima @XiaobingSuper @sanchitintel @ashokei @jingxu10 @voznesenskym @penguinwu @EikanWang @Guobing-Chen @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @ColinPeppler @amjames @desertfire @chauhang @aakhundov @gujinghui @fengyuan14 @guangyey