pytorch - 💡(How to fix) Fix DISABLED test_unary_ufunc_numerical_rsqrt_backend_inductor_numerics_cuda_bfloat16 (__main__.TestOpInfoPropertiesCUDA) [1 comments, 2 participants]

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pytorch/pytorch#179980Fetched 2026-04-11 06:08:33
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Root Cause

Platforms: rocm This test was disabled because it is failing on main branch (recent examples).

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Platforms: rocm This test was disabled because it is failing on main branch (recent examples).

cc @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @jataylo @hongxiayang @naromero77amd @jerrymannil @xinyazhang @mruberry @chauhang @penguinwu @voznesenskym @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @kadeng @muchulee8 @amjames @aakhundov @coconutruben

extent analysis

TL;DR

The test failure on the main branch for the test_torchinductor_opinfo_properties.py test may be resolved by investigating and addressing the numerical issues related to the rsqrt backend inductor numerics for bfloat16 data type on the ROCm platform.

Guidance

  • Investigate the recent examples of test failures on torch-ci.com to understand the patterns and potential causes of the failure.
  • Review the test_torchinductor_opinfo_properties.py test code, specifically the test_unary_ufunc_numerical_rsqrt_backend_inductor_numerics_cuda_bfloat16 test case, to identify potential numerical instability or precision issues.
  • Consider reaching out to the listed maintainers and experts (@jeffdaily, @sunway513, etc.) for guidance on resolving the issue, as they may have knowledge about similar problems or ongoing efforts to address them.
  • Check if there are any known issues or ongoing work in the repository related to the rsqrt backend inductor numerics for bfloat16 data type on the ROCm platform.

Notes

The provided information lacks specific technical details about the failure, so a more detailed analysis of the test code and failure examples is necessary to determine the root cause.

Recommendation

Apply workaround: Since the issue is related to a specific test case and platform, it may be possible to apply a workaround, such as skipping the test case for the bfloat16 data type on the ROCm platform or using a different numerical method, until a permanent fix is available.

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pytorch - 💡(How to fix) Fix DISABLED test_unary_ufunc_numerical_rsqrt_backend_inductor_numerics_cuda_bfloat16 (__main__.TestOpInfoPropertiesCUDA) [1 comments, 2 participants]