pytorch - 💡(How to fix) Fix DISABLED test_unary_ufunc_numerical_log_backend_inductor_numerics_cuda_bfloat16 (__main__.TestOpInfoPropertiesCUDA) [1 comments, 2 participants]

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pytorch/pytorch#180066Fetched 2026-04-11 06:08:38
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Root Cause

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 issues related to the test_unary_ufunc_numerical_log_backend_inductor_numerics_cuda_bfloat16 test case.

Guidance

  • Investigate the recent examples of test failures on torch-ci.com to identify patterns or common causes of the failure.
  • Review the test_torchinductor_opinfo_properties.py test file, specifically the TestOpInfoPropertiesCUDA class and the test_unary_ufunc_numerical_log_backend_inductor_numerics_cuda_bfloat16 test case, to understand the test logic and potential failure points.
  • Check the ROCm platform configuration and version to ensure compatibility with the test requirements.
  • Consider re-enabling the test and running it with additional logging or debugging to gather more information about the failure.

Notes

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

Recommendation

Apply workaround: Investigate and address the specific test case failure, as the issue seems to be related to a particular test case rather than a general platform or version problem.

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