pytorch - 💡(How to fix) Fix DISABLED test_opcheck_opinfo_NumpyCubeCustomOp_cpu_float32 (__main__.TestCustomOpTestingCPU) [1 comments, 1 participants]

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pytorch/pytorch#179992Fetched 2026-04-11 06:10:23
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Root Cause

This test was disabled because it is failing in CI. See recent examples and the most recent trunk workflow logs.

RAW_BUFFERClick to expand / collapse

Platforms: asan, linux

This test was disabled because it is failing in CI. See recent examples and the most recent trunk workflow logs.

Over the past 6 hours, it has been determined flaky in 18 workflow(s) with 36 failures and 18 successes.

Debugging instructions (after clicking on the recent samples link): DO NOT ASSUME THINGS ARE OKAY IF THE CI IS GREEN. We now shield flaky tests from developers so CI will thus be green but it will be harder to parse the logs. To find relevant log snippets:

  1. Click on the workflow logs linked above
  2. Click on the Test step of the job so that it is expanded. Otherwise, the grepping will not work.
  3. Grep for test_opcheck_opinfo_NumpyCubeCustomOp_cpu_float32
  4. There should be several instances run (as flaky tests are rerun in CI) from which you can study the logs.

Test file path: test_custom_ops.py

For all disabled tests (by GitHub issue), see https://hud.pytorch.org/disabled.

cc @chauhang @penguinwu @bdhirsh @bobrenjc93 @aorenste

extent analysis

TL;DR

The test test_opcheck_opinfo_NumpyCubeCustomOp_cpu_float32 in test_custom_ops.py is likely failing due to flakiness and needs to be debugged by analyzing the workflow logs.

Guidance

  • To debug the issue, follow the provided debugging instructions: click on the recent samples link, expand the Test step in the workflow logs, and grep for test_opcheck_opinfo_NumpyCubeCustomOp_cpu_float32 to find relevant log snippets.
  • Study the logs from multiple instances of the test run to identify patterns or common errors that may be causing the flakiness.
  • Review the test code in test_custom_ops.py to ensure it is correctly implemented and not prone to intermittent failures.
  • Consider re-enabling the test and running it locally to reproduce the issue and gather more information.

Notes

The provided information suggests that the test is flaky, but the root cause is unknown. Debugging the issue will require careful analysis of the workflow logs and potentially the test code itself.

Recommendation

Apply workaround: temporarily re-enable the test and run it locally to gather more information and reproduce the issue, then debug and fix the underlying cause of the flakiness.

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pytorch - 💡(How to fix) Fix DISABLED test_opcheck_opinfo_NumpyCubeCustomOp_cpu_float32 (__main__.TestCustomOpTestingCPU) [1 comments, 1 participants]