pytorch - 💡(How to fix) Fix DISABLED test_addcdiv_cuda_complex64 (__main__.TestTorchDeviceTypeCUDA) [1 comments, 1 participants]

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pytorch/pytorch#181537Fetched 2026-04-27 05:28:41
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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: linux, slow

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 3 workflow(s) with 6 failures and 3 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_addcdiv_cuda_complex64
  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_torch.py

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

cc @mruberry

extent analysis

TL;DR

The test test_addcdiv_cuda_complex64 in test_torch.py is likely failing due to flakiness and needs to be investigated by analyzing the workflow logs.

Guidance

  • Investigate the workflow logs by following the provided debugging instructions to identify the cause of the flakiness.
  • Look for patterns or common errors in the log snippets related to test_addcdiv_cuda_complex64.
  • Check the test file test_torch.py for any potential issues or recent changes that could be contributing to the flakiness.
  • Consider re-enabling the test and re-running the workflow to gather more information.

Example

No code snippet is provided as the issue does not contain enough information to suggest a specific code change.

Notes

The flakiness of the test may be due to various factors, including environmental issues, test dependencies, or test implementation. A thorough investigation of the logs and test code is necessary to determine the root cause.

Recommendation

Apply workaround: Investigate and debug the test to determine the cause of the flakiness, rather than simply re-enabling the test or ignoring the issue. This will help to ensure the reliability and stability of the test suite.

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pytorch - 💡(How to fix) Fix DISABLED test_addcdiv_cuda_complex64 (__main__.TestTorchDeviceTypeCUDA) [1 comments, 1 participants]