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

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pytorch/pytorch#181323Fetched 2026-04-24 10:35:56
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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.

Fix Action

Fix / Workaround

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 25 workflow(s) with 50 failures and 25 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_is_retain_graph_cuda
  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_autograd.py

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

cc @ezyang @albanD @gqchen @nikitaved @soulitzer @Varal7 @bobrenjc93

extent analysis

TL;DR

The test test_is_retain_graph_cuda in test_autograd.py is failing intermittently, and to fix it, we need to investigate the logs and identify the root cause of the flakiness.

Guidance

  • Investigate the workflow logs by following the provided debugging instructions to find relevant log snippets for test_is_retain_graph_cuda.
  • Study the logs from multiple instances of the test run to identify patterns or common errors that may be causing the flakiness.
  • Check the test file test_autograd.py to see if there are any issues with the test case itself that could be contributing to the flakiness.
  • 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 failing intermittently, and the root cause is not immediately clear. Further investigation is needed to determine the cause of the flakiness.

Recommendation

Apply workaround: Investigate and debug the test case to identify the root 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_is_retain_graph_cuda (__main__.TestAutogradMultipleDispatchCUDA) [2 comments, 1 participants]