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pytorch - 💡(How to fix) Fix DISABLED test_dtensor_basic_export (__main__.TestDTensorCompile) [2 comments, 2 participants]

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pytorch/pytorch#179690•Fetched 2026-04-09 07:50:38
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pytorch-bot[bot]pytorch-bot[bot]
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arkadip-maitraarkadip-maitrapytorch-bot[bot]pytorch-bot[bot]
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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

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 27 workflow(s) with 0 failures and 27 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_dtensor_basic_export
  4. There should be several instances run (as flaky tests are rerun in CI) from which you can study the logs.

Test file path: distributed/tensor/test_dtensor_compile.py

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

cc @awgu @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @pragupta @msaroufim @dcci @aditvenk @xmfan

extent analysis

TL;DR

The test test_dtensor_basic_export is failing intermittently in CI, and to fix it, we need to investigate the workflow logs to 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_dtensor_basic_export.
  • Study the logs from multiple instances of the test run to identify any patterns or common errors that may be causing the flakiness.
  • Check the test file distributed/tensor/test_dtensor_compile.py for any potential issues that could be contributing to the flakiness.
  • Review the list of disabled tests at https://hud.pytorch.org/disabled to see if there are any other related tests that may be experiencing similar issues.

Notes

The issue lacks specific technical details about the error messages or exceptions being encountered, so a more detailed analysis of the workflow logs is necessary to determine the root cause of the flakiness.

Recommendation

Apply workaround: Investigate and debug the test using the provided instructions to identify the root cause of the flakiness, rather than simply re-enabling the test or ignoring the issue.

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