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pytorch - 💡(How to fix) Fix DISABLED test_unbacked_dtensor_op_db_norm_nuc_cpu_float32 (__main__.TestUnbackedDTensorOpsCPU)

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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.

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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 3 workflow(s) with 0 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_unbacked_dtensor_op_db_norm_nuc_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: distributed/tensor/test_dtensor_ops.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_unbacked_dtensor_op_db_norm_nuc_cpu_float32 is failing intermittently in CI and needs to be debugged by analyzing the workflow logs.

Guidance

  • To debug the issue, follow the provided debugging instructions: click on the workflow logs, expand the Test step, and grep for test_unbacked_dtensor_op_db_norm_nuc_cpu_float32 to find relevant log snippets.
  • Study the logs from multiple instances of the test run to identify patterns or clues that may indicate the cause of the flakiness.
  • Review the test file distributed/tensor/test_dtensor_ops.py to understand the test case and potential areas of failure.
  • Check the list of disabled tests at https://hud.pytorch.org/disabled for any related issues or patterns.

Notes

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

Recommendation

Apply workaround: temporarily enable the test and run it locally or in a controlled environment to gather more information about the failure, then debug and fix the issue.

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