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pytorch - 💡(How to fix) Fix DISABLED test_replicate_ignore_module (__main__.ReplicateFullyShardInit)

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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 5 workflow(s) with 0 failures and 5 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_replicate_ignore_module
  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/_composable/test_replicate.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

Enable and re-run the disabled test test_replicate_ignore_module to investigate and resolve the flakiness issue.

Guidance

  • Investigate the workflow logs linked in the issue to identify patterns or errors related to the test.
  • Follow the provided debugging instructions to find relevant log snippets for the test.
  • Study the logs from multiple instances of the test run to understand the cause of flakiness.
  • Consider re-enabling the test and running it locally or in a controlled environment to reproduce and debug the issue.

Notes

The issue lacks specific technical details about the test or the errors encountered, so a more targeted solution cannot be provided.

Recommendation

Apply workaround: Re-enable and re-run the test to gather more information and debug the issue, as the current state of the test (disabled) does not allow for direct resolution of the flakiness.

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#orchestration issue#cache issue#memory leak#API versioning#request timeout

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