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

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pytorch/pytorch#180367•Fetched 2026-04-16 06:34:59
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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 34 workflow(s) with 68 failures and 34 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_nested_mempool
  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_cuda.py

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

cc @ptrblck @msaroufim @eqy @jerryzh168 @tinglvv @nWEIdia

extent analysis

TL;DR

The test test_nested_mempool in test_cuda.py is likely failing due to flakiness 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_nested_mempool to find relevant log snippets.
  • 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_cuda.py for any potential issues or recent changes 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 provided information does not include specific error messages or stack traces, so it is difficult to determine the exact cause of the flakiness without further investigation.

Recommendation

Apply workaround: Analyze the workflow logs and debug the test as described in the guidance section to identify and fix the root cause of the flakiness.

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#docker error#permission error#memory optimization#batch processing#GPU compatibility

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