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pytorch - ✅(Solved) Fix DISABLED test_hf_bert_ddp_aot_eager (__main__.TestFakeDistributedSingleProc) [1 pull requests, 2 comments, 2 participants]

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pytorch/pytorch#179484•Fetched 2026-04-08 03:00:44
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2
Participants
2
Timeline
79
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0
Author
malfetmalfet
Participants
malfetmalfetpytorch-bot[bot]pytorch-bot[bot]
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mentioned ×33subscribed ×33labeled ×9commented ×2

Root Cause

This test was disabled because it is failing on main branch (recent examples).

Fix Action

Fixed

PR fix notes

PR #179321: Consolidate gcc11 CPU Docker image into clang18

Description (problem / solution / changelog)

Stack from ghstack (oldest at bottom):

  • -> #179321

The pytorch-linux-jammy-py3.10-gcc11 and py3.10-clang18 Docker images were nearly identical. This consolidates them by installing both GCC 11 and Clang 18 in the clang18 image, and selecting the compiler at build time via CC/CXX env vars and update-alternatives based on the build-environment name.

The inductor-benchmarks gcc11 image is left unchanged for now.

Co-authored-by: Claude [email protected]

Changed files

  • .ci/docker/build.sh (modified, +3/-6)
  • .ci/pytorch/build.sh (modified, +3/-8)
  • .ci/pytorch/common.sh (modified, +13/-0)
  • .github/workflows/docker-builds.yml (modified, +0/-1)
  • .github/workflows/nightly.yml (modified, +1/-1)
  • .github/workflows/pull.yml (modified, +3/-3)
  • .github/workflows/trunk.yml (modified, +1/-1)
  • test/distributed/test_dynamo_distributed.py (modified, +24/-16)
  • test/test_tensorboard.py (modified, +2/-0)
RAW_BUFFERClick to expand / collapse

Platforms: linux

This test was disabled because it is failing on main branch (recent examples).

cc @awgu @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @pragupta @msaroufim @dcci @aditvenk @xmfan @mruberry @chauhang @penguinwu @bdhirsh @bobrenjc93 @aorenste

extent analysis

TL;DR

The test test_hf_bert_ddp_aot_eager in test_dynamo_distributed.py needs to be investigated and potentially updated to fix the failure on the main branch.

Guidance

  • Review the recent failure examples on torch-ci.com to understand the nature of the test failure.
  • Investigate the test_hf_bert_ddp_aot_eager test case in test_dynamo_distributed.py to identify potential issues with the test or the code it is testing.
  • Check for any recent changes in the main branch that could be causing the test to fail.
  • Consider re-enabling the test and running it locally to gather more information about the failure.

Notes

The provided information does not include details about the failure, so it's difficult to provide a more specific solution.

Recommendation

Apply workaround: Investigate and update the failing test case, as the issue seems to be related to a specific test and not a general problem that would be fixed by an upgrade.

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#training loop#device allocation#model download#tokenizer error#prompt formatting

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