NVIDIA / NVIDIA/TensorRT-LLM

[Bug] test_nvfp4_gather_grouped_gemm_act_fusion_blackwell flaky on B300: ~0.05% mismatch vs rtol 1e-4, varying parametrizations

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Pytorch
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Python
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Description

Summary

unittest/_torch/thop/parallel/test_cute_dsl_moe.py::test_nvfp4_gather_grouped_gemm_act_fusion_blackwell fails intermittently in pre-merge stage B300-PyTorch-2 with:

Exception: Mismatch percentage is ~0.05 for rtol 0.000100

Observed twice on unrelated PR #15730 with different parametrizations:

  • [8192-8-1-256-relu2] — L0_MergeRequest_PR build 47303 (mismatch 0.050421)
  • [128-1-32-128-relu2] — L0_MergeRequest_PR build 47362 (mismatch 0.054688)

Both runs were on current main bases; the test passes in other runs, so this is a marginal-tolerance flake on B300 rather than a deterministic regression.

Impact

Pre-merge blocker (fail-fast) for unrelated PRs when B300-PyTorch-2 is selected and the tolerance coin-flip loses.

Ask

Loosen rtol / deflake the kernel comparison for B300, or waive until fixed.

Contributor guide

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First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start with unittest/_torch/thop/parallel/test_cute_dsl_moe.py::test_nvfp4_gather_grouped_gemm_act_fusion_blackwell and reproduce the reported parametrizations on B300-PyTorch-2. Inspect the comparison tolerance and kernel test behavior, then validate the chosen deflake or tolerance change across the affected cases. Done means intermittent failures no longer block unrelated pre-merge runs.

Written by the indexing model from the issue text.

Assessment

Tech stack
python, pytorch
Domain
machine-learning, testing-qa
Issue type
Bug
Difficulty
4/5
Estimated time
3-5 days
Activity status
Quiet
Clarity
Mostly clear
Newbie friendliness
55/100

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