[None][fix] reject incompatible cached low-M GEMM tactics

[Wanli-Jiang]

Dev Engineer Review

• Cached direct GEMM tactics are validated against runtime (M, N, K) dimensions.
• Incompatible tactics fall back to cuBLAS.
• M-dimension tuning uses exact profiles for M=1 through M=8 and coarse buckets for larger values.
• The public API remains unchanged.
• No configuration or test-list files changed.

QA Engineer Review

• Added test_cached_direct_tactic_uses_exact_small_m_and_validates_large_m.
• The test covers exact-M cache lookup, incompatible tactic rejection, cuBLAS fallback, numerical correctness, and split-K exclusion.
• Test-list coverage requires confirmation for the added test.
• Verdict: needs follow-up.

Description

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• tensorrt_llm/_torch/modules/low_m_gemm.py
• tests/unittest/_torch/modules/test_low_m_gemm.py

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Walkthrough

The change preserves exact small-M tuning buckets, validates cached direct GEMM tactics against runtime shapes, and falls back to cuBLAS when cached tactics are incompatible. An SM10x integration test verifies dispatch and output correctness.

Changes

Direct GEMM tactic validation

Layer / File(s)	Summary
M-dimension bucket mapping tensorrt_llm/_torch/modules/low_m_gemm.py	Direct-kernel-compatible values through M=8 retain exact buckets. Larger values use configured coarse buckets.
Cached tactic validation and fallback tensorrt_llm/_torch/modules/low_m_gemm.py, tests/unittest/_torch/modules/test_low_m_gemm.py	Cached direct tactics are validated against runtime (M, N, K) dimensions. Incompatible tactics use cuBLAS with tactic -1. The SM10x test verifies bucket selection, numerical correctness, and no split-K execution.

Estimated code review effort: 3 (Moderate) | ~20 minutes

Merge Risk: ⚪ Minimal · up to 058da

Cached low-M GEMM tactics now avoid incompatible direct-kernel dispatches by falling back to cuBLAS, preserving correct output for affected runtime shapes. The covered behavior has no remaining identified merge-blocking risk.

Suggested reviewers: bowenfu

🚥 Pre-merge checks | ✅ 4 | ❌ 1

❌ Failed checks (1 warning)

Check name	Status	Explanation	Resolution
Description check	⚠️ Warning	The description includes the template and marks the final checklist item, but it does not provide the required issue, solution, or test coverage details.	Add a concise Description section that explains the issue and solution. Add a Test Coverage section that names the new SM10x CUDA integration test and the scenarios it verifies. Review and mark the applicable checklist items individually.

✅ Passed checks (4 passed)

Check name	Status	Explanation
Title check	✅ Passed	The title clearly identifies a fix for incompatible cached low-M GEMM tactics and follows the required [None][type] format.
Docstring Coverage	✅ Passed	Docstring coverage is 85.71% which is sufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 7 functions across 2 files.
Linked Issues check	✅ Passed	Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check	✅ Passed	Check skipped because no linked issues were found for this pull request.

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Actionable comments posted: 3

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Inline comments:
In `@tensorrt_llm/_torch/modules/low_m_gemm.py`:
- Line 160: Update the inputs annotation in the affected function from
typing.List to the built-in list generic, using list[torch.Tensor], while
preserving the existing type and function behavior.
- Line 19: Update _M_TUNING_BUCKETS and gen_tuning_buckets so profiles are
generated for every exact small-M key through M=8, including 3, 5, 6, and 7,
matching _map_m_to_tuning_bucket. Add a cache round-trip test using one
non-power-of-two M value to verify the generated profile can be stored and
retrieved.

In `@tests/unittest/_torch/modules/test_low_m_gemm.py`:
- Line 301: Annotate the monkeypatch parameter in
test_cached_direct_tactic_uses_exact_small_m_and_validates_large_m with
pytest.MonkeyPatch, preserving the existing test behavior and return annotation.

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• tests/unittest/_torch/modules/test_low_m_gemm.py

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[tongyuantongyu]

There's some inconsistency in the CODEOWNERS file. Leave the real review to models-dev side.

[jiahanc]

lgtm

[Wanli-Jiang]

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PR_Github #71176 [ run ] completed with state FAILURE. Commit: 058daba
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