[None][fix] Disable DeepGEMM for Qwen3 MoE Attention layers

[achartier]

Summary by CodeRabbit

• New Features
  • Added a configuration option to disable deep GEMM in Qwen3 attention, giving users finer control over attention compute behavior.
  • The MoE variant now initializes attention with deep GEMM disabled by default for consistent behavior out of the box.
• Chores
  • Updated initialization pathways to propagate the new configuration option without altering existing defaults for non-MoE setups.

Description

Disable DeepGEMM for Qwen3 MoE Attention layers. !8030 caused a regression as Qwen3 MoE models also use the Qwen3Attention class. Benchmarking shows DG has slightly worse performance, so disabling it for MoE models

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[achartier]

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[coderabbitai]

📝 Walkthrough

Walkthrough

Introduces a new boolean parameter disable_deep_gemm in Qwen3Attention, forwards it to the base class, and sets it to True when constructing attention within Qwen3MoEDecoderLayer. No other logic or behavior is modified.

Changes

Cohort / File(s)	Summary
Qwen3 Attention deep GEMM flag integration tensorrt_llm/_torch/models/modeling_qwen3.py, tensorrt_llm/_torch/models/modeling_qwen3_moe.py	Add disable_deep_gemm parameter to Qwen3Attention.init, propagate to super().init; update MoE decoder to instantiate Qwen3Attention with disable_deep_gemm=True.

Sequence Diagram(s)

sequenceDiagram
    actor Dev as Init
    participant MoE as Qwen3MoEDecoderLayer
    participant Attn as Qwen3Attention
    participant Base as BaseAttention

    Dev->>MoE: __init__()
    MoE->>Attn: Qwen3Attention(..., disable_deep_gemm=True)
    Attn->>Base: super().__init__(..., disable_deep_gemm=True)
    Note right of Base: Base receives flag and configures internals

    rect rgba(230,240,255,0.5)
    Note over MoE,Attn: MoE path explicitly disables deep GEMM
    end

    Dev->>Attn: Qwen3Attention(..., disable_deep_gemm=False) 
    Attn->>Base: super().__init__(..., disable_deep_gemm=False)
    Note right of Base: Default behavior when not in MoE

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Estimated code review effort

🎯 2 (Simple) | ⏱️ ~10 minutes

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❌ Failed checks (2 warnings)

Check name	Status	Explanation	Resolution
Description Check	⚠️ Warning	The PR description includes the Description, PR Checklist, and GitHub Bot Help sections as required by the repository template but leaves the Test Coverage section empty and retains the “@coderabbitai summary” placeholder without an actual summary. The template instructs authors to provide a clear summary at the top and to list relevant test cases under Test Coverage to ensure sufficient coverage for new code paths. Because these mandatory pieces of information are missing, the PR description is incomplete relative to the repository’s standards and additional details are needed before merging.	Please replace the “@coderabbitai summary” placeholder with an actual summary of the PR and populate the Test Coverage section with the names of new or updated test cases that validate the disable_deep_gemm behavior. Ensuring these details are present will satisfy the repository’s description template and support maintainability and CI validation. Once updated, the PR description should fully comply with the template.
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✅ Passed checks (1 passed)

Check name	Status	Explanation
Title Check	✅ Passed	The title “[None][fix] Disable DeepGEMM for Qwen3 MoE Attention layers” succinctly follows the repository’s prefix convention and accurately communicates the primary change of disabling DeepGEMM in Qwen3 MoE attention modules. It is clear, specific, and concise, without extraneous detail or vague terminology. Therefore, it effectively summarizes the main intent of the pull request.

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• tensorrt_llm/_torch/models/modeling_qwen3.py (2 hunks)
• tensorrt_llm/_torch/models/modeling_qwen3_moe.py (1 hunks)

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🔇 Additional comments (3)

tensorrt_llm/_torch/models/modeling_qwen3.py (1)

37-37: LGTM! Parameter addition and forwarding are correct.

The disable_deep_gemm parameter is properly added with a sensible default of False, maintaining existing behavior for non-MoE Qwen3 models while allowing MoE models to disable DeepGEMM. The parameter is correctly forwarded to the base class.

Also applies to: 75-75

tensorrt_llm/_torch/models/modeling_qwen3_moe.py (2)

168-172: LGTM! DeepGEMM correctly disabled for MoE attention.

The change appropriately disables DeepGEMM for Qwen3 MoE attention layers by passing disable_deep_gemm=True, addressing the performance regression identified in the PR objectives.

---

168-172: No action needed: Qwen3Attention instantiations are correctly configured – it’s used only in modeling_qwen3.py (default disable_deep_gemm=False) and modeling_qwen3_moe.py (disable_deep_gemm=True); no other occurrences found.

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