[https://nvbugs/5835925][fix] Add EPD disagg support for Qwen3 VL MoE

[2ez4bz]

Summary by CodeRabbit

• New Features

  • Added multimodal disaggregation support for Qwen3 VL MoE models.

• Refactor

  • Optimized key-value head configuration handling in model weight mapping for Qwen3 variants.
  • Enhanced test infrastructure with CI-friendly model simulation support.

_{✏️ Tip: You can customize this high-level summary in your review settings.}

Description

• Why?

Trying to instantiate a MultimodalEncoder for a Qwen3 VL MoE model would fail during weight loading.

• What?

This commit fixes the bug, alongside:

• explicit, intentional support for EPD for Qwen3 VL MoE.
• extends EPD unit tests for Qwen3 VL MoE, albeit with dummy weights.
• unit tests for the weight mapper fixes.

Test Coverage

• extends EPD unit tests for Qwen3 VL MoE, albeit with dummy weights.
• unit tests for the weight mapper fixes.

PR Checklist

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• Documentation updated as needed

• Update tava architecture diagram if there is a significant design change in PR.

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• Please check this after reviewing the above items as appropriate for this PR.

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[coderabbitai]

📝 Walkthrough

Walkthrough

The pull request refactors weight mapper property initialization to computed properties, applies multimodal disaggregation decorator support to Qwen3-VL MoE models, and extends test infrastructure to support fake Qwen3-VL models for CI-friendly testing scenarios.

Changes

Cohort / File(s)	Summary
Weight mapper property refactoring tensorrt_llm/_torch/models/checkpoints/hf/qwen3_moe_weight_mapper.py, tensorrt_llm/_torch/models/checkpoints/hf/qwen3vl_moe_weight_mapper.py	Converted _num_kv_heads from initialization-time field to computed properties. Qwen3MoeHfWeightMapper uses fallback logic (num_key_value_heads or num_attention_heads). Qwen3VLMoeHfWeightMapper distinguishes between TextConfig and VisionConfig, raising TypeError for unexpected types. Added imports for config types from transformers.
Multimodal decorator support tensorrt_llm/_torch/models/modeling_qwen3vl_moe.py	Applied @support_multimodal_disaggregated decorator to Qwen3MoeVLModel class. Added import of decorator from tensorrt_llm._torch.models.inputs. Added explanatory comment on decorator rationale.
Test infrastructure for fake models tests/unittest/_torch/multimodal/test_mm_encoder_standalone.py	Extended test fixtures and helpers to support lightweight fake Qwen3-VL-30B-A3B-FP8 model for CI environments. Added path constants, config modification helper, fake directory creation via symlinking, and checkpoint detection. Modified model_dir fixture signature to accept tmp_path_factory. Introduced helpers: _get_fake_qwen3_vl_30b_a3b_config(), _create_fake_qwen3_vl_30b_a3b_fp8_dir(), _get_fake_checkpoint_kwargs(), _is_fake_checkpoint(). Updated test fixtures and test methods to propagate fake checkpoint kwargs through encoder and LLM initialization paths. Added import for copy module.

Estimated code review effort

🎯 3 (Moderate) | ⏱️ ~20 minutes

🚥 Pre-merge checks | ✅ 2 | ❌ 1

❌ Failed checks (1 warning)

Check name	Status	Explanation	Resolution
Docstring Coverage	⚠️ Warning	Docstring coverage is 26.67% which is insufficient. The required threshold is 80.00%.	Write docstrings for the functions missing them to satisfy the coverage threshold.

✅ Passed checks (2 passed)

Check name	Status	Explanation
Title check	✅ Passed	The title clearly and specifically describes the main change: adding EPD (Early Parameter Disaggregation) support for Qwen3 VL MoE model, which directly aligns with the changeset.
Description check	✅ Passed	The description includes both required sections (Description with Why/What context and Test Coverage details) and follows the template structure with clear explanations of the bug fix and supporting changes.

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[2ez4bz]

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[tensorrt-cicd]

PR_Github #33411 [ run ] triggered by Bot. Commit: fb276fb

[tensorrt-cicd]

PR_Github #33411 [ run ] completed with state SUCCESS. Commit: fb276fb
/LLM/release-1.2/L0_MergeRequest_PR pipeline #213 completed with status: 'FAILURE'

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