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[Model] Enable --mm-encoder-tp-mode data for MiMo-V2.6 - #64179
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Signed-off-by: vllmellm <vllm.ellm@embeddedllm.com>
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Overview
Using
--mm-encoder-tp-mode dataon MimoV2.6 exposed a bug - under data parallel the vision attention collapsedtp_sizeto 1 but kept the process's tensor-parallel rank, so on any rank > 0 the per-head slice started past the end of the head range and the sink effect was silently dropped.Claims
supports_encoder_tp_data, and collapse the rank together with the size.Validation
pytest tests/models/multimodal/test_mimo_v2_omni.py # 4 passed, 2 skipped here; 3 of the 4 fail on mainEnd to end, TP4, MiMo-V2.6-Flash-MOPD, one boot per mode:
--mm-encoder-tp-mode dataweights)Details
This change is a correctness and availability fix, we do not claimed any performance gain.
Pull Request Checklist
I used vLLM's
/pr-checklistskill. (Mandatory for agents, optional for humans).AI assistance was used during the creation of this PR.
Design Fit: Minimizes impact on core components, reuses existing functionality, and justifies added complexity.
Testing and Validation: Validates the change and ensures any added tests are meaningful and reliable, with CI coverage or documented CI resource constraints and validation performed outside CI.
Code Quality and Style: Keeps code and comments clear and concise, and updates relevant documentation and examples.
Pull Request Contents: Includes a brief summary and relevant links, supports claims with evidence, explains root causes and implementation trade-offs, and follows the contributing guide.