[Model] Add Ovis2.5 PP support

[Isotr0py]

Purpose

• Fix [Feature]: Support pipeline parallelism for AIDC-AI/Ovis2.5-9B #23355
• Add PP support to Ovis2.5
• Expose use_data_parallel for ViT to support data parallel in the future after [Core] Allow disabling TP sharding for parallel Linear layer #23024

Test Plan

Test Result

(Optional) Documentation Update

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Essential Elements of an Effective PR Description Checklist

• The purpose of the PR, such as "Fix some issue (link existing issues this PR will resolve)".
• The test plan, such as providing test command.
• The test results, such as pasting the results comparison before and after, or e2e results
• (Optional) The necessary documentation update, such as updating supported_models.md and examples for a new model.

[gemini-code-assist]

Code Review

This pull request adds Pipeline Parallelism (PP) support for the Ovis2.5 model and introduces Tensor Parallelism (TP) for its Siglip2Navit vision backbone. The changes are extensive, replacing standard nn.Linear layers with vLLM's parallel equivalents and updating the model architecture to be compatible with distributed execution. Overall, the implementation looks solid, but I've found a critical issue in the weight loading logic that appears to be a copy-paste error and could lead to incorrect behavior.

[DarkLight1337]

Thanks, can you run the example script with PP=1 and PP=2 to check the correctness?

[Isotr0py]

With this revision, we can run the model test without flash-attn installed now:

tests/models/multimodal/generation/test_common.py::test_video_models[ovis2_5-test_case3]
  /kaggle/working/vllm/tests/models/multimodal/generation/vlm_utils/core.py:154: UserWarning: Test1:
  Matched tokens:       [151667, 198, 20002, 99601, 85106, 101042, 100678, 99487, 87140, 103027, 1773, 101140, 50930, 102650, 5122, 102833, 100469, 103645, 100811, 3837, 108391, 105666, 104433, 104972, 3837, 102196, 33108, 102936, 99165, 100243, 116434, 1773, 101889]
  hf:   '<think>\n用户现在需要分析为什么这个视频有趣。首先看画面：婴儿戴着眼镜，模仿大人读书的样子，动作和表情很滑稽。然后分解元素：\n\n1. 婴儿的“阅读”行为：婴儿模仿大人读书，动作笨拙但可爱，比如翻页、专注的样子，和成人读书的场景形成反差，很幽默。\n2. 眼镜的拟人化：婴儿戴眼镜，像是在认真阅读，这种拟人化的表现很有趣，因为婴儿戴眼镜是现实中不太常见的，加上模仿阅读，强化了喜剧效果。\n3. �'     {107799: -1.5044023990631104, 104449: -2.0981523990631104, 50930: -2.2387773990631104, 100062: -2.8325273990631104, 30534: -2.9419023990631104, 99172: -3.0044023990631104, 20412: -3.1762773990631104, 104107: -3.6137773990631104, 3837: -3.7856523990631104, 101348: -3.7856523990631104}
  vllm: '<think>\n用户现在需要分析为什么这个视频有趣。首先看画面：婴儿戴着眼镜，模仿大人读书的样子，动作和表情很滑稽。然后细节：婴儿的动作（翻书、抬手）像在认真阅读，眼镜的拟人化，还有环境（床上、背景的家具）营造的居家氛围，加上婴儿的天真可爱，模仿成人行为的反差萌，这些元素结合起来让视频有幽默感。\n\n首先，**拟人化与模仿**：婴儿戴着眼镜，模仿大人读书，这种“成人化”的行为在婴儿身上显得滑稽，因为婴儿本'     {104449: Logprob(logprob=-1.8062855005264282, rank=1, decoded_token='细节'), 107799: Logprob(logprob=-2.4156603813171387, rank=2, decoded_token='分解'), 30534: Logprob(logprob=-2.6187853813171387, rank=3, decoded_token='要'), 100374: Logprob(logprob=-2.6187853813171387, rank=4, decoded_token='结合'), 50930: Logprob(logprob=-2.7281603813171387, rank=5, decoded_token='看'), 20412: Logprob(logprob=-2.8531603813171387, rank=6, decoded_token='是'), 102122: Logprob(logprob=-2.9156603813171387, rank=7, decoded_token='场景'), 99719: Logprob(logprob=-3.0562853813171387, rank=8, decoded_token='环境'), 99172: Logprob(logprob=-3.4156603813171387, rank=9, decoded_token='想'), 3837: Logprob(logprob=-3.5250353813171387, rank=10, decoded_token='，')}
    comparator(

-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html
=============================================== 12 passed, 302 deselected, 29 warnings in 1048.85s (0:17:28) ================================================

[Isotr0py]

Have confirmed this test set can pass after increasing max_model_len to 8192.