[Model] Enable BNB support for qwen2_5_omni_thinker

[jeejeelee]

Purpose

• Enable bitsandbytes quantization for qwen2_5_omni_thinker, fix [Feature]: qwen2.5 omni doesn't support bnb quantification. #23240
• Add get_mm_mapping and SupportLoRA, deleted by Migrate Qwen2 inputs to TensorSchema #23475

Test Plan

python examplexamples/offline_inference/vision_language.py \                                                                                                             
    --modality image \
    --model-type qwen2_5_omni

• The model utilizes Qwen/Qwen2.5-Omni-3B, with additional parameters: quantization="bitsandbytes" and enable_lora=True

Test Result

I can generated the reasonable result on my local device:

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Well, this image shows a tall tower, which looks like the Tokyo Skytree. There are also lots of pink cherry blossom branches in the foreground. The sky is blue and clear. It's a really nice scene. What do you think about it?
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Well, this image shows the Tokyo Skytree. It's a tall tower with a lot of intricate details on its top. And there are cherry blossom trees in the foreground, with lots of pink flowers. The sky is clear and blue. It's a really nice picture. So, what do you think about it?
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Well, this image shows a tall tower with a lot of pink flowers around it. The flowers are in full bloom, and the tower is kind of in the background. It looks like a beautiful scene, maybe a place in Japan. What do you think about it?
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Well, this image shows a tall tower in the background. It's surrounded by cherry blossom trees. The flowers are in full bloom, with lots of pink blossoms. The sky is clear and blue. It looks like a beautiful spring scene. What do you think about it?

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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.
• (Optional) Release notes update. If your change is user facing, please update the release notes draft in the Google Doc.

[gemini-code-assist]

Code Review

This pull request re-enables LoRA support for the qwen2_5_omni_thinker model, which is a prerequisite for bitsandbytes (BNB) quantization. The changes correctly add the SupportsLoRA interface, define the packed_modules_mapping for merged layers in both the language and vision components, and implement the get_mm_mapping method to identify the different parts of the multimodal model. These changes appear correct and necessary to fix the LoRA functionality that was removed in a previous refactoring. The implementation aligns well with vLLM's patterns for multimodal LoRA support. I have reviewed the code and found no issues.