[Model] add colqwen2_vl code & inference

[BloomBerry]

Add support for ColQwen2VL model
Description
This PR adds support for the ColQwen2VL model to vLLM. ColQwen2VL is an efficient document retrieval vision language model based on Qwen2VL, as described in the paper "ColPali: Efficient Document Retrieval with Vision Language Models". The model is designed to generate embeddings rather than text outputs, making it suitable for document retrieval applications.
Key implementation details:
Extended the existing Qwen2VL implementation for ColQwen2VL compatibility
Implemented custom text projection layer and L2 normalization for embedding generation
Added appropriate processing utilities for image and video inputs
Overrode forward, compute_logits and sample methods to optimize for embedding output
This implementation enables users to leverage ColQwen2VL's multimodal document retrieval capabilities through vLLM's efficient serving infrastructure.
Testing
Tested with sample image inputs
Verified embedding output format and dimensions
Confirmed compatibility with HuggingFace ColQwen2VL models

[github-actions]

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[DarkLight1337]

Thanks for implementing this! Can you update the following files as well?

• Supported Models page
• Test registry tests/models/test_registry.py
• Model correctness tests tests/models/embedding/vision_language
• Processor correctness tests tests/models/multimodal/processing/test_common.py