[Model] support input embeddings for qwen2vl

[whyiug]

FILL IN THE PR DESCRIPTION HERE

FIX #8857

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[DarkLight1337]

@fyabc can you assist OP to address #6613 (comment)? Thanks in advance for your help!

[whyiug]

Adding to our usage scenarios.
We need to perform multiple VQA tasks (same image, different questions) using several Qwen2VL models(finetuned). In this case, I can use this feature to deploy image encoding and language model inference in different pods. This will save much time by avoiding redundant image downloading and image encoding for each language model inference.
@fyabc

[whyiug]

Can vllm support this multmodal input format?
To support multiple images, videos, dynamic resolution, and M-RoPE in the future.
@ywang96 please have a look and consider it.

    image_embeds = ……
    # mm_data['image'] = image_embeds
    mm_data['image'] = {
        "image_embeds": image_embeds,
        "image_grid_thw":  inputs["image_grid_thw"],
    }

    llm_inputs = {
        "prompt": prompt,
        "multi_modal_data": mm_data,
    }

    outputs = llm.generate([llm_inputs], sampling_params=sampling_params)
    generated_text = outputs[0].outputs[0].text

[DarkLight1337]

Thanks for implementing this! Some comments.

Can vllm support this multmodal input format?
To support multiple images, videos, dynamic resolution, and M-RoPE in the future.

For now, I suggest you override the default input mapper (in register_image_input_mapper) to support it for this model specifically. To maintain a consistent API, the regular case of just inputting a tensor should still be supported.

[DarkLight1337]

You should also update the Supported Models page in the docs to indicate that the model supports image embeddings.

[whyiug]

Thanks for implementing this! Some comments.感谢您实施此操作！一些评论。

Can vllm support this multmodal input format?vllm可以支持这种多模态输入格式吗？
To support multiple images, videos, dynamic resolution, and M-RoPE in the future.未来支持多图像、视频、动态分辨率和M-RoPE。

For now, I suggest you override the default input mapper (in register_image_input_mapper) to support it for this model specifically. To maintain a consistent API, the regular case of just inputting a tensor should still be supported.目前，我建议您覆盖默认输入映射器（在register_image_input_mapper中）以专门支持该模型。为了保持 API 的一致性，仍应支持仅输入张量的常规情况。

We have already modified the default input mapper for Qwen2VL (image_input_mapper_for_qwen2_vl). Are you suggesting that we create an additional mapper? I can incorporate logic such as elif isinstance(data, torch.Tensor) to support input tensors in image_input_mapper_for_qwen2_vl; however, please note that the results may be somewhat inconsistent with the previous implementation. This is due to the fact that Qwen2VL requires image_grid_thw for calculating M-RoPE.

Right now it only works on Qwen2VL and does not affect the inputs of other models.
What I'm thinking about is how vllm will come to expand the image embedding inputs in the future, as well as embedding inputs support for video.
By the way, I have implemented Qwen2VL for input video embedding, haven't submitted it.

[DarkLight1337]

For now, I suggest you override the default input mapper (in register_image_input_mapper) to support it for this model specifically. To maintain a consistent API, the regular case of just inputting a tensor should still be supported.目前，我建议您覆盖默认输入映射器（在register_image_input_mapper中）以专门支持该模型。为了保持 API 的一致性，仍应支持仅输入张量的常规情况。

We have already modified the default input mapper for Qwen2VL (image_input_mapper_for_qwen2_vl). Are you suggesting that we create an additional mapper? I can incorporate logic such as elif isinstance(data, torch.Tensor) to support input tensors in image_input_mapper_for_qwen2_vl; however, please note that the results may be somewhat inconsistent with the previous implementation. This is due to the fact that Qwen2VL requires image_grid_thw for calculating M-RoPE.

Sorry, I forgot there is already an existing input mapper. In that case, you can update the existing one.

[whyiug]

@DarkLight1337 This ci's failure seems to have nothing to do with my changes. please have a look.

[DarkLight1337]

You should merge in the changes from main branch to resolve the CI failures.

[DarkLight1337]

You should also update the Supported Models page in the docs to indicate that the model supports image embeddings.

Since the input format is different for this model, I suggest also adding a note to the documentation to explain how to input embeddings for Qwen2-VL.

[whyiug]

You should also update the Supported Models page in the docs to indicate that the model supports image embeddings.

Since the input format is different for this model, I suggest also adding a note to the documentation to explain how to input embeddings for Qwen2-VL.

Thanks for your tips.
Specifically, we are conducting a trial run of Qwen2VL with the new input format, as the model utilizes additional parameters for calculating positional encoding.
I think this feature could be extended in the future with minicpmv that also supports multiple images, such as video inputs.
If you guys need it and agree with this, I might be able to refactor all.

[whyiug]

While it is a rare use case and probably inconsequential to most users, it is a great enhancement to our production environment.

[DarkLight1337]

You should also update the Supported Models page in the docs to indicate that the model supports image embeddings.

Since the input format is different for this model, I suggest also adding a note to the documentation to explain how to input embeddings for Qwen2-VL.

Thanks for your tips.
Specifically, we are conducting a trial run of Qwen2VL with the new input format, as the model utilizes additional parameters for calculating positional encoding.

Thanks, the example looks good.

I think this feature could be extended in the future with minicpmv that also supports multiple images, such as video inputs.
If you guys need it and agree with this, I might be able to refactor all.

@alex-jw-brooks are you already working on dynamic options to the input mapper?

[DarkLight1337]

I tested Qwen2-VL and can verify that the model still works on regular image inputs. Assuming that you have already tested Qwen2-VL to work with embedding inputs, let's merge this first - follow-up work can be done in another PR.

[alex-jw-brooks]

Hey @DarkLight1337 - yup, I am working on it and should have a PR for passing dynamic processor / mapper options up within the next week or so!

[fyabc]

@whyiug @DarkLight1337 sorry for late response, I have checked the update and its okay to me. Very thanks to your contribution!

[micyan01]

This is very needed