[model] Support for Llava-Next-Video model #7559

TKONIY · 2024-08-15T15:57:19Z

Roadmap

Add VideoPlugin to MultiModalPlugin.

LLM.generate API for a single video input.

LLM.generate({
    "prompt": "<video> please summarize this video",
    "multi_modal_data": {
        "video": video # currently only support type of np.ndarry
    }
})

Support LlavaNextVideoForConditionalGeneration model with single video input.
[15 Aug. Update] Waiting for the configuration file in hugging-face to be fixed. https://huggingface.co/llava-hf/LLaVA-NeXT-Video-7B-hf/discussions/4
Add example for llava-next-video.

Support all kinds of video input type like transformers

VideoInput = Union[
    List["PIL.Image.Image"], # Supported
    "np.ndarray",
    "torch.Tensor",
    List["np.ndarray"],
    List["torch.Tensor"],
    List[List["PIL.Image.Image"]],
    List[List["np.ndarrray"]],
    List[List["torch.Tensor"]],
]

Support multiple image-video-mixed input.
Support Siglip.
Support Chat Completion APIs.
Support prefix caching

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DarkLight1337 · 2024-08-15T16:46:30Z

This is an exciting development! This should be the last of the common modality types to cover for now.

TKONIY · 2024-08-19T19:02:32Z

@DarkLight1337 @ywang96 The initial support for Llava-Next-Video is done, which is also the first support for video in vLLM. Could you help review this PR?

It now supports integrating a single video into a prompt with the "<video>" symbol. I am happy to tell you that compared to SGLang which fixes the number of input frames when launching the model, vLLM now has a stronger implementation that supports any number of input frames per video.

ywang96 · 2024-08-19T20:30:11Z

@DarkLight1337 @ywang96 The initial support for Llava-Next-Video is done, which is also the first support for video in vLLM. Could you help review this PR?

It now supports integrating a single video into a prompt with the "

This is great and thank you very much for making this contribution! @TKONIY

I will review this PR either today or tomorrow!

TKONIY · 2024-08-20T02:44:48Z

Thank you!

TKONIY · 2024-08-21T09:42:21Z

@DarkLight1337 @ywang96 The initial support for Llava-Next-Video is done, which is also the first support for video in vLLM. Could you help review this PR?
It now supports integrating a single video into a prompt with the "

This is great and thank you very much for making this contribution! @TKONIY

I will review this PR either today or tomorrow!

Dear @ywang96, are you available today to review this PR?

ywang96 · 2024-08-21T15:06:25Z

@TKONIY Reviewing it now!

ywang96

Thank you for the PR @TKONIY! It seems that this PR only focuses on the offline inference, is that correct? OpenAI Vision API does support video frames as input, so we should make changes to our frontend to support the end-to-end online inference. (This can be in a later PR if you plan to work on it as well)

Overall I think PR is in the right track! I left a few comments as the first round of the review, mostly regarding the code cleanups. Please take a look, thanks!

examples/offline_inference_vision_language.py

vllm/model_executor/models/llava_next_video.py

vllm/multimodal/video.py

vllm/model_executor/models/llava_next_video.py

vllm/transformers_utils/image_processor.py

litianjian · 2024-08-22T13:12:35Z

vllm/model_executor/models/llava_next_video.py

+    tokens_per_frame = get_llava_next_video_frame_feature_size(hf_config)
+    video_feature_size = frames_per_video * tokens_per_frame
+
+    if isinstance(vision_config, CLIPVisionConfig):


I think LLaVA models should enable the Siglip vision encoder.

You are right! It seems not complicated, but I haven't had time to verify the Siglip implementation. I would like to leave this to other PRs.

I am excited about it. Many of our models use the siglip. BTW, I am currently using your PR to verify our video models.

Feel free to take a look at our llava-next implementation, where we allow both CLIP and SIGLIP to be the vision tower

Thanks! I saw it in Llava Next implementation. I'll try.

@litianjian @ywang96 I tried to integrate SIGLIP like llava-next did. But I am not confident about its correctness. If would be nice if you could have a check on my latest commits.

TKONIY · 2024-08-22T18:45:07Z

Thank you for the PR @TKONIY! It seems that this PR only focuses on the offline inference, is that correct? OpenAI Vision API does support video frames as input, so we should make changes to our frontend to support the end-to-end online inference. (This can be in a later PR if you plan to work on it as well)

Overall I think PR is in the right track! I left a few comments as the first round of the review, mostly regarding the code cleanups. Please take a look, thanks!

Thanks for your review. It would be exciting if video input is supported by chat completion APIs. I have read the code of our front end and I think it requires changes to some interfaces, so I did not implement it in this PR. I may open an RFC to discuss it if I got time.

TKONIY · 2024-08-23T01:22:56Z

@ywang96 Thanks for your review! I have resolved most of the comments except max_llm_tokens. Please have a check. Thank you!

ywang96 · 2024-08-23T15:54:05Z

@ywang96 Thanks for your review! I have resolved most of the comments except max_llm_tokens. Please have a check. Thank you!

Thank you for addressing my comments! I have replied regarding your question as well!

Could you add a correctness test for this model in tests/models, like for all other models we have?

TKONIY · 2024-08-26T15:31:49Z

@ywang96 Thanks for your review! I have resolved most of the comments except max_llm_tokens. Please have a check. Thank you!

Thank you for addressing my comments! I have replied regarding your question as well!

Could you add a correctness test for this model in tests/models, like for all other models we have?

I am working on it. But I am busy with a conference this week. So the progress would not be fast. Sorry.

ywang96 · 2024-08-26T16:12:26Z

@ywang96 Thanks for your review! I have resolved most of the comments except max_llm_tokens. Please have a check. Thank you!

Thank you for addressing my comments! I have replied regarding your question as well!
Could you add a correctness test for this model in tests/models, like for all other models we have?

I am working on it. But I am busy with a conference this week. So the progress would not be fast. Sorry.

@TKONIY No worries at all and I can work on adding the test too if you don't mind. Thank you for the contribution!

TKONIY · 2024-08-31T05:43:32Z

@ywang96 Thanks for your review! I have resolved most of the comments except max_llm_tokens. Please have a check. Thank you!

Thank you for addressing my comments! I have replied regarding your question as well!
Could you add a correctness test for this model in tests/models, like for all other models we have?

I am working on it. But I am busy with a conference this week. So the progress would not be fast. Sorry.

@TKONIY No worries at all and I can work on adding the test too if you don't mind. Thank you for the contribution!

I am back and working on it now.

ywang96 · 2024-08-31T06:11:48Z

@ywang96 Thanks for your review! I have resolved most of the comments except max_llm_tokens. Please have a check. Thank you!

Thank you for addressing my comments! I have replied regarding your question as well!
Could you add a correctness test for this model in tests/models, like for all other models we have?

I am working on it. But I am busy with a conference this week. So the progress would not be fast. Sorry.

@TKONIY No worries at all and I can work on adding the test too if you don't mind. Thank you for the contribution!

I am back and working on it now.

Hey @TKONIY! Sounds good - I was actually just working on this branch but still run into the issue of ValueError: The checkpoint you are trying to load has model type `llava_next_video` but Transformers does not recognize this architecture. This could be because of an issue with the checkpoint, or because your version of Transformers is out of date.. Are you also seeing this in your dev environment?

Also FYI, #8049 should be merged pretty soon in case you also want to add the frontend support.

TKONIY · 2024-08-31T06:29:53Z

@ywang96 Thanks for your review! I have resolved most of the comments except max_llm_tokens. Please have a check. Thank you!

Thank you for addressing my comments! I have replied regarding your question as well!
Could you add a correctness test for this model in tests/models, like for all other models we have?

I am working on it. But I am busy with a conference this week. So the progress would not be fast. Sorry.

@TKONIY No worries at all and I can work on adding the test too if you don't mind. Thank you for the contribution!

I am back and working on it now.

Hey @TKONIY! Sounds good - I was actually just working on this branch but still run into the issue of ValueError: The checkpoint you are trying to load has model type `llava_next_video` but Transformers does not recognize this architecture. This could be because of an issue with the checkpoint, or because your version of Transformers is out of date.. Are you also seeing this in your dev environment?

Also FYI, #8049 should be merged pretty soon in case you also want to add the frontend support.

There is an error in the newest release version of the Transformers library. I fixed them with this commit huggingface/transformers@a27182b so that vLLM can correctly load the model config. Therefore, vLLM could only run with the Transformers library after this commit, which has not been released.

ywang96 · 2024-08-31T08:09:25Z

vllm/model_executor/models/llava_next_video.py

+        video_pixels = inputs["data"]
+
+        if isinstance(video_pixels, torch.Tensor):
+            b, num_frames, c, h, w = video_pixels.shape


For some reason the shape of video_pixels has an additional dimension between batch size and num_frames so I had to change this line to b, _, num_frames, c, h, w = video_pixels.shape to make this PR work with the main branch of transformers

I think this is due to the recent update to batched inputs, which introduced an additional level to the tensor shape where the second dimension now refers to the number of multimodal inputs (here, the number of videos).

I think it is because of the multi-multimodal input supports. My PR doesn't support multiple video and images per input yet. So I will just leave it as b, _, num_frames, c, h, w yet.

DarkLight1337 · 2024-09-10T10:35:50Z

Can you check the build failure for AMD? Other PRs don't have this problem so it is likely caused by your changes.

TKONIY · 2024-09-10T12:49:24Z

Can you check the build failure for AMD? Other PRs don't have this problem so it is likely caused by your changes.

I will check, thank you.

Co-authored-by: Roger Wang <[email protected]> Co-authored-by: Cyrus Leung <[email protected]> Co-authored-by: Cyrus Leung <[email protected]>

PancakeAwesome · 2024-09-14T14:43:33Z

So we can now use the main branch to implement qwenvl2, internvl2 and other multi-modal models of openai vllm server video inference?

DarkLight1337 · 2024-09-14T14:49:44Z

No, OpenAI API support is not out yet (unless you consider multi-image input).

PancakeAwesome · 2024-09-14T14:52:23Z

No, OpenAI API support is not out yet (unless you consider multi-image input).不，OpenAI API目前还不支持这种功能（除非你把多张图片作为输入）。

So you mean that the openai api must support video input?

DarkLight1337 · 2024-09-14T14:55:19Z

I mean that for now, you can pass in multiple images as a "video" to the model. Explicit video support will be added later as mentioned in #7558.

Co-authored-by: Roger Wang <[email protected]> Co-authored-by: Cyrus Leung <[email protected]> Co-authored-by: Cyrus Leung <[email protected]> Signed-off-by: Alvant <[email protected]>

Co-authored-by: Roger Wang <[email protected]> Co-authored-by: Cyrus Leung <[email protected]> Co-authored-by: Cyrus Leung <[email protected]> Signed-off-by: Amit Garg <[email protected]>

Co-authored-by: Roger Wang <[email protected]> Co-authored-by: Cyrus Leung <[email protected]> Co-authored-by: Cyrus Leung <[email protected]> Signed-off-by: LeiWang1999 <[email protected]>

TKONIY mentioned this pull request Aug 15, 2024

[RFC]: Support for video input #7558

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TKONIY force-pushed the llava-next-video branch from c27fd58 to d95701b Compare August 15, 2024 16:21

DarkLight1337 mentioned this pull request Aug 15, 2024

[RFC]: Multi-modality Support on vLLM #4194

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DarkLight1337 self-assigned this Aug 15, 2024

TKONIY force-pushed the llava-next-video branch 2 times, most recently from 2beafbe to d6c783b Compare August 19, 2024 18:53

TKONIY marked this pull request as ready for review August 19, 2024 18:54

TKONIY force-pushed the llava-next-video branch from 393f206 to 3179393 Compare August 19, 2024 18:56

TKONIY force-pushed the llava-next-video branch from 12f4d45 to d4a0112 Compare August 20, 2024 12:19

ywang96 reviewed Aug 21, 2024

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TKONIY force-pushed the llava-next-video branch from e28f0b6 to 65dd96a Compare August 22, 2024 08:01

litianjian reviewed Aug 22, 2024

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DarkLight1337 mentioned this pull request Aug 29, 2024

[Model][VLM] Add Qwen2-VL model support #7905

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ywang96 reviewed Aug 31, 2024

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TKONIY force-pushed the llava-next-video branch from 46960dc to 925c49e Compare August 31, 2024 16:01

TKONIY added 2 commits September 10, 2024 09:48

update notes

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TKONIY force-pushed the llava-next-video branch from 44e239b to 6d481dd Compare September 10, 2024 09:48

Fix notes

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Fix dockerfile rocm

66bf496

DarkLight1337 added the ready ONLY add when PR is ready to merge/full CI is needed label Sep 10, 2024

TKONIY and others added 5 commits September 10, 2024 18:17

Add open-cv for tests

808dcae

Merge branch 'main' into llava-next-video

bdf429d

Skip LLaVA-NeXT-Video tests for now

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Fix missing reason

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Reword

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DarkLight1337 enabled auto-merge (squash) September 11, 2024 03:35

youkaichao disabled auto-merge September 11, 2024 05:21

youkaichao merged commit 6a512a0 into vllm-project:main Sep 11, 2024
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AlpinDale mentioned this pull request Dec 25, 2024

vlm: add support for video modality + llava next video model aphrodite-engine/aphrodite-engine#1014

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[model] Support for Llava-Next-Video model #7559

[model] Support for Llava-Next-Video model #7559

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[model] Support for Llava-Next-Video model #7559

[model] Support for Llava-Next-Video model #7559

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