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[Benchmarks] Add video inputs to ShareGPTDataset. (#23199)
Signed-off-by: Chenheli Hua <huachenheli@outlook.com>
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@ -32,6 +32,14 @@ become available.
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<div>Note that the images need to be downloaded separately. For example, to download COCO's 2017 Train images:</div>
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<code>wget http://images.cocodataset.org/zips/train2017.zip</code>
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</td>
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</tr>
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<tr>
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<td><strong>ShareGPT4Video (Video)</strong></td>
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<td style="text-align: center;">✅</td>
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<td style="text-align: center;">✅</td>
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<td>
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<code>git clone https://huggingface.co/datasets/ShareGPT4Video/ShareGPT4Video</code>
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</td>
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</tr>
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<tr>
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<td><strong>BurstGPT</strong></td>
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@ -231,7 +239,7 @@ vllm serve Qwen/Qwen2-VL-7B-Instruct
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```bash
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vllm bench serve \
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--backend openai-chat \
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--endpoint-type openai-chat \
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--endpoint-type openai-chat \
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--model Qwen/Qwen2-VL-7B-Instruct \
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--endpoint /v1/chat/completions \
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--dataset-name hf \
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@ -246,7 +254,7 @@ vllm bench serve \
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```bash
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vllm bench serve \
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--backend openai-chat \
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--endpoint-type openai-chat \
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--endpoint-type openai-chat \
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--model Qwen/Qwen2-VL-7B-Instruct \
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--endpoint /v1/chat/completions \
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--dataset-name hf \
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@ -612,7 +620,7 @@ vllm bench serve \
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--prefix-repetition-prefix-len 512 \
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--prefix-repetition-suffix-len 128 \
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--prefix-repetition-num-prefixes 5 \
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--prefix-repetition-output-len 128
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--prefix-repetition-output-len 128
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```
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</details>
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@ -687,4 +695,31 @@ python benchmarks/benchmark_serving.py \
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--endpoint /v1/chat/completion
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```
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### Videos (ShareGPT4Video)
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Start vLLM:
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```bash
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python -m vllm.entrypoints.openai.api_server \
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--model Qwen/Qwen2.5-VL-7B-Instruct \
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--dtype bfloat16 \
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--limit-mm-per-prompt '{"video": 1}' \
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--allowed-local-media-path /path/to/sharegpt4video/videos
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```
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Send requests with videos:
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```bash
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python benchmarks/benchmark_serving.py \
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--backend openai-chat \
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--model Qwen/Qwen2.5-VL-7B-Instruct \
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--dataset-name sharegpt \
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--dataset-path /path/to/ShareGPT4Video/llava_v1_5_mix665k_with_video_chatgpt72k_share4video28k.json \
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--num-prompts 100 \
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--save-result \
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--result-dir ~/vllm_benchmark_results \
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--save-detailed \
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--endpoint /v1/chat/completion
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```
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</details>
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@ -293,6 +293,41 @@ def process_image(image: Any) -> Mapping[str, Any]:
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)
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def process_video(video: Any) -> Mapping[str, Any]:
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"""
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Process a single video input and return a multimedia content dictionary.
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Supports the following input types:
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1. Dictionary with raw video bytes: - Expects a dict with a 'bytes' key
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containing raw video data.
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2. String input: - Treats the string as a URL or local file path. -
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Prepends "file://" if the string doesn't start with "http://" or
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"file://". - Returns a dictionary with the image URL.
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Raises:
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ValueError: If the input is not a supported type.
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"""
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if isinstance(video, dict) and "bytes" in video:
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video_bytes = video["bytes"]
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video_base64 = base64.b64encode(video_bytes).decode("utf-8")
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return {
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"type": "video_url",
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"video_url": {"url": f"data:video/mp4;base64,{video_base64}"},
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}
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if isinstance(video, str):
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video_url = (
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video if video.startswith(("http://", "file://")) else f"file://{video}"
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)
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return {"type": "video_url", "video_url": {"url": video_url}}
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raise ValueError(
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f"Invalid video input {video}. Must be a string of local path/remote url, or a dictionary with raw video bytes in the form of `{{'bytes': raw_video_bytes}}`." # noqa: E501
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)
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# -----------------------------------------------------------------------------
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# Random Dataset Implementation (Synthetic Data)
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# -----------------------------------------------------------------------------
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@ -451,9 +486,10 @@ class ShareGPTDataset(BenchmarkDataset):
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skip_min_output_len_check=output_len is not None,
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):
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continue
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# TODO: Also support ShareGPT4Video.
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if image_path := entry.get("image"):
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mm_content = process_image(image_path)
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elif video_path := entry.get("video"):
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mm_content = process_video(video_path)
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else:
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mm_content = None
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if enable_multimodal_chat:
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@ -281,7 +281,7 @@ def process_image(image: Any) -> Mapping[str, Any]:
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"""
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Process a single image input and return a multimedia content dictionary.
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Supports three input types:
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Supports the following input types:
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1. Dictionary with raw image bytes: - Expects a dict with a 'bytes' key
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containing raw image data. - Loads the bytes as a PIL.Image.Image.
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@ -321,6 +321,41 @@ def process_image(image: Any) -> Mapping[str, Any]:
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" or str or dictionary with raw image bytes.")
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def process_video(video: Any) -> Mapping[str, Any]:
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"""
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Process a single video input and return a multimedia content dictionary.
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Supports the following input types:
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1. Dictionary with raw video bytes: - Expects a dict with a 'bytes' key
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containing raw video data.
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2. String input: - Treats the string as a URL or local file path. -
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Prepends "file://" if the string doesn't start with "http://" or
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"file://". - Returns a dictionary with the image URL.
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Raises:
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ValueError: If the input is not a supported type.
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"""
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if isinstance(video, dict) and 'bytes' in video:
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video_bytes = video['bytes']
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video_base64 = base64.b64encode(video_bytes).decode("utf-8")
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return {
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"type": "video_url",
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"video_url": {
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"url": f"data:video/mp4;base64,{video_base64}"
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},
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}
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if isinstance(video, str):
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video_url = (video if video.startswith(
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("http://", "file://")) else f"file://{video}")
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return {"type": "video_url", "video_url": {"url": video_url}}
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raise ValueError(
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f"Invalid video input {video}. Must be a string of local path/remote url, or a dictionary with raw video bytes in the form of `{{'bytes': raw_video_bytes}}`." # noqa: E501
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)
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# -----------------------------------------------------------------------------
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# Random Dataset Implementation (Synthetic Data)
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# -----------------------------------------------------------------------------
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@ -474,9 +509,10 @@ class ShareGPTDataset(BenchmarkDataset):
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skip_min_output_len_check=output_len
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is not None):
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continue
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# TODO: Also support ShareGPT4Video.
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if image_path := entry.get("image"):
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mm_content = process_image(image_path)
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elif video_path := entry.get("video"):
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mm_content = process_video(video_path)
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else:
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mm_content = None
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if enable_multimodal_chat:
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