From de590a6ce53a576844d090b97651970bd7520216 Mon Sep 17 00:00:00 2001 From: Roger Wang Date: Thu, 23 Jan 2025 22:09:56 -0800 Subject: [PATCH] vision Signed-off-by: Roger Wang --- benchmarks/benchmark_serving.py | 32 ++++++++++++-------------------- 1 file changed, 12 insertions(+), 20 deletions(-) diff --git a/benchmarks/benchmark_serving.py b/benchmarks/benchmark_serving.py index bc026b0ec1ca6..63d2c3f7c7dd9 100644 --- a/benchmarks/benchmark_serving.py +++ b/benchmarks/benchmark_serving.py @@ -200,7 +200,7 @@ def sample_sonnet_requests( return sampled_requests -def sample_mmmu_pro_vision_requests( +def sample_vision_arena_requests( dataset, num_requests: int, tokenizer: PreTrainedTokenizerBase, @@ -212,13 +212,7 @@ def sample_mmmu_pro_vision_requests( if len(sampled_requests) == num_requests: break - # MMMU-Pro vision direct prompt - # Ref: https://github.com/MMMU-Benchmark/MMMU/blob/6ce42f4d8f70c1841c67867152648974415b5cac/mmmu-pro/prompts.yaml#L5 - prompt = ( - "Answer with the option letter from the given choices directly. " - "The last line of your response should be of the following " - "format: 'Answer: $LETTER' (without quotes) where LETTER is one of " - "options.") + prompt = data["turns"][0][0]['content'] prompt_token_ids = tokenizer(prompt).input_ids if fixed_output_len is None: @@ -230,10 +224,10 @@ def sample_mmmu_pro_vision_requests( output_len = fixed_output_len assert isinstance( - data["image"], + data["images"][0], Image), ("Input image format must be `PIL.Image.Image`, " f"given {type(data['image'])}.") - image: Image = data["image"] + image: Image = data["images"][0] image = image.convert("RGB") image_data = io.BytesIO() image.save(image_data, format='JPEG') @@ -252,7 +246,7 @@ def sample_mmmu_pro_vision_requests( def sample_hf_requests( dataset_path: str, - dataset_subset: str, + dataset_subset: Optional[str], dataset_split: str, num_requests: int, tokenizer: PreTrainedTokenizerBase, @@ -260,19 +254,17 @@ def sample_hf_requests( fixed_output_len: Optional[int] = None, ) -> List[Tuple[str, str, int, Optional[Dict[str, Collection[str]]]]]: - # Special case for MMMU-Pro vision dataset - if dataset_path == 'MMMU/MMMU_Pro' and dataset_subset == 'vision': - assert dataset_split == "test" + # Special case for vision_arena dataset + if dataset_path == 'lmarena-ai/vision-arena-bench-v0.1' \ + and dataset_subset is None: + assert dataset_split == "train" dataset = load_dataset(dataset_path, name=dataset_subset, split=dataset_split, streaming=True) - assert "image" in dataset.features, ( - "MMMU/MMMU_Pro vision dataset must have 'image' column.") - filter_func = lambda x: isinstance(x["image"], Image) - dataset = dataset.shuffle(seed=random_seed).filter(filter_func) - return sample_mmmu_pro_vision_requests(dataset, num_requests, - tokenizer, fixed_output_len) + dataset = dataset.shuffle(seed=random_seed) + return sample_vision_arena_requests(dataset, num_requests, tokenizer, + fixed_output_len) dataset = load_dataset(dataset_path, name=dataset_subset,