bench: Add MMMU benchmark for vLM (#3562)

2025-02-23 00:10:59 +08:00
parent 9087694006
commit 45205d88a0
9 changed files with 1026 additions and 7 deletions
--- a/benchmark/mmmu/bench_sglang.py
+++ b/benchmark/mmmu/bench_sglang.py
@@ -0,0 +1,101 @@
+"""
+    Bench the sglang-hosted vLM with benchmark MMMU
+
+    Usage:
+        python benchmark/mmmu/bench_sglang.py --model-path Qwen/Qwen2-VL-7B-Instruct --chat-template qwen2-vl
+
+    The eval output will be logged
+"""
+
+import argparse
+import dataclasses
+import random
+import re
+from io import BytesIO
+
+from data_utils import save_json
+from eval_utils import (
+    EvalArgs,
+    eval_result,
+    get_sampling_params,
+    parse_multi_choice_response,
+    prepare_samples,
+)
+from tqdm import tqdm
+
+from sglang import Engine
+from sglang.srt.conversation import chat_templates
+from sglang.srt.server_args import ServerArgs
+
+
+def eval_mmmu(args):
+    server_args = ServerArgs.from_cli_args(args)
+    eval_args = EvalArgs.from_cli_args(args)
+
+    if server_args.chat_template is None:
+        raise ValueError("Chat template must be provided for this benchmark")
+
+    samples = prepare_samples(eval_args)
+
+    backend = Engine(**dataclasses.asdict(server_args))
+
+    out_samples = dict()
+
+    sampling_params = get_sampling_params(eval_args)
+
+    conv = chat_templates[server_args.chat_template].copy()
+    image_token = conv.image_token
+    answer_dict = {}
+    for sample in tqdm(samples):
+        prompt = sample["final_input_prompt"]
+        image = sample["image"]
+        bytes_io = BytesIO()
+        image.save(bytes_io, format="PNG")
+        png_bytes = bytes_io.getvalue()
+
+        prompt = re.sub(r"<[^>]*>", image_token, prompt)
+
+        if image is not None:
+            gen_out = backend.generate(
+                prompt=prompt, image_data=[png_bytes], sampling_params=sampling_params
+            )["text"]
+
+            response = gen_out
+        else:  # multiple images actually
+            if sample["question_type"] == "multiple-choice":
+                all_choices = sample["all_choices"]
+                response = random.choice(all_choices)
+
+            else:
+                response = "INVALID GENERATION FOR MULTIPLE IMAGE INPUTS"
+
+        if sample["question_type"] == "multiple-choice":
+            pred_ans = parse_multi_choice_response(
+                response, sample["all_choices"], sample["index2ans"]
+            )
+        else:  # open question
+            pred_ans = response
+        out_samples[sample["id"]] = pred_ans
+
+        # set ground truth answer
+        answer_dict[sample["id"]] = {
+            "question_type": sample["question_type"],
+            "ground_truth": (
+                sample["correct_choice"]
+                if "correct_choice" in samples
+                else sample["answer"]
+            ),
+        }
+
+    args.output_path = f"{args.model_path}_val_sglang.json"
+    save_json(args.output_path, out_samples)
+    eval_result(output_path=args.output_path, answer_dict=answer_dict)
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+    ServerArgs.add_cli_args(parser)
+    EvalArgs.add_cli_args(parser)
+    args = parser.parse_args()
+
+    eval_mmmu(args)