[Bugfix] Add random_seed to sample_hf_requests in benchmark_serving script (#9013)

Co-authored-by: Isotr0py <2037008807@qq.com>

benchmarks/benchmark_serving.py

@@ -202,6 +202,7 @@ def sample_hf_requests(
     dataset_split: str,
     num_requests: int,
     tokenizer: PreTrainedTokenizerBase,
+    random_seed: int,
     fixed_output_len: Optional[int] = None,
 ) -> List[Tuple[str, str, int, Optional[Dict[str, Collection[str]]]]]:
     dataset = load_dataset(dataset_path,
@@ -210,8 +211,8 @@ def sample_hf_requests(
                            streaming=True)
     assert "conversations" in dataset.features, (
         "HF Dataset must have 'conversations' column.")
-    filtered_dataset = dataset.shuffle().filter(
-        lambda x: len(x["conversations"]) >= 2)
+    filter_func = lambda x: len(x["conversations"]) >= 2
+    filtered_dataset = dataset.shuffle(seed=random_seed).filter(filter_func)
     sampled_requests: List[Tuple[str, int, int, Dict[str,
                                                      Collection[str]]]] = []
     for data in filtered_dataset:
@@ -646,6 +647,7 @@ def main(args: argparse.Namespace):
             dataset_split=args.hf_split,
             num_requests=args.num_prompts,
             tokenizer=tokenizer,
+            random_seed=args.seed,
             fixed_output_len=args.hf_output_len,
         )