[Benchmarking] Add disable_shuffle option for dataset loading (#26258)

Signed-off-by: Yasmin Moslem <48152713+ymoslem@users.noreply.github.com>

vllm/benchmarks/datasets.py

@@ -96,6 +96,8 @@ class BenchmarkDataset(ABC):
         self,
         dataset_path: Optional[str] = None,
         random_seed: int = DEFAULT_SEED,
+        disable_shuffle: bool = False,
+        **kwargs,
     ) -> None:
         """
         Initialize the BenchmarkDataset with an optional dataset path and random
@@ -111,6 +113,7 @@ class BenchmarkDataset(ABC):
         # Set the random seed, ensuring that a None value is replaced with the
         # default seed.
         self.random_seed = random_seed if random_seed is not None else self.DEFAULT_SEED
+        self.disable_shuffle = disable_shuffle
         self.data = None
 
     def apply_multimodal_chat_transformation(
@@ -1044,7 +1047,8 @@ class ShareGPTDataset(BenchmarkDataset):
             if "conversations" in entry and len(entry["conversations"]) >= 2
         ]
         random.seed(self.random_seed)
-        random.shuffle(self.data)
+        if not getattr(self, "disable_shuffle", False):
+            random.shuffle(self.data)
 
     def sample(
         self,
@@ -1175,6 +1179,11 @@ def add_dataset_parser(parser: FlexibleArgumentParser):
         action="store_true",
         help="Skip applying chat template to prompt for datasets that support it.",
     )
+    parser.add_argument(
+        "--disable-shuffle",
+        action="store_true",
+        help="Disable shuffling of dataset samples for deterministic ordering.",
+    )
 
     # group for dataset specific arguments
     custom_group = parser.add_argument_group("custom dataset options")
@@ -1441,7 +1450,9 @@ def get_samples(args, tokenizer) -> list[SampleRequest]:
         args.request_id_prefix = ""
 
     if args.dataset_name == "custom":
-        dataset = CustomDataset(dataset_path=args.dataset_path)
+        dataset = CustomDataset(
+            dataset_path=args.dataset_path, disable_shuffle=args.disable_shuffle
+        )
         input_requests = dataset.sample(
             num_requests=args.num_prompts,
             tokenizer=tokenizer,
@@ -1452,7 +1463,9 @@ def get_samples(args, tokenizer) -> list[SampleRequest]:
         )
 
     elif args.dataset_name == "sonnet":
-        dataset = SonnetDataset(dataset_path=args.dataset_path)
+        dataset = SonnetDataset(
+            dataset_path=args.dataset_path, disable_shuffle=args.disable_shuffle
+        )
         # For the "sonnet" dataset, formatting depends on the backend.
         if args.backend == "openai-chat":
             input_requests = dataset.sample(
@@ -1586,6 +1599,7 @@ def get_samples(args, tokenizer) -> list[SampleRequest]:
             random_seed=args.seed,
             no_stream=args.no_stream,
             hf_name=args.hf_name,
+            disable_shuffle=args.disable_shuffle,
         ).sample(
             num_requests=args.num_prompts,
             tokenizer=tokenizer,
@@ -1600,7 +1614,9 @@ def get_samples(args, tokenizer) -> list[SampleRequest]:
         # For datasets that follow a similar structure, use a mapping.
         dataset_mapping = {
             "spec_bench": lambda: SpecBench(
-                dataset_path=args.dataset_path, category=args.spec_bench_category
+                dataset_path=args.dataset_path,
+                category=args.spec_bench_category,
+                disable_shuffle=args.disable_shuffle,
             ).sample(
                 num_requests=args.num_prompts,
                 tokenizer=tokenizer,
@@ -1609,7 +1625,9 @@ def get_samples(args, tokenizer) -> list[SampleRequest]:
                 no_oversample=args.no_oversample,
             ),
             "sharegpt": lambda: ShareGPTDataset(
-                random_seed=args.seed, dataset_path=args.dataset_path
+                random_seed=args.seed,
+                dataset_path=args.dataset_path,
+                disable_shuffle=args.disable_shuffle,
             ).sample(
                 tokenizer=tokenizer,
                 num_requests=args.num_prompts,
@@ -1618,7 +1636,9 @@ def get_samples(args, tokenizer) -> list[SampleRequest]:
                 no_oversample=args.no_oversample,
             ),
             "burstgpt": lambda: BurstGPTDataset(
-                random_seed=args.seed, dataset_path=args.dataset_path
+                random_seed=args.seed,
+                dataset_path=args.dataset_path,
+                disable_shuffle=args.disable_shuffle,
             ).sample(
                 tokenizer=tokenizer,
                 num_requests=args.num_prompts,
@@ -1626,7 +1646,9 @@ def get_samples(args, tokenizer) -> list[SampleRequest]:
                 no_oversample=args.no_oversample,
             ),
             "random": lambda: RandomDataset(
-                random_seed=args.seed, dataset_path=args.dataset_path
+                random_seed=args.seed,
+                dataset_path=args.dataset_path,
+                disable_shuffle=args.disable_shuffle,
             ).sample(
                 tokenizer=tokenizer,
                 num_requests=args.num_prompts,
@@ -1639,7 +1661,9 @@ def get_samples(args, tokenizer) -> list[SampleRequest]:
                 no_oversample=args.no_oversample,
             ),
             "random-mm": lambda: RandomMultiModalDataset(
-                random_seed=args.seed, dataset_path=args.dataset_path
+                random_seed=args.seed,
+                dataset_path=args.dataset_path,
+                disable_shuffle=args.disable_shuffle,
             ).sample(
                 tokenizer=tokenizer,
                 num_requests=args.num_prompts,
@@ -1655,7 +1679,9 @@ def get_samples(args, tokenizer) -> list[SampleRequest]:
                 no_oversample=args.no_oversample,
             ),
             "prefix_repetition": lambda: PrefixRepetitionRandomDataset(
-                random_seed=args.seed, dataset_path=args.dataset_path
+                random_seed=args.seed,
+                dataset_path=args.dataset_path,
+                disable_shuffle=args.disable_shuffle,
             ).sample(
                 tokenizer=tokenizer,
                 num_requests=args.num_prompts,
@@ -1733,7 +1759,8 @@ class CustomDataset(BenchmarkDataset):
             )
 
         random.seed(self.random_seed)
-        random.shuffle(self.data)
+        if not getattr(self, "disable_shuffle", False):
+            random.shuffle(self.data)
 
     def sample(
         self,
@@ -1825,7 +1852,8 @@ class SpecBench(CustomDataset):
                 self.data.append({"prompt": prompt})
 
         random.seed(self.random_seed)
-        random.shuffle(self.data)
+        if not getattr(self, "disable_shuffle", False):
+            random.shuffle(self.data)
 
     def sample(self, **kwargs) -> list:
         # leverage CustomDataset sample
@@ -2033,7 +2061,8 @@ class HuggingFaceDataset(BenchmarkDataset):
             split=self.dataset_split,
             streaming=self.load_stream,
         )
-        self.data = self.data.shuffle(seed=self.random_seed)
+        if not getattr(self, "disable_shuffle", False):
+            self.data = self.data.shuffle(seed=self.random_seed)
 
 
 # -----------------------------------------------------------------------------
@@ -2849,7 +2878,8 @@ class PrefixRepetitionRandomDataset(BenchmarkDataset):
                 abs(token_mismatch_total),
                 sign,
             )
-        random.shuffle(requests)
+        if not getattr(self, "disable_shuffle", False):
+            random.shuffle(requests)
         return requests