From cd086369260ccf2289b9b3d96319792705df4e5b Mon Sep 17 00:00:00 2001
From: Ekagra Ranjan <3116519+ekagra-ranjan@users.noreply.github.com>
Date: Mon, 8 Sep 2025 13:32:52 -0400
Subject: [PATCH] [Spec Decode][Benchmark] Add Blitzedit dataset (#23605)

Signed-off-by: Ekagra Ranjan <3116519+ekagra-ranjan@users.noreply.github.com>
Co-authored-by: Roger Wang <hey@rogerw.io>
---
 vllm/benchmarks/datasets.py | 113 ++++++++++++++++++++++++++++++++++++
 1 file changed, 113 insertions(+)

diff --git a/vllm/benchmarks/datasets.py b/vllm/benchmarks/datasets.py
index 2e0c02d31767d..1c358a835cac5 100644
--- a/vllm/benchmarks/datasets.py
+++ b/vllm/benchmarks/datasets.py
@@ -1101,6 +1101,22 @@ def add_dataset_parser(parser: FlexibleArgumentParser):
         "from the ShareGPT dataset.",
     )
 
+    blazedit_group = parser.add_argument_group("blazedit dataset options")
+    blazedit_group.add_argument(
+        "--blazedit-min-distance",
+        type=float,
+        default=0.0,
+        help=
+        "Minimum distance for blazedit dataset. Min: 0, Max: 1.0",
+    )
+    blazedit_group.add_argument(
+        "--blazedit-max-distance",
+        type=float,
+        default=1.0,
+        help=
+        "Maximum distance for blazedit dataset. Min: 0, Max: 1.0",
+    )
+
     random_group = parser.add_argument_group("random dataset options")
     random_group.add_argument(
         "--random-input-len",
@@ -1333,6 +1349,7 @@ def get_samples(args, tokenizer) -> list[SampleRequest]:
     elif args.dataset_name == "hf":
         # all following datasets are implemented from the
         # HuggingFaceDataset base class
+        hf_kwargs = {}
         if (
             args.dataset_path in VisionArenaDataset.SUPPORTED_DATASET_PATHS
             or args.hf_name in VisionArenaDataset.SUPPORTED_DATASET_PATHS
@@ -1376,6 +1393,13 @@ def get_samples(args, tokenizer) -> list[SampleRequest]:
         ):
             dataset_class = ASRDataset
             args.hf_split = "train"
+        elif args.dataset_path in BlazeditDataset.SUPPORTED_DATASET_PATHS:
+            dataset_class = BlazeditDataset
+            args.hf_split = "train"
+            hf_kwargs = {
+                "min_distance": args.blazedit_min_distance,
+                "max_distance": args.blazedit_max_distance,
+            }
         elif (
             args.dataset_path in MLPerfDataset.SUPPORTED_DATASET_PATHS
             or args.hf_name in MLPerfDataset.SUPPORTED_DATASET_PATHS
@@ -1415,6 +1439,7 @@ def get_samples(args, tokenizer) -> list[SampleRequest]:
             tokenizer=tokenizer,
             output_len=args.hf_output_len,
             request_id_prefix=args.request_id_prefix,
+            **hf_kwargs
         )
 
     else:
@@ -2090,6 +2115,94 @@ class MTBenchDataset(HuggingFaceDataset):
         return sampled_requests
 
 
+# -----------------------------------------------------------------------------
+# Blazedit Dataset Implementation
+# -----------------------------------------------------------------------------
+
+
+class BlazeditDataset(HuggingFaceDataset):
+    """
+    Blazedit Dataset.
+    https://github.com/ise-uiuc/blazedit
+
+    5k char version: vdaita/edit_5k_char
+    10k char version: vdaita/edit_10k_char
+    """  # noqa: E501
+
+    # 5k char version will have output as ~5k chars
+    # 10k char version will have output as ~10k chars
+    # Assuming 3 char per token, 10k chars will be 3333 tokens
+    # We set default to 4000 to be safe
+    DEFAULT_OUTPUT_LEN = 4000
+    SUPPORTED_DATASET_PATHS = {
+        "vdaita/edit_5k_char",
+        "vdaita/edit_10k_char",
+    }
+
+    def sample(
+        self,
+        tokenizer: PreTrainedTokenizerBase,
+        num_requests: int,
+        output_len: Optional[int] = None,
+        request_id_prefix: str = "",
+        min_distance: float = 0.0,
+        max_distance: float = 1.0,
+        **kwargs,
+    ) -> list:
+        output_len = (output_len
+                      if output_len is not None else self.DEFAULT_OUTPUT_LEN)
+        sampled_requests = []
+
+        for i, item in enumerate(self.data):
+            if len(sampled_requests) >= num_requests:
+                break
+            code = item["code"]
+            change_request = item["change_request"]
+            norm_distance = item["norm_distance"]
+
+            # compare the levenshtein distance normalized by code length
+            if norm_distance < min_distance or norm_distance > max_distance:
+                continue
+            
+            # template copied from 
+            # https://github.com/ise-uiuc/blazedit/blob/7765137e656fd62de877422d2e4cf8de51228054/dataset/create_refined_dataset.py#L94-L105 # noqa: E501
+            instruction = f"""Given a code file, please apply the change requests and generate the new file.
+
+Original file:
+```python
+{code}
+```
+
+Change request:
+{change_request}
+
+Please generate the new code file in the "New file" section below.""" # noqa: E501
+
+            # apply template
+            prompt = tokenizer.apply_chat_template(
+                [{
+                    "role": "user",
+                    "content": instruction
+                }],
+                add_generation_prompt=True,
+                tokenize=False,
+            )
+
+            prompt_len = len(tokenizer(prompt).input_ids)
+
+            sampled_requests.append(
+                SampleRequest(
+                    prompt=prompt,
+                    prompt_len=prompt_len,
+                    expected_output_len=output_len,
+                    request_id=request_id_prefix + str(i),
+                ))
+        self.maybe_oversample_requests(sampled_requests, num_requests, 
+                                       request_id_prefix)
+        
+        return sampled_requests
+
+
 # -----------------------------------------------------------------------------
 # AIMO Dataset Implementation
 # -----------------------------------------------------------------------------