minor: add dataset dump and questions shuffle

python/sglang/bench_serving.py

@@ -15,6 +15,7 @@
 import asyncio
 import json
 import os
+import pickle
 import random
 import resource
 import sys
@@ -682,6 +683,11 @@ def sample_generated_shared_prefix_requests(
     output_len: int,
     tokenizer: PreTrainedTokenizerBase,
 ) -> List[Tuple[str, int, int]]:
+    if args.generated_input_path and os.path.exists(args.generated_input_path):
+        print(f"\nloading generated input data from {args.generated_input_path}")
+        with open(args.generated_input_path, "rb") as f:
+            return pickle.load(f)
+
     """Generate benchmark requests with shared system prompts using random tokens."""
     # Generate system prompts for each group
     system_prompts = []
@@ -695,6 +701,9 @@ def sample_generated_shared_prefix_requests(
         question = gen_prompt(tokenizer, question_len)
         questions.append(question)
 
+    # Shuffle questions
+    random.shuffle(questions)
+
     # Combine system prompts with questions
     input_requests = []
     total_input_tokens = 0
@@ -723,6 +732,11 @@ def sample_generated_shared_prefix_requests(
     print(
         f"Average question length: {sum(len(tokenizer.encode(q)) for q in questions) / len(questions):.1f} tokens\n"
     )
+    if args.generated_input_save_path:
+        print(f"Saving generated input data to {args.generated_input_save_path}")
+        os.makedirs(os.path.dirname(args.generated_input_save_path), exist_ok=True)
+        with open(args.generated_input_save_path, "wb") as f:
+            pickle.dump(input_requests, f)
 
     return input_requests
 
@@ -1331,6 +1345,16 @@ def set_ulimit(target_soft_limit=65535):
         default=256,
         help="Target length in tokens for outputs in generated-shared-prefix dataset",
     )
+    parser.add_argument(
+        "--generated-input-save-path",
+        type=str,
+        help="Path to save generated input data",
+    )
+    parser.add_argument(
+        "--generated-input-path",
+        type=str,
+        help="Path to load previously generated input data",
+    )
 
     args = parser.parse_args()
     run_benchmark(args)