[Bugfix] Support testing prefill throughput with benchmark_serving.py…

… --hf-output-len 1 (vllm-project#8891)

benchmarks/benchmark_serving.py

@@ -89,8 +89,6 @@ def sample_sharegpt_requests(
     tokenizer: PreTrainedTokenizerBase,
     fixed_output_len: Optional[int] = None,
 ) -> List[Tuple[str, int, int, None]]:
-    if fixed_output_len is not None and fixed_output_len < 4:
-        raise ValueError("output_len too small")
     # Load the dataset.
     with open(dataset_path) as f:
         dataset = json.load(f)
@@ -117,7 +115,7 @@ def sample_sharegpt_requests(
         prompt_len = len(prompt_token_ids)
         output_len = len(completion_token_ids
                          ) if fixed_output_len is None else fixed_output_len
-        if prompt_len < 4 or output_len < 4:
+        if prompt_len < 4 or (fixed_output_len is None and output_len < 4):
             # Prune too short sequences.
             continue
         if prompt_len > 1024 or prompt_len + output_len > 2048:
@@ -228,10 +226,11 @@ def sample_hf_requests(
         prompt_len = len(prompt_token_ids)
         output_len = len(completion_token_ids
                          ) if fixed_output_len is None else fixed_output_len
-        if prompt_len < 4 or output_len < 4:
+        if fixed_output_len is None and (prompt_len < 4 or output_len < 4):
             # Prune too short sequences.
             continue
-        if prompt_len > 1024 or prompt_len + output_len > 2048:
+        if fixed_output_len is None and \
+            (prompt_len > 1024 or prompt_len + output_len > 2048):
             # Prune too long sequences.
             continue