[Misc] use AutoTokenizer for benchmark serving when vLLM not installed (

vllm-project#5588)

benchmarks/backend_request_func.py

@@ -4,10 +4,13 @@
 import time
 import traceback
 from dataclasses import dataclass, field
-from typing import List, Optional
+from typing import List, Optional, Union
 
 import aiohttp
+import huggingface_hub.constants
 from tqdm.asyncio import tqdm
+from transformers import (AutoTokenizer, PreTrainedTokenizer,
+                          PreTrainedTokenizerFast)
 
 AIOHTTP_TIMEOUT = aiohttp.ClientTimeout(total=6 * 60 * 60)
 
@@ -388,6 +391,30 @@ def remove_prefix(text: str, prefix: str) -> str:
     return text
 
 
+def get_model(pretrained_model_name_or_path: str):
+    if os.getenv('VLLM_USE_MODELSCOPE', 'False').lower() == 'true':
+        from modelscope import snapshot_download
+    else:
+        from huggingface_hub import snapshot_download
+
+    model_path = snapshot_download(
+        model_id=pretrained_model_name_or_path,
+        local_files_only=huggingface_hub.constants.HF_HUB_OFFLINE,
+        ignore_file_pattern=[".*.pt", ".*.safetensors", ".*.bin"])
+    return model_path
+
+
+def get_tokenizer(
+    pretrained_model_name_or_path: str, trust_remote_code: bool
+) -> Union[PreTrainedTokenizer, PreTrainedTokenizerFast]:
+    if pretrained_model_name_or_path is not None and not os.path.exists(
+            pretrained_model_name_or_path):
+        pretrained_model_name_or_path = get_model(
+            pretrained_model_name_or_path)
+    return AutoTokenizer.from_pretrained(pretrained_model_name_or_path,
+                                         trust_remote_code=trust_remote_code)
+
+
 ASYNC_REQUEST_FUNCS = {
     "tgi": async_request_tgi,
     "vllm": async_request_openai_completions,

benchmarks/benchmark_serving.py

@@ -39,7 +39,10 @@
 from tqdm.asyncio import tqdm
 from transformers import PreTrainedTokenizerBase
 
-from vllm.transformers_utils.tokenizer import get_tokenizer
+try:
+    from vllm.transformers_utils.tokenizer import get_tokenizer
+except ImportError:
+    from backend_request_func import get_tokenizer
 
 
 @dataclass