Brings in flexargparse and rebases

Signed-off-by: Rafael Vasquez <[email protected]>

benchmarks/benchmark_serving.py

@@ -2,7 +2,7 @@
 
 On the server side, run one of the following commands:
     vLLM OpenAI API server
-    vllm serve <your_model>
+    vllm serve <your_model> \
         --swap-space 16 \
         --disable-log-requests
 
@@ -17,7 +17,7 @@
         --dataset-path <path to dataset> \
         --request-rate <request_rate> \ # By default <request_rate> is inf
         --num-prompts <num_prompts> # By default <num_prompts> is 1000
-        
+
     when using tgi backend, add
         --endpoint /generate_stream
     to the end of the command above.
@@ -44,6 +44,11 @@
 except ImportError:
     from backend_request_func import get_tokenizer
 
+try:
+    from vllm.utils import FlexibleArgumentParser
+except ImportError:
+    from argparse import ArgumentParser as FlexibleArgumentParser
+
 
 @dataclass
 class BenchmarkMetrics:
@@ -72,7 +77,6 @@ def sample_sharegpt_requests(
 ) -> List[Tuple[str, int, int]]:
     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)
@@ -191,6 +195,7 @@ async def get_request(
         if request_rate == float("inf"):
             # If the request rate is infinity, then we don't need to wait.
             continue
+
         # Sample the request interval from the exponential distribution.
         interval = np.random.exponential(1.0 / request_rate)
         # The next request will be sent after the interval.
@@ -214,7 +219,7 @@ def calculate_metrics(
             # We use the tokenizer to count the number of output tokens for all
             # serving backends instead of looking at len(outputs[i].itl) since
             # multiple output tokens may be bundled together
-            # Note: this may inflate the output token count slightly
+            # Note : this may inflate the output token count slightly
             output_len = len(
                 tokenizer(outputs[i].generated_text,
                           add_special_tokens=False).input_ids)
@@ -511,7 +516,7 @@ def main(args: argparse.Namespace):
 
 
 if __name__ == "__main__":
-    parser = argparse.ArgumentParser(
+    parser = FlexibleArgumentParser(
         description="Benchmark the online serving throughput.")
     parser.add_argument(
         "--backend",

tests/utils.py

@@ -3,7 +3,6 @@
 import sys
 import time
 import warnings
-from argparse import ArgumentParser
 from contextlib import contextmanager
 from typing import List
 
@@ -14,7 +13,7 @@
 from vllm.distributed import (ensure_model_parallel_initialized,
                               init_distributed_environment)
 from vllm.entrypoints.openai.cli_args import make_arg_parser
-from vllm.utils import get_open_port
+from vllm.utils import FlexibleArgumentParser, get_open_port
 
 # Path to root of repository so that utilities can be imported by ray workers
 VLLM_PATH = os.path.abspath(os.path.join(__file__, os.pardir, os.pardir))
@@ -32,7 +31,10 @@ def __init__(self, cli_args: List[str], *, wait_url: str,
             env = os.environ.copy()
             env["PYTHONUNBUFFERED"] = "1"
             self.proc = subprocess.Popen(
-                ["vllm", "serve", *cli_args],
+                [
+                    sys.executable, "-m", "vllm.entrypoints.openai.api_server",
+                    *cli_args
+                ],
                 env=env,
                 stdout=sys.stdout,
                 stderr=sys.stderr,
@@ -72,7 +74,8 @@ def __init__(self, cli_args: List[str], *, auto_port: bool = True) -> None:
 
             cli_args = cli_args + ["--port", str(get_open_port())]
 
-        parser = ArgumentParser(description="vLLM's remote OpenAI server.")
+        parser = FlexibleArgumentParser(
+            description="vLLM's remote OpenAI server.")
         parser = make_arg_parser(parser)
         args = parser.parse_args(cli_args)
         self.host = str(args.host or 'localhost')

vllm/entrypoints/openai/api_server.py

@@ -1,4 +1,3 @@
-import argparse
 import asyncio
 import importlib
 import inspect
@@ -31,6 +30,7 @@
 from vllm.logger import init_logger
 from vllm.tgis_utils.args import add_tgis_args, postprocess_tgis_args
 from vllm.usage.usage_lib import UsageContext
+from vllm.utils import FlexibleArgumentParser
 from vllm.version import __version__ as VLLM_VERSION
 
 TIMEOUT_KEEP_ALIVE = 5  # seconds
@@ -89,7 +89,7 @@ async def health() -> Response:
 
 @router.get("/v1/models")
 async def show_available_models():
-    models = await openai_serving_chat.show_available_models()
+    models = await openai_serving_completion.show_available_models()
     return JSONResponse(content=models.model_dump())
 
 
@@ -263,8 +263,7 @@ def run_server(args, llm_engine=None):
 if __name__ == "__main__":
     # NOTE(simon):
     # This section should be in sync with vllm/scripts.py for CLI entrypoints.
-
-    parser = argparse.ArgumentParser(
+    parser = FlexibleArgumentParser(
         description="vLLM OpenAI-Compatible RESTful API server.")
     parser = make_arg_parser(parser)
     parser = add_tgis_args(parser)

vllm/entrypoints/openai/cli_args.py

@@ -10,6 +10,7 @@
 
 from vllm.engine.arg_utils import AsyncEngineArgs, nullable_str
 from vllm.entrypoints.openai.serving_engine import LoRAModulePath
+from vllm.utils import FlexibleArgumentParser
 
 
 class LoRAParserAction(argparse.Action):
@@ -22,8 +23,7 @@ def __call__(self, parser, namespace, values, option_string=None):
         setattr(namespace, self.dest, lora_list)
 
 
-def make_arg_parser(
-        parser: argparse.ArgumentParser) -> argparse.ArgumentParser:
+def make_arg_parser(parser: FlexibleArgumentParser) -> FlexibleArgumentParser:
     parser.add_argument("--host",
                         type=nullable_str,
                         default=None,
@@ -114,7 +114,7 @@ def make_arg_parser(
     return parser
 
 
-def create_parser_for_docs() -> argparse.ArgumentParser:
-    parser_for_docs = argparse.ArgumentParser(
+def create_parser_for_docs() -> FlexibleArgumentParser:
+    parser_for_docs = FlexibleArgumentParser(
         prog="-m vllm.entrypoints.openai.api_server")
     return make_arg_parser(parser_for_docs)

vllm/scripts.py

@@ -10,6 +10,7 @@
 
 from vllm.entrypoints.openai.api_server import run_server
 from vllm.entrypoints.openai.cli_args import make_arg_parser
+from vllm.utils import FlexibleArgumentParser
 
 
 def registrer_signal_handlers():
@@ -23,10 +24,6 @@ def signal_handler(sig, frame):
 
 def serve(args: argparse.Namespace) -> None:
     # EngineArgs expects the model name to be passed as --model.
-    if args.model is not None and args.model == args.model_tag:
-        raise ValueError(
-            "The --model argument is not supported for the serve command. "
-            "Use positional argument [model_tag] instead.")
     args.model = args.model_tag
 
     run_server(args)
@@ -245,7 +242,7 @@ def convert_to_fast_tokenizer(
 
 
 def _add_query_options(
-        parser: argparse.ArgumentParser) -> argparse.ArgumentParser:
+        parser: FlexibleArgumentParser) -> FlexibleArgumentParser:
     parser.add_argument(
         "--url",
         type=str,
@@ -269,7 +266,7 @@ def _add_query_options(
 
 
 def main():
-    parser = argparse.ArgumentParser(description="vLLM CLI")
+    parser = FlexibleArgumentParser(description="vLLM CLI")
     subparsers = parser.add_subparsers(required=True)
 
     serve_parser = subparsers.add_parser(

vllm/utils.py

@@ -1,3 +1,4 @@
+import argparse
 import asyncio
 import datetime
 import enum
@@ -775,3 +776,27 @@ def wrapper(*args, **kwargs) -> Any:
 
     wrapper.has_run = False  # type: ignore[attr-defined]
     return wrapper
+
+
+class FlexibleArgumentParser(argparse.ArgumentParser):
+    """ArgumentParser that allows both underscore and dash in names."""
+
+    def parse_args(self, args=None, namespace=None):
+        if args is None:
+            args = sys.argv[1:]
+
+        # Convert underscores to dashes and vice versa in argument names
+        processed_args = []
+        for arg in args:
+            if arg.startswith('--'):
+                if '=' in arg:
+                    key, value = arg.split('=', 1)
+                    key = '--' + key[len('--'):].replace('_', '-')
+                    processed_args.append(f'{key}={value}')
+                else:
+                    processed_args.append('--' +
+                                          arg[len('--'):].replace('_', '-'))
+            else:
+                processed_args.append(arg)
+
+        return super().parse_args(processed_args, namespace)