[Frontend] Add FlexibleArgumentParser to support both underscore and dash in names (#5718)

benchmarks/benchmark_latency.py

@@ -13,6 +13,7 @@ from vllm import LLM, SamplingParams
 from vllm.engine.arg_utils import EngineArgs
 from vllm.inputs import PromptStrictInputs
 from vllm.model_executor.layers.quantization import QUANTIZATION_METHODS
+from vllm.utils import FlexibleArgumentParser
 
 
 def main(args: argparse.Namespace):
@@ -120,7 +121,7 @@ def main(args: argparse.Namespace):
 
 
 if __name__ == '__main__':
-    parser = argparse.ArgumentParser(
+    parser = FlexibleArgumentParser(
         description='Benchmark the latency of processing a single batch of '
         'requests till completion.')
     parser.add_argument('--model', type=str, default='facebook/opt-125m')

benchmarks/benchmark_prefix_caching.py

-import argparse
 import time
 
 from vllm import LLM, SamplingParams
+from vllm.utils import FlexibleArgumentParser
 
 PROMPT = "You are a helpful assistant in recognizes the content of tables in markdown format. Here is a table as fellows. You need to answer my question about the table.\n# Table\n|Opening|Opening|Sl. No.|Film|Cast|Director|Music Director|Notes|\n|----|----|----|----|----|----|----|----|\n|J A N|9|1|Agni Pushpam|Jayabharathi, Kamalahasan|Jeassy|M. K. Arjunan||\n|J A N|16|2|Priyamvada|Mohan Sharma, Lakshmi, KPAC Lalitha|K. S. Sethumadhavan|V. Dakshinamoorthy||\n|J A N|23|3|Yakshagaanam|Madhu, Sheela|Sheela|M. S. Viswanathan||\n|J A N|30|4|Paalkkadal|Sheela, Sharada|T. K. Prasad|A. T. Ummer||\n|F E B|5|5|Amma|Madhu, Srividya|M. Krishnan Nair|M. K. Arjunan||\n|F E B|13|6|Appooppan|Thikkurissi Sukumaran Nair, Kamal Haasan|P. Bhaskaran|M. S. Baburaj||\n|F E B|20|7|Srishti|Chowalloor Krishnankutty, Ravi Alummoodu|K. T. Muhammad|M. S. Baburaj||\n|F E B|20|8|Vanadevatha|Prem Nazir, Madhubala|Yusufali Kechery|G. Devarajan||\n|F E B|27|9|Samasya|Madhu, Kamalahaasan|K. Thankappan|Shyam||\n|F E B|27|10|Yudhabhoomi|K. P. Ummer, Vidhubala|Crossbelt Mani|R. K. Shekhar||\n|M A R|5|11|Seemantha Puthran|Prem Nazir, Jayabharathi|A. B. Raj|M. K. Arjunan||\n|M A R|12|12|Swapnadanam|Rani Chandra, Dr. Mohandas|K. G. George|Bhaskar Chandavarkar||\n|M A R|19|13|Thulavarsham|Prem Nazir, sreedevi, Sudheer|N. Sankaran Nair|V. Dakshinamoorthy||\n|M A R|20|14|Aruthu|Kaviyoor Ponnamma, Kamalahasan|Ravi|G. Devarajan||\n|M A R|26|15|Swimming Pool|Kamal Haasan, M. G. Soman|J. Sasikumar|M. K. Arjunan||\n\n# Question\nWhat' s the content in the (1,1) cells\n"  # noqa: E501
 
@@ -44,7 +44,7 @@ def main(args):
 
 
 if __name__ == "__main__":
-    parser = argparse.ArgumentParser(
+    parser = FlexibleArgumentParser(
         description='Benchmark the performance with or without automatic '
         'prefix caching.')
     parser.add_argument('--model',

benchmarks/benchmark_serving.py

@@ -44,6 +44,11 @@ try:
 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:
@@ -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",

benchmarks/benchmark_throughput.py

@@ -12,6 +12,7 @@ from transformers import (AutoModelForCausalLM, AutoTokenizer,
 
 from vllm.engine.arg_utils import EngineArgs
 from vllm.model_executor.layers.quantization import QUANTIZATION_METHODS
+from vllm.utils import FlexibleArgumentParser
 
 
 def sample_requests(
@@ -261,7 +262,7 @@ def main(args: argparse.Namespace):
 
 
 if __name__ == "__main__":
-    parser = argparse.ArgumentParser(description="Benchmark the throughput.")
+    parser = FlexibleArgumentParser(description="Benchmark the throughput.")
     parser.add_argument("--backend",
                         type=str,
                         choices=["vllm", "hf", "mii"],

benchmarks/cutlass_benchmarks/w8a8_benchmarks.py

@@ -11,6 +11,7 @@ from torch.utils.benchmark import Measurement as TMeasurement
 from weight_shapes import WEIGHT_SHAPES
 
 from vllm import _custom_ops as ops
+from vllm.utils import FlexibleArgumentParser
 
 DEFAULT_MODELS = list(WEIGHT_SHAPES.keys())[1:]
 DEFAULT_BATCH_SIZES = [1, 16, 32, 64, 128, 256, 512]
@@ -293,7 +294,7 @@ if __name__ == '__main__':
             return torch.float8_e4m3fn
         raise ValueError("unsupported dtype")
 
-    parser = argparse.ArgumentParser(
+    parser = FlexibleArgumentParser(
         description="""
 Benchmark Cutlass GEMM.
 

benchmarks/kernels/benchmark_aqlm.py

-import argparse
 import os
 import sys
 from typing import Optional
@@ -10,6 +9,7 @@ from vllm import _custom_ops as ops
 from vllm.model_executor.layers.quantization.aqlm import (
     dequantize_weight, generic_dequantize_gemm, get_int_dtype,
     optimized_dequantize_gemm)
+from vllm.utils import FlexibleArgumentParser
 
 os.environ['CUDA_VISIBLE_DEVICES'] = '0'
 
@@ -137,7 +137,7 @@ def dequant_test(k: int, parts: torch.Tensor, nbooks: int, bits: int) -> None:
 
 def main():
 
-    parser = argparse.ArgumentParser(description="Benchmark aqlm performance.")
+    parser = FlexibleArgumentParser(description="Benchmark aqlm performance.")
 
     # Add arguments
     parser.add_argument("--nbooks",

benchmarks/kernels/benchmark_marlin.py

-import argparse
 from typing import List
 
 import torch
@@ -16,6 +15,7 @@ from vllm.model_executor.layers.quantization.utils.marlin_utils import (
     MarlinWorkspace, marlin_24_quantize, marlin_quantize)
 from vllm.model_executor.layers.quantization.utils.quant_utils import (
     gptq_pack, quantize_weights, sort_weights)
+from vllm.utils import FlexibleArgumentParser
 
 DEFAULT_MODELS = ["meta-llama/Llama-2-7b-hf/TP1"]
 DEFAULT_BATCH_SIZES = [1, 16, 32, 64, 128, 256, 512]
@@ -211,7 +211,7 @@ def main(args):
 #   python benchmark_marlin.py --batch-sizes 1 16 32 --limit-k 4096 --limit-n 4096 --limit-group-size 128 --limit-num-bits 4 --limit-act-order 0 --limit-k-full 1 # noqa E501
 #
 if __name__ == "__main__":
-    parser = argparse.ArgumentParser(
+    parser = FlexibleArgumentParser(
         description="Benchmark Marlin across specified models/shapes/batches")
     parser.add_argument(
         "--models",

benchmarks/kernels/benchmark_moe.py

@@ -10,6 +10,7 @@ from ray.experimental.tqdm_ray import tqdm
 from transformers import AutoConfig
 
 from vllm.model_executor.layers.fused_moe.fused_moe import *
+from vllm.utils import FlexibleArgumentParser
 
 
 class BenchmarkConfig(TypedDict):
@@ -315,7 +316,7 @@ def main(args: argparse.Namespace):
 
 
 if __name__ == "__main__":
-    parser = argparse.ArgumentParser()
+    parser = FlexibleArgumentParser()
     parser.add_argument("--model",
                         type=str,
                         default="mistralai/Mixtral-8x7B-Instruct-v0.1")

benchmarks/kernels/benchmark_paged_attention.py

-import argparse
 import random
 import time
 from typing import List, Optional
@@ -6,7 +5,8 @@ from typing import List, Optional
 import torch
 
 from vllm import _custom_ops as ops
-from vllm.utils import STR_DTYPE_TO_TORCH_DTYPE, create_kv_caches_with_random
+from vllm.utils import (STR_DTYPE_TO_TORCH_DTYPE, FlexibleArgumentParser,
+                        create_kv_caches_with_random)
 
 NUM_BLOCKS = 1024
 PARTITION_SIZE = 512
@@ -161,7 +161,7 @@ def main(
 
 
 if __name__ == '__main__':
-    parser = argparse.ArgumentParser(
+    parser = FlexibleArgumentParser(
         description="Benchmark the paged attention kernel.")
     parser.add_argument("--version",
                         type=str,

benchmarks/kernels/benchmark_rope.py

-import argparse
 from itertools import accumulate
 from typing import List, Optional
 
@@ -7,6 +6,7 @@ import torch
 
 from vllm.model_executor.layers.rotary_embedding import (RotaryEmbedding,
                                                          get_rope)
+from vllm.utils import FlexibleArgumentParser
 
 
 def benchmark_rope_kernels_multi_lora(
@@ -86,7 +86,7 @@ def benchmark_rope_kernels_multi_lora(
 
 
 if __name__ == '__main__':
-    parser = argparse.ArgumentParser(
+    parser = FlexibleArgumentParser(
         description="Benchmark the rotary embedding kernels.")
     parser.add_argument("--is-neox-style", type=bool, default=True)
     parser.add_argument("--batch-size", type=int, default=16)

benchmarks/overheads/benchmark_hashing.py

-import argparse
 import cProfile
 import pstats
 
 from vllm import LLM, SamplingParams
+from vllm.utils import FlexibleArgumentParser
 
 # A very long prompt, total number of tokens is about 15k.
 LONG_PROMPT = ["You are an expert in large language models, aren't you?"
@@ -47,7 +47,7 @@ def main(args):
 
 
 if __name__ == "__main__":
-    parser = argparse.ArgumentParser(
+    parser = FlexibleArgumentParser(
         description='Benchmark the performance of hashing function in'
         'automatic prefix caching.')
     parser.add_argument('--model', type=str, default='lmsys/longchat-7b-16k')

examples/aqlm_example.py

-import argparse
-
 from vllm import LLM, SamplingParams
+from vllm.utils import FlexibleArgumentParser
 
 
 def main():
 
-    parser = argparse.ArgumentParser(description='AQLM examples')
+    parser = FlexibleArgumentParser(description='AQLM examples')
 
     parser.add_argument('--model',
                         '-m',

examples/llm_engine_example.py

@@ -2,6 +2,7 @@ import argparse
 from typing import List, Tuple
 
 from vllm import EngineArgs, LLMEngine, RequestOutput, SamplingParams
+from vllm.utils import FlexibleArgumentParser
 
 
 def create_test_prompts() -> List[Tuple[str, SamplingParams]]:
@@ -55,7 +56,7 @@ def main(args: argparse.Namespace):
 
 
 if __name__ == '__main__':
-    parser = argparse.ArgumentParser(
+    parser = FlexibleArgumentParser(
         description='Demo on using the LLMEngine class directly')
     parser = EngineArgs.add_cli_args(parser)
     args = parser.parse_args()

examples/save_sharded_state.py

@@ -20,15 +20,15 @@ llm = LLM(
     tensor_parallel_size=8,
 )
 """
-import argparse
 import dataclasses
 import os
 import shutil
 from pathlib import Path
 
 from vllm import LLM, EngineArgs
+from vllm.utils import FlexibleArgumentParser
 
-parser = argparse.ArgumentParser()
+parser = FlexibleArgumentParser()
 EngineArgs.add_cli_args(parser)
 parser.add_argument("--output",
                     "-o",

examples/tensorize_vllm_model.py

@@ -9,6 +9,7 @@ from vllm.engine.arg_utils import EngineArgs
 from vllm.model_executor.model_loader.tensorizer import (TensorizerArgs,
                                                          TensorizerConfig,
                                                          tensorize_vllm_model)
+from vllm.utils import FlexibleArgumentParser
 
 # yapf conflicts with isort for this docstring
 # yapf: disable
@@ -96,7 +97,7 @@ deserialization in this example script, although `--tensorizer-uri` and
 
 
 def parse_args():
-    parser = argparse.ArgumentParser(
+    parser = FlexibleArgumentParser(
         description="An example script that can be used to serialize and "
         "deserialize vLLM models. These models "
         "can be loaded using tensorizer directly to the GPU "

tests/async_engine/api_server_async_engine.py

 """vllm.entrypoints.api_server with some extra logging for testing."""
-import argparse
 from typing import Any, Dict
 
 import uvicorn
@@ -8,6 +7,7 @@ from fastapi.responses import JSONResponse, Response
 import vllm.entrypoints.api_server
 from vllm.engine.arg_utils import AsyncEngineArgs
 from vllm.engine.async_llm_engine import AsyncLLMEngine
+from vllm.utils import FlexibleArgumentParser
 
 app = vllm.entrypoints.api_server.app
 
@@ -33,7 +33,7 @@ def stats() -> Response:
 
 
 if __name__ == "__main__":
-    parser = argparse.ArgumentParser()
+    parser = FlexibleArgumentParser()
     parser.add_argument("--host", type=str, default="localhost")
     parser.add_argument("--port", type=int, default=8000)
     parser = AsyncEngineArgs.add_cli_args(parser)

vllm/engine/arg_utils.py

@@ -11,7 +11,7 @@ from vllm.config import (CacheConfig, DecodingConfig, DeviceConfig,
                          SpeculativeConfig, TokenizerPoolConfig,
                          VisionLanguageConfig)
 from vllm.model_executor.layers.quantization import QUANTIZATION_METHODS
-from vllm.utils import str_to_int_tuple
+from vllm.utils import FlexibleArgumentParser, str_to_int_tuple
 
 
 def nullable_str(val: str):
@@ -110,7 +110,7 @@ class EngineArgs:
 
     @staticmethod
     def add_cli_args_for_vlm(
-            parser: argparse.ArgumentParser) -> argparse.ArgumentParser:
+            parser: FlexibleArgumentParser) -> FlexibleArgumentParser:
         parser.add_argument('--image-input-type',
                             type=nullable_str,
                             default=None,
@@ -156,8 +156,7 @@ class EngineArgs:
         return parser
 
     @staticmethod
-    def add_cli_args(
-            parser: argparse.ArgumentParser) -> argparse.ArgumentParser:
+    def add_cli_args(parser: FlexibleArgumentParser) -> FlexibleArgumentParser:
         """Shared CLI arguments for vLLM engine."""
 
         # Model arguments
@@ -800,8 +799,8 @@ class AsyncEngineArgs(EngineArgs):
     max_log_len: Optional[int] = None
 
     @staticmethod
-    def add_cli_args(parser: argparse.ArgumentParser,
-                     async_args_only: bool = False) -> argparse.ArgumentParser:
+    def add_cli_args(parser: FlexibleArgumentParser,
+                     async_args_only: bool = False) -> FlexibleArgumentParser:
         if not async_args_only:
             parser = EngineArgs.add_cli_args(parser)
         parser.add_argument('--engine-use-ray',
@@ -822,13 +821,13 @@ class AsyncEngineArgs(EngineArgs):
 
 # These functions are used by sphinx to build the documentation
 def _engine_args_parser():
-    return EngineArgs.add_cli_args(argparse.ArgumentParser())
+    return EngineArgs.add_cli_args(FlexibleArgumentParser())
 
 
 def _async_engine_args_parser():
-    return AsyncEngineArgs.add_cli_args(argparse.ArgumentParser(),
+    return AsyncEngineArgs.add_cli_args(FlexibleArgumentParser(),
                                         async_args_only=True)
 
 
 def _vlm_engine_args_parser():
-    return EngineArgs.add_cli_args_for_vlm(argparse.ArgumentParser())
+    return EngineArgs.add_cli_args_for_vlm(FlexibleArgumentParser())

vllm/entrypoints/api_server.py

@@ -6,7 +6,6 @@ We are also not going to accept PRs modifying this file, please
 change `vllm/entrypoints/openai/api_server.py` instead.
 """
 
-import argparse
 import json
 import ssl
 from typing import AsyncGenerator
@@ -19,7 +18,7 @@ from vllm.engine.arg_utils import AsyncEngineArgs
 from vllm.engine.async_llm_engine import AsyncLLMEngine
 from vllm.sampling_params import SamplingParams
 from vllm.usage.usage_lib import UsageContext
-from vllm.utils import random_uuid
+from vllm.utils import FlexibleArgumentParser, random_uuid
 
 TIMEOUT_KEEP_ALIVE = 5  # seconds.
 app = FastAPI()
@@ -80,7 +79,7 @@ async def generate(request: Request) -> Response:
 
 
 if __name__ == "__main__":
-    parser = argparse.ArgumentParser()
+    parser = FlexibleArgumentParser()
     parser.add_argument("--host", type=str, default=None)
     parser.add_argument("--port", type=int, default=8000)
     parser.add_argument("--ssl-keyfile", type=str, default=None)

vllm/entrypoints/openai/cli_args.py

@@ -10,6 +10,7 @@ import ssl
 
 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):
@@ -23,7 +24,7 @@ class LoRAParserAction(argparse.Action):
 
 
 def make_arg_parser():
-    parser = argparse.ArgumentParser(
+    parser = FlexibleArgumentParser(
         description="vLLM OpenAI-Compatible RESTful API server.")
     parser.add_argument("--host",
                         type=nullable_str,

vllm/entrypoints/openai/run_batch.py

-import argparse
 import asyncio
 import sys
 from io import StringIO
@@ -16,14 +15,14 @@ from vllm.entrypoints.openai.protocol import (BatchRequestInput,
 from vllm.entrypoints.openai.serving_chat import OpenAIServingChat
 from vllm.logger import init_logger
 from vllm.usage.usage_lib import UsageContext
-from vllm.utils import random_uuid
+from vllm.utils import FlexibleArgumentParser, random_uuid
 from vllm.version import __version__ as VLLM_VERSION
 
 logger = init_logger(__name__)
 
 
 def parse_args():
-    parser = argparse.ArgumentParser(
+    parser = FlexibleArgumentParser(
         description="vLLM OpenAI-Compatible batch runner.")
     parser.add_argument(
         "-i",