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[Misc] refactor argument parsing in examples (#16635)

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Signed-off-by: reidliu41 <reid201711@gmail.com>
Co-authored-by: reidliu41 <reid201711@gmail.com>
This commit is contained in:
Reid
2025-04-15 16:05:30 +08:00
committed by GitHub
parent b590adfdc1
commit 6ae996a873
25 changed files with 595 additions and 411 deletions
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105
examples/offline_inference/vision_language.py
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@@ -1097,6 +1097,59 @@ def time_counter(enable: bool):
yield
def parse_args():
parser = FlexibleArgumentParser(
description='Demo on using vLLM for offline inference with '
'vision language models for text generation')
parser.add_argument('--model-type',
'-m',
type=str,
default="llava",
choices=model_example_map.keys(),
help='Huggingface "model_type".')
parser.add_argument('--num-prompts',
type=int,
default=4,
help='Number of prompts to run.')
parser.add_argument('--modality',
type=str,
default="image",
choices=['image', 'video'],
help='Modality of the input.')
parser.add_argument('--num-frames',
type=int,
default=16,
help='Number of frames to extract from the video.')
parser.add_argument("--seed",
type=int,
default=None,
help="Set the seed when initializing `vllm.LLM`.")
parser.add_argument(
'--image-repeat-prob',
type=float,
default=None,
help='Simulates the hit-ratio for multi-modal preprocessor cache'
' (if enabled)')
parser.add_argument(
'--disable-mm-preprocessor-cache',
action='store_true',
help='If True, disables caching of multi-modal preprocessor/mapper.')
parser.add_argument(
'--time-generate',
action='store_true',
help='If True, then print the total generate() call time')
parser.add_argument(
'--use-different-prompt-per-request',
action='store_true',
help='If True, then use different prompt (with the same multi-modal '
'data) for each request.')
return parser.parse_args()
def main(args):
model = args.model_type
if model not in model_example_map:
@@ -1175,55 +1228,5 @@ def main(args):
if __name__ == "__main__":
parser = FlexibleArgumentParser(
description='Demo on using vLLM for offline inference with '
'vision language models for text generation')
parser.add_argument('--model-type',
'-m',
type=str,
default="llava",
choices=model_example_map.keys(),
help='Huggingface "model_type".')
parser.add_argument('--num-prompts',
type=int,
default=4,
help='Number of prompts to run.')
parser.add_argument('--modality',
type=str,
default="image",
choices=['image', 'video'],
help='Modality of the input.')
parser.add_argument('--num-frames',
type=int,
default=16,
help='Number of frames to extract from the video.')
parser.add_argument("--seed",
type=int,
default=None,
help="Set the seed when initializing `vllm.LLM`.")
parser.add_argument(
'--image-repeat-prob',
type=float,
default=None,
help='Simulates the hit-ratio for multi-modal preprocessor cache'
' (if enabled)')
parser.add_argument(
'--disable-mm-preprocessor-cache',
action='store_true',
help='If True, disables caching of multi-modal preprocessor/mapper.')
parser.add_argument(
'--time-generate',
action='store_true',
help='If True, then print the total generate() call time')
parser.add_argument(
'--use-different-prompt-per-request',
action='store_true',
help='If True, then use different prompt (with the same multi-modal '
'data) for each request.')
args = parser.parse_args()
args = parse_args()
main(args)