A high-throughput and memory-efficient inference and serving engine for LLMs
Mirrored from https://github.com/tduncan-lum/Nvidia-Optimization-Stack---VLLM.git
Synced Nov 8, 14:13 UTC
[Bugfix] Fix `--trust-remote-code` conflict (#34218)
Signed-off-by: DarkLight1337 <tlleungac@connect.ust.hk>
Cyrus Leung committed
Feb 10, 2026 at 16:29 UTC
2c32558a3c467253161e32203584c1ecb33bb584
2 files changed
+2
-16
examples/offline_inference/spec_decode.py
+1
-6
@@ -5,14 +5,9 @@ from transformers import AutoTokenizer
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from vllm import LLM, SamplingParams
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from vllm.benchmarks.datasets import add_dataset_parser, get_samples
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+from vllm.utils.argparse_utils import FlexibleArgumentParser
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from vllm.v1.metrics.reader import Counter, Vector
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-try:
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- from vllm.utils.argparse_utils import FlexibleArgumentParser
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-except ImportError:
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- from argparse import ArgumentParser as FlexibleArgumentParser
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-
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-
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QUESTION = "What is the content of each image?"
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IMAGE_URLS = [
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"https://vllm-public-assets.s3.us-west-2.amazonaws.com/multimodal_asset/duck.jpg",
vllm/benchmarks/datasets.py
+1
-10
@@ -39,6 +39,7 @@ from vllm.lora.utils import get_adapter_absolute_path
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from vllm.multimodal import MultiModalDataDict
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from vllm.multimodal.image import convert_image_mode
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from vllm.tokenizers import TokenizerLike
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+from vllm.utils.argparse_utils import FlexibleArgumentParser
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from vllm.utils.import_utils import PlaceholderModule
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try:
@@ -57,11 +58,6 @@ try:
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except ImportError:
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librosa = PlaceholderModule("librosa")
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-try:
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- from vllm.utils.argparse_utils import FlexibleArgumentParser
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-except ImportError:
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- from argparse import ArgumentParser as FlexibleArgumentParser
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-
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logger = logging.getLogger(__name__)
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# -----------------------------------------------------------------------------
@@ -1374,11 +1370,6 @@ def add_dataset_parser(parser: FlexibleArgumentParser):
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action="store_true",
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help="Disable shuffling of dataset samples for deterministic ordering.",
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)
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- parser.add_argument(
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- "--trust-remote-code",
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- action="store_true",
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- help="Trust remote code from HuggingFace.",
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- )
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# group for dataset specific arguments
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custom_group = parser.add_argument_group("custom dataset options")