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 13, 17:00 UTC
Make the cv2 dependency optional (#27780)
Signed-off-by: Jacob <cmpute@qq.com>
Jacob Zhong committed
Nov 6, 2025 at 13:08 UTC
d72299d47ba64e38f6876f3d5fc69ea70d13d718
1 file changed
+2
-1
vllm/benchmarks/datasets.py
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-1
@@ -30,7 +30,6 @@ from io import BytesIO
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from tempfile import NamedTemporaryFile
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from typing import Any, cast
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-import cv2
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import numpy as np
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from PIL import Image
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from transformers import PreTrainedTokenizerBase
@@ -850,6 +849,8 @@ class RandomMultiModalDataset(RandomDataset):
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Creates a video with random pixel values, encodes it to MP4 format,
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and returns the content as bytes.
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"""
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+ import cv2
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+
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random_pixels = self._rng.integers(
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0,
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256,