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Convert formatting to use ruff instead of yapf + isort (#26247)

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Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>
This commit is contained in:
Harry Mellor
2025-10-05 15:06:22 +01:00
committed by GitHub
parent 17edd8a807
commit d6953beb91
1508 changed files with 115244 additions and 94146 deletions
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36
tests/models/multimodal/generation/vlm_utils/custom_inputs.py
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@@ -1,12 +1,16 @@
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
"""Custom input builders for edge-cases in different models."""
from typing import Callable
from vllm.assets.image import ImageAsset
from vllm.multimodal.image import rescale_image_size
from vllm.multimodal.video import (rescale_video_size, resize_video,
sample_frames_from_video)
from vllm.multimodal.video import (
rescale_video_size,
resize_video,
sample_frames_from_video,
)
from .....conftest import IMAGE_ASSETS, VIDEO_ASSETS
from .builders import build_multi_image_inputs, build_single_image_inputs
@@ -15,7 +19,7 @@ from .types import ImageSizeWrapper, PromptWithMultiModalInput, SizeType
def multi_image_multi_aspect_ratio_inputs(formatter: Callable[[str], str]):
"""Builds inputs for multi-image (varied sizes/aspect ratio) testing.
Args:
formatter: model-specific prompt formatter.
"""
@@ -41,7 +45,7 @@ def multi_image_multi_aspect_ratio_inputs(formatter: Callable[[str], str]):
stop_sign,
rescale_image_size(stop_sign, 0.25),
cherry_blossom.resize((183, 488)),
cherry_blossom.resize((488, 183))
cherry_blossom.resize((488, 183)),
],
cherry_blossom,
]
@@ -54,10 +58,11 @@ def multi_image_multi_aspect_ratio_inputs(formatter: Callable[[str], str]):
]
def multi_video_multi_aspect_ratio_inputs(formatter: Callable[[str], str],
num_frames: int = 16):
def multi_video_multi_aspect_ratio_inputs(
formatter: Callable[[str], str], num_frames: int = 16
):
"""Builds inputs for multi-video (varied sizes/aspect ratio) testing.
Args:
formatter: model-specific prompt formatter.
"""
@@ -81,7 +86,7 @@ def multi_video_multi_aspect_ratio_inputs(formatter: Callable[[str], str],
video,
rescale_video_size(video, 0.25),
resize_video(video, (183, 488)),
resize_video(video, (488, 183))
resize_video(video, (488, 183)),
],
video,
]
@@ -96,7 +101,9 @@ def multi_video_multi_aspect_ratio_inputs(formatter: Callable[[str], str],
def different_patch_input_cases_internvl():
images = [asset.pil_image.resize((896, 896)) for asset in IMAGE_ASSETS]
formatter = lambda img_prompt: f"<|im_start|>User\n{img_prompt}<|im_end|>\n<|im_start|>Assistant\n" # noqa: E501
formatter = (
lambda img_prompt: f"<|im_start|>User\n{img_prompt}<|im_end|>\n<|im_start|>Assistant\n"
) # noqa: E501
single_img_prompts = [
"<image>\nWhat's the content in the center of the image?",
"<image>\nWhat is the season?",
@@ -115,14 +122,14 @@ def different_patch_input_cases_internvl():
def windows_attention_image_qwen2_5_vl():
# image from regression issue: https://github.com/vllm-project/vllm/issues/15122 # noqa: E501
image = ImageAsset("hato").pil_image
question = "Describe the image."
img_prompt = "<|vision_start|><|image_pad|><|vision_end|>"
prompt = (f"<|im_start|>User\n{img_prompt}{question}<|im_end|>\n"
"<|im_start|>assistant\n")
prompt = (
f"<|im_start|>User\n{img_prompt}{question}<|im_end|>\n<|im_start|>assistant\n"
)
wrapped_sf = ImageSizeWrapper(type=SizeType.SIZE_FACTOR, data=[0.5])
return build_single_image_inputs([image], [prompt], wrapped_sf)
@@ -136,8 +143,9 @@ def video_with_metadata_glm4_1v():
formatted_prompt = f"<|user|>\n{video_prompt}{question}<|assistant|>\n"
scales = [0.1, 0.2, 0.25]
video_input = [[(rescale_video_size(video_array, scale), metadata)]
for scale in scales]
video_input = [
[(rescale_video_size(video_array, scale), metadata)] for scale in scales
]
prompts = [formatted_prompt] * len(video_input)
return [