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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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47
tests/models/multimodal/pooling/test_phi3v.py
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@@ -19,14 +19,14 @@ HF_TEXT_PROMPTS = [
"Retrieve an image of this caption: cherry blossom",
]
HF_IMAGE_PROMPTS = IMAGE_ASSETS.prompts({
# T + I -> X
"stop_sign":
"<|image_1|> Select the portion of the image that isolates the object of the given label: The label of the object is stop sign", # noqa: E501
# I -> X
"cherry_blossom":
"<|image_1|> Represent the given image for classification", # noqa: E501
})
HF_IMAGE_PROMPTS = IMAGE_ASSETS.prompts(
{
# T + I -> X
"stop_sign": "<|image_1|> Select the portion of the image that isolates the object of the given label: The label of the object is stop sign", # noqa: E501
# I -> X
"cherry_blossom": "<|image_1|> Represent the given image for classification", # noqa: E501
}
)
MODELS = ["TIGER-Lab/VLM2Vec-Full"]
@@ -44,14 +44,14 @@ def _run_test(
# vLLM needs a fresh new process without cuda initialization.
# if we run HF first, the cuda initialization will be done and it
# will hurt multiprocessing backend with fork method (the default method).
with vllm_runner(model, runner="pooling", dtype=dtype,
enforce_eager=True) as vllm_model:
with vllm_runner(
model, runner="pooling", dtype=dtype, enforce_eager=True
) as vllm_model:
vllm_outputs = vllm_model.embed(input_texts, images=input_images)
# use eager mode for hf runner, since phi3_v didn't work with flash_attn
hf_model_kwargs = {"_attn_implementation": "eager"}
with hf_runner(model, dtype=dtype,
model_kwargs=hf_model_kwargs) as hf_model:
with hf_runner(model, dtype=dtype, model_kwargs=hf_model_kwargs) as hf_model:
all_inputs = hf_model.get_inputs(input_texts, images=input_images)
all_outputs = []
@@ -114,18 +114,21 @@ def test_models_image(
dtype: str,
) -> None:
input_texts_images = [
(text, asset.pil_image)
for text, asset in zip(HF_IMAGE_PROMPTS, image_assets)
(text, asset.pil_image) for text, asset in zip(HF_IMAGE_PROMPTS, image_assets)
]
# add cases for special_tokens
input_texts_images.append((
"\n<s><|user|>\n <|image_1|>\n\t <s>"
"Represent the given image for classification<|end|>"
"\n<|assistant|>\n",
Image.open(
get_vllm_public_assets(filename="cherry_blossom.jpg",
s3_prefix=VLM_IMAGES_DIR)),
))
input_texts_images.append(
(
"\n<s><|user|>\n <|image_1|>\n\t <s>"
"Represent the given image for classification<|end|>"
"\n<|assistant|>\n",
Image.open(
get_vllm_public_assets(
filename="cherry_blossom.jpg", s3_prefix=VLM_IMAGES_DIR
)
),
)
)
input_texts = [text for text, _ in input_texts_images]
input_images = [image for _, image in input_texts_images]