biondizzle/vllm
1
0
Fork 0
Code Issues Pull Requests Actions 2 Packages Projects Releases Wiki Activity

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

Browse Source 
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
Download Patch File Download Diff File Expand all files Collapse all files

35
tests/models/multimodal/pooling/test_clip.py
View File

@@ -12,10 +12,12 @@ HF_TEXT_PROMPTS = [
"a photo of a cherry blossom",
]
HF_IMAGE_PROMPTS = IMAGE_ASSETS.prompts({
"stop_sign": "",
"cherry_blossom": "",
})
HF_IMAGE_PROMPTS = IMAGE_ASSETS.prompts(
{
"stop_sign": "",
"cherry_blossom": "",
}
)
MODELS = ["openai/clip-vit-base-patch32"]
@@ -33,11 +35,9 @@ 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,
max_model_len=77) as vllm_model:
with vllm_runner(
model, runner="pooling", dtype=dtype, enforce_eager=True, max_model_len=77
) as vllm_model:
vllm_outputs = vllm_model.embed(input_texts, images=input_images)
with hf_runner(model, dtype=dtype, auto_cls=CLIPModel) as hf_model:
@@ -48,10 +48,12 @@ def _run_test(
if "pixel_values" in inputs:
inputs.pop("input_ids")
pooled_output = hf_model.model.get_image_features(
**hf_model.wrap_device(inputs)).squeeze(0)
**hf_model.wrap_device(inputs)
).squeeze(0)
else:
pooled_output = hf_model.model.get_text_features(
**hf_model.wrap_device(inputs)).squeeze(0)
**hf_model.wrap_device(inputs)
).squeeze(0)
all_outputs.append(pooled_output.tolist())
@@ -98,8 +100,7 @@ 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)
]
input_texts = [text for text, _ in input_texts_images]
input_images = [image for _, image in input_texts_images]
@@ -125,11 +126,9 @@ def test_models_text_image_no_crash(
texts = [HF_TEXT_PROMPTS[0]]
images = [image_assets[0].pil_image]
with vllm_runner(model,
runner="pooling",
dtype=dtype,
enforce_eager=True,
max_model_len=77) as vllm_model:
with vllm_runner(
model, runner="pooling", dtype=dtype, enforce_eager=True, max_model_len=77
) as vllm_model:
with pytest.raises(ValueError, match="not both"):
vllm_model.embed(texts, images=images)