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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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112
tests/v1/engine/test_processor_multi_modal_uuids.py
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@@ -16,35 +16,33 @@ baby_reading_np_ndarrays = VideoAsset("baby_reading").np_ndarrays
# Mock processor for testing
def _mk_processor(monkeypatch,
*,
mm_cache_gb: float = 4.0,
enable_prefix_caching: bool = True) -> Processor:
def _mk_processor(
monkeypatch, *, mm_cache_gb: float = 4.0, enable_prefix_caching: bool = True
) -> Processor:
"""
Create a Processor instance with minimal configuration suitable for unit
tests without accessing external resources.
"""
monkeypatch.setattr(ModelConfig,
"try_get_generation_config",
lambda self: {},
raising=True)
monkeypatch.setattr(ModelConfig,
"__post_init__",
lambda self, *args: None,
raising=True)
monkeypatch.setattr(ModelConfig,
"verify_with_parallel_config",
lambda self, parallel_config: None,
raising=True)
monkeypatch.setattr(processor_mod,
"processor_cache_from_config",
lambda vllm_config, mm_registry: None,
raising=True)
monkeypatch.setattr(
ModelConfig, "try_get_generation_config", lambda self: {}, raising=True
)
monkeypatch.setattr(
ModelConfig, "__post_init__", lambda self, *args: None, raising=True
)
monkeypatch.setattr(
ModelConfig,
"verify_with_parallel_config",
lambda self, parallel_config: None,
raising=True,
)
monkeypatch.setattr(
processor_mod,
"processor_cache_from_config",
lambda vllm_config, mm_registry: None,
raising=True,
)
monkeypatch.setattr(VllmConfig,
"__post_init__",
lambda self: None,
raising=True)
monkeypatch.setattr(VllmConfig, "__post_init__", lambda self: None, raising=True)
model_config = ModelConfig(
skip_tokenizer_init=True,
@@ -57,12 +55,10 @@ def _mk_processor(monkeypatch,
# Minimal multimodal_config to satisfy references in
# Processor.process_inputs.
class _MockMMConfig:
def __init__(self, gb: float):
self.mm_processor_cache_gb = gb
model_config.multimodal_config = _MockMMConfig(
mm_cache_gb) # type: ignore[attr-defined]
model_config.multimodal_config = _MockMMConfig(mm_cache_gb) # type: ignore[attr-defined]
vllm_config = VllmConfig(
model_config=model_config,
cache_config=CacheConfig(enable_prefix_caching=enable_prefix_caching),
@@ -79,13 +75,9 @@ def test_multi_modal_uuids_length_mismatch_raises(monkeypatch):
prompt = {
"prompt": "USER: <image>\nDescribe\nASSISTANT:",
"multi_modal_data": {
"image": [cherry_pil_image, stop_pil_image]
},
"multi_modal_data": {"image": [cherry_pil_image, stop_pil_image]},
# Mismatch: 2 items but only 1 uuid provided
"multi_modal_uuids": {
"image": ["hash_cherry"]
},
"multi_modal_uuids": {"image": ["hash_cherry"]},
}
with pytest.raises(ValueError, match="must have same length as data"):
@@ -104,16 +96,13 @@ def test_multi_modal_uuids_missing_modality_raises(monkeypatch):
# Two modalities provided in data
"multi_modal_data": {
"image": [cherry_pil_image],
"video": [baby_reading_np_ndarrays]
"video": [baby_reading_np_ndarrays],
},
# Only image uuids provided; video missing should raise
"multi_modal_uuids": {
"image": ["hash_cherry"]
},
"multi_modal_uuids": {"image": ["hash_cherry"]},
}
with pytest.raises(ValueError,
match="must be provided if multi_modal_data"):
with pytest.raises(ValueError, match="must be provided if multi_modal_data"):
processor.process_inputs(
request_id="req-2",
prompt=prompt, # type: ignore[arg-type]
@@ -130,28 +119,28 @@ def test_multi_modal_uuids_missing_modality_raises(monkeypatch):
],
)
def test_multi_modal_uuids_accepts_none_and_passes_through(
monkeypatch, mm_cache_gb: float, enable_prefix_caching: bool):
processor = _mk_processor(monkeypatch,
mm_cache_gb=mm_cache_gb,
enable_prefix_caching=enable_prefix_caching)
monkeypatch, mm_cache_gb: float, enable_prefix_caching: bool
):
processor = _mk_processor(
monkeypatch,
mm_cache_gb=mm_cache_gb,
enable_prefix_caching=enable_prefix_caching,
)
# Capture the overrides passed to InputPreprocessor.preprocess
captured: dict[str, object] = {}
def fake_preprocess(prompt,
*,
tokenization_kwargs=None,
lora_request=None,
mm_uuids=None):
def fake_preprocess(
prompt, *, tokenization_kwargs=None, lora_request=None, mm_uuids=None
):
captured["mm_uuids"] = mm_uuids
# Minimal processed inputs for decoder-only flow
return {"type": "token", "prompt_token_ids": [1]}
# Monkeypatch only the bound preprocess method on this instance
monkeypatch.setattr(processor.input_preprocessor,
"preprocess",
fake_preprocess,
raising=True)
monkeypatch.setattr(
processor.input_preprocessor, "preprocess", fake_preprocess, raising=True
)
# Use a consistent two-image scenario across all configurations
mm_uuids = {"image": [None, "hash_stop"], "video": None}
@@ -176,24 +165,19 @@ def test_multi_modal_uuids_accepts_none_and_passes_through(
def test_multi_modal_uuids_ignored_when_caching_disabled(monkeypatch):
# When both processor cache is 0 and prefix caching disabled, the
# processor builds overrides from request id instead of using user UUIDs.
processor = _mk_processor(monkeypatch,
mm_cache_gb=0.0,
enable_prefix_caching=False)
processor = _mk_processor(monkeypatch, mm_cache_gb=0.0, enable_prefix_caching=False)
captured: dict[str, object] = {}
def fake_preprocess(prompt,
*,
tokenization_kwargs=None,
lora_request=None,
mm_uuids=None):
def fake_preprocess(
prompt, *, tokenization_kwargs=None, lora_request=None, mm_uuids=None
):
captured["mm_uuids"] = mm_uuids
return {"type": "token", "prompt_token_ids": [1]}
monkeypatch.setattr(processor.input_preprocessor,
"preprocess",
fake_preprocess,
raising=True)
monkeypatch.setattr(
processor.input_preprocessor, "preprocess", fake_preprocess, raising=True
)
request_id = "req-42"
mm_uuids = {"image": ["hash_cherry", "hash_stop"], "video": "hash_video"}