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[Core][MultiModalHasher] Don't convert memoryviews to bytes during hashing (#24925)

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Signed-off-by: Lukas Geiger <lukas.geiger94@gmail.com>
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Lukas Geiger 2025-09-16 16:32:47 +01:00 committed by GitHub
parent 73cfb3c5ee
commit 08369289af
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GPG Key ID: B5690EEEBB952194
1 changed files with 18 additions and 29 deletions
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47
vllm/multimodal/hasher.py
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@ -20,22 +20,22 @@ logger = init_logger(__name__)
class MultiModalHasher:
@classmethod
def serialize_item(cls, obj: object) -> Union[bytes, memoryview]:
def serialize_item(cls, obj: object) -> Iterable[Union[bytes, memoryview]]:
# Simple cases
if isinstance(obj, str):
return obj.encode("utf-8")
if isinstance(obj, (bytes, memoryview)):
return obj
return (obj, )
if isinstance(obj, str):
return (obj.encode("utf-8"), )
if isinstance(obj, (int, float)):
return np.array(obj).tobytes()
return (np.array(obj).tobytes(), )
if isinstance(obj, Image.Image):
exif = obj.getexif()
if Image.ExifTags.Base.ImageID in exif and isinstance(
exif[Image.ExifTags.Base.ImageID], uuid.UUID):
# If the image has exif ImageID tag, use that
return exif[Image.ExifTags.Base.ImageID].bytes
return cls.item_to_bytes(
return (exif[Image.ExifTags.Base.ImageID].bytes, )
return cls.iter_item_to_bytes(
"image", np.asarray(convert_image_mode(obj, "RGBA")))
if isinstance(obj, torch.Tensor):
tensor_obj: torch.Tensor = obj.cpu()
@ -49,43 +49,34 @@ class MultiModalHasher:
tensor_obj = tensor_obj.view(
(tensor_obj.numel(), )).view(torch.uint8)
return cls.item_to_bytes(
return cls.iter_item_to_bytes(
"tensor", {
"original_dtype": str(tensor_dtype),
"original_shape": tuple(tensor_shape),
"data": tensor_obj.numpy(),
})
return cls.item_to_bytes("tensor", tensor_obj.numpy())
return cls.iter_item_to_bytes("tensor", tensor_obj.numpy())
if isinstance(obj, np.ndarray):
# If the array is non-contiguous, we need to copy it first
arr_data = obj.data if obj.flags.c_contiguous else obj.tobytes()
return cls.item_to_bytes("ndarray", {
arr_data = obj.view(
np.uint8).data if obj.flags.c_contiguous else obj.tobytes()
return cls.iter_item_to_bytes("ndarray", {
"dtype": obj.dtype.str,
"shape": obj.shape,
"data": arr_data,
})
logger.warning(
"No serialization method found for %s. "
"Falling back to pickle.", type(obj))
return pickle.dumps(obj)
@classmethod
def item_to_bytes(
cls,
key: str,
obj: object,
) -> bytes:
return b''.join(kb + vb for kb, vb in cls.iter_item_to_bytes(key, obj))
return (pickle.dumps(obj), )
@classmethod
def iter_item_to_bytes(
cls,
key: str,
obj: object,
) -> Iterable[tuple[bytes, Union[bytes, memoryview]]]:
) -> Iterable[Union[bytes, memoryview]]:
# Recursive cases
if isinstance(obj, (list, tuple)):
for i, elem in enumerate(obj):
@ -94,17 +85,15 @@ class MultiModalHasher:
for k, v in obj.items():
yield from cls.iter_item_to_bytes(f"{key}.{k}", v)
else:
key_bytes = key.encode("utf-8")
value_bytes = cls.serialize_item(obj)
yield key_bytes, value_bytes
yield key.encode("utf-8")
yield from cls.serialize_item(obj)
@classmethod
def hash_kwargs(cls, **kwargs: object) -> str:
hasher = blake3()
for k, v in kwargs.items():
for k_bytes, v_bytes in cls.iter_item_to_bytes(k, v):
hasher.update(k_bytes)
hasher.update(v_bytes)
for bytes_ in cls.iter_item_to_bytes(k, v):
hasher.update(bytes_)
return hasher.hexdigest()