

A_ :				int						 =    tuple[float, float, float]
A_ :				Optional[Any]						 =    tuple[float, float, float]

def 		UpperCamelCase      (lowercase_:				Pointad					,   lowercase_:				Pointad      )  ->   Vectorad:
	A__							:					List[Any]       =	end_pointa[0] - end_pointa[0]
	A__							:					Union[str, Any]       =	end_pointa[1] - end_pointa[1]
	A__							:					List[str]       =	end_pointa[2] - end_pointa[2]
	return (x, y, z)

def 		UpperCamelCase      (lowercase_:				Vectorad					,   lowercase_:				Vectorad      )  ->   Vectorad:
	A__							:					Optional[int]       =	ab[1] * ac[2] - ab[2] * ac[1]  # *i
	A__							:					Dict       =	(ab[0] * ac[2] - ab[2] * ac[0]) * -1  # *j
	A__							:					Dict       =	ab[0] * ac[1] - ab[1] * ac[0]  # *k
	return (x, y, z)

def 		UpperCamelCase      (lowercase_:				Vectorad					,   lowercase_:				int      )  ->   bool:
	return tuple(round(lowercase_					,   lowercase_      ) for x in vector      ) == (0, 0, 0)


def 		UpperCamelCase      (lowercase_:				Pointad					,   lowercase_:				Pointad					,   lowercase_:				Pointad					,   lowercase_:				int = 10      )  ->   bool:
	A__							:					Tuple       =	create_vector(lowercase_					,   lowercase_      )
	A__							:					Dict       =	create_vector(lowercase_					,   lowercase_      )
	return is_zero_vector(get_ad_vectors_cross(lowercase_					,   lowercase_      )					,   lowercase_      )






import warnings

from ...utils import logging
from .image_processing_poolformer import PoolFormerImageProcessor


A_ :				Union[str, Any]						 =    logging.get_logger(__name__)



class 					_a		(__magic_name__       ):


					'''simple docstring'''






					def __init__(				self					, *A__					, **A__    ):
						warnings.warn(
						    """The class PoolFormerFeatureExtractor is deprecated and will be removed in version 5 of Transformers."""
						    """ Please use PoolFormerImageProcessor instead."""					, A__					, )
						super().__init__(*A__					, **A__    )



