"""simple docstring"""

import random






def      lowercase		(						a__	:		list ,  a__	:		List[Any]     )						->   tuple:
					_UpperCamelCase						,							_UpperCamelCase						,							_UpperCamelCase      						=	[], [], []
					for element in data:
										if element < pivot:
															less.append(UpperCamelCase__     )
										elif element > pivot:
															greater.append(UpperCamelCase__     )
										else:
															equal.append(UpperCamelCase__     )
					return less, equal, greater






def      lowercase		(						a__	:		list ,  a__	:		int     )						->   Optional[int]:
					# index = len(items) // 2 when trying to find the median
					#   (value of index when items is sorted)

					# invalid input
					if index >= len(UpperCamelCase__     ) or index < 0:
										return None

					_UpperCamelCase      						=	items[random.randint(0 ,  len(UpperCamelCase__     ) - 1     )]
					_UpperCamelCase      						=	0
					_UpperCamelCase						,							_UpperCamelCase						,							_UpperCamelCase      						=	_partition(UpperCamelCase__ ,  UpperCamelCase__     )
					_UpperCamelCase      						=	len(UpperCamelCase__     )
					_UpperCamelCase      						=	len(UpperCamelCase__     )

					# index is the pivot
					if m <= index < m + count:
										return pivot
					# must be in smaller
					elif m > index:
										return quick_select(UpperCamelCase__ ,  UpperCamelCase__     )
					# must be in larger
					else:
										return quick_select(UpperCamelCase__ ,  index - (m + count)     )







from ..utils import DummyObject, requires_backends




class     SCREAMING_SNAKE_CASE__ (						metaclass=UpperCamelCase__      ):
 __SCREAMING_SNAKE_CASE							       =	['''keras_nlp''']



 def __init__(							self,*__lowerCamelCase,**__lowerCamelCase ):
        requires_backends(self,['''keras_nlp'''] )





