import numpy as np
def    A			(					_lowercase		):
						return 1 / (1 + np.exp(-vector		))
def    A			(					_lowercase		):
						return vector * sigmoid(_snake_case		)


if __name__ == "__main__":
					import doctest

					doctest.testmod()




import random
def    A			(					_lowercase	,						_lowercase		):
						SCREAMING_SNAKE_CASE       ,						SCREAMING_SNAKE_CASE       ,						SCREAMING_SNAKE_CASE							:					Tuple           =							[], [], []
						for element in data:
												if element < pivot:
																		less.append(_lowercase		)
												elif element > pivot:
																		greater.append(_lowercase		)
												else:
																		equal.append(_lowercase		)
						return less, equal, greater



def    A			(					_lowercase	,						_lowercase		):
						# index = len(items) // 2 when trying to find the median
						#   (value of index when items is sorted)

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

						SCREAMING_SNAKE_CASE							:					Dict           =							items[random.randint(0	,						len(_lowercase		) - 1		)]
						SCREAMING_SNAKE_CASE							:					int           =							0
						SCREAMING_SNAKE_CASE       ,						SCREAMING_SNAKE_CASE       ,						SCREAMING_SNAKE_CASE							:					List[str]           =							_partition(_lowercase	,						_lowercase		)
						SCREAMING_SNAKE_CASE							:					List[Any]           =							len(_lowercase		)
						SCREAMING_SNAKE_CASE							:					Optional[Any]           =							len(_lowercase		)

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





