

import math

def 							__SCREAMING_SNAKE_CASE							(				lowerCAmelCase:  List[Any]  ,      lowerCAmelCase:  List[str] )   ->       List[str]:
				return math.pow(__A  ,      2 ) - a

def 							__SCREAMING_SNAKE_CASE							(				lowerCAmelCase:  Dict )   ->       List[Any]:
				return 2 * x

def 							__SCREAMING_SNAKE_CASE							(				lowerCAmelCase:  int )   ->       int:
				_UpperCAmelCase       :		List[str] 		=    2.0

				while start <= a:
								_UpperCAmelCase       :		Tuple 		=    math.pow(__A  ,      2 )

				return start

def 							__SCREAMING_SNAKE_CASE							(				lowerCAmelCase:  Any  ,      lowerCAmelCase:  Dict = 9999  ,      lowerCAmelCase:  Tuple = 0.00_000_000_000_001 )   ->       str:

				if a < 0:
								raise ValueError("math domain error" )

				_UpperCAmelCase       :		Optional[int] 		=    get_initial_point(__A )

				for _ in range(__A ):
								_UpperCAmelCase       :		int 		=    value
								_UpperCAmelCase       :		Optional[Any] 		=    value - fx(__A  ,      __A ) / fx_derivative(__A )
								if abs(prev_value - value ) < tolerance:
												return value

				return value


if __name__ == "__main__":
					from doctest import testmod

					testmod()





import warnings

from ...utils import logging
from .image_processing_deformable_detr import DeformableDetrImageProcessor


SCREAMING_SNAKE_CASE_        =      logging.get_logger(__name__)

class 				a  (	UpperCAmelCase				):


						def __init__(       self						,					*A_						,					**A_	):







										'''simple docstring'''


										warnings.warn(
										    "The class DeformableDetrFeatureExtractor is deprecated and will be removed in version 5 of Transformers."
										    " Please use DeformableDetrImageProcessor instead."						,					A_						,					)
										super().__init__(*A_						,					**A_	)


