



from __future__ import annotations

import math
import random







def  _UpperCAmelCase  (				SCREAMING_SNAKE_CASE__			,SCREAMING_SNAKE_CASE__			,SCREAMING_SNAKE_CASE__  ):


						'''simple docstring'''




						lowerCAmelCase	:   Any					     =					d * e - 1
						lowerCAmelCase	:   List[Any]					     =					0
						lowerCAmelCase	:   Optional[Any]					     =					0
						while p == 0:
												lowerCAmelCase	:   Tuple					     =					random.randint(2			,n - 1  )
												lowerCAmelCase	:   Optional[Any]					     =					k
												while True:
																		if t % 2 == 0:
																								lowerCAmelCase	:   int					     =					t // 2
																								lowerCAmelCase	:   Union[str, Any]					     =					(g**t) % n
																								lowerCAmelCase	:   Any					     =					math.gcd(x - 1			,_lowerCAmelCase  )
																								if x > 1 and y > 1:
																														lowerCAmelCase	:   str					     =					y
																														lowerCAmelCase	:   Any					     =					n // y
																														break  # find the correct factors
																		else:
																								break  # t is not divisible by 2, break and choose another g
						return sorted([p, q]  )


if __name__ == "__main__":
		import doctest

		doctest.testmod()


import warnings

from ...utils import logging
from .image_processing_conditional_detr import ConditionalDetrImageProcessor


__lowerCAmelCase    :  Tuple										= logging.get_logger(__name__)
class 				lowerCamelCase			(							__snake_case					):






      def __init__(      self  ,		*__lowerCamelCase  ,		**__lowerCamelCase						)     ->				None:


          '''simple docstring'''







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


