





from __future__ import annotations

import math





def lowerCAmelCase__(__snake_case ,__snake_case ,__snake_case ,__snake_case ,__snake_case							)       ->   Dict:







 '''simple docstring'''







 if depth < 0:
  raise ValueError('''Depth cannot be less than 0'''							)

 if len(_UpperCamelCase							) == 0:
  raise ValueError('''Scores cannot be empty'''							)

 if depth == height:
  return scores[node_index]

 if is_max:
  return max(
      minimax(depth + 1 ,node_index * 2 ,_UpperCamelCase ,_UpperCamelCase ,_UpperCamelCase							) ,minimax(depth + 1 ,node_index * 2 + 1 ,_UpperCamelCase ,_UpperCamelCase ,_UpperCamelCase							) ,)

 return min(
     minimax(depth + 1 ,node_index * 2 ,_UpperCamelCase ,_UpperCamelCase ,_UpperCamelCase							) ,minimax(depth + 1 ,node_index * 2 + 1 ,_UpperCamelCase ,_UpperCamelCase ,_UpperCamelCase							) ,)





def lowerCAmelCase__()       ->   str:







 '''simple docstring'''







 lowerCamelCase__              =	[90, 23, 6, 33, 21, 65, 123, 34423]
 lowerCamelCase__              =	math.log(len(_UpperCamelCase							) ,2							)
 print('''Optimal value : ''' ,end=''''''							)
 print(minimax(0 ,0 ,_UpperCamelCase ,_UpperCamelCase ,_UpperCamelCase							)							)


if __name__ == "__main__":
   import doctest

   doctest.testmod()
   main()










import warnings

from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor


_a						=   logging.get_logger(__name__)






class       __A					(					lowerCAmelCase				):

			'''simple docstring'''







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



				'''simple docstring'''







				warnings.warn(
				    '''The class SegformerFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'''
				    ''' Please use SegformerImageProcessor instead.''' ,						__lowerCAmelCase ,						)
				super().__init__(*__lowerCAmelCase ,						**__lowerCAmelCase							)



