


from __future__ import annotations

import math






def 							__lowercase     (				__lowerCAmelCase							:       int      ,					__lowerCAmelCase							:       int      ,					__lowerCAmelCase							:       bool      ,					__lowerCAmelCase							:       list[int]      ,					__lowerCAmelCase							:       float     ):

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

							if len(__lowerCAmelCase     ) == 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      ,					__lowerCAmelCase      ,					__lowerCAmelCase      ,					__lowerCAmelCase     )      ,					minimax(depth + 1      ,					node_index * 2 + 1      ,					__lowerCAmelCase      ,					__lowerCAmelCase      ,					__lowerCAmelCase     )      ,					)

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






def 							__lowercase     (				):
							a__    =  [9_0, 2_3, 6, 3_3, 2_1, 6_5, 1_2_3, 3_4_4_2_3]
							a__    =  math.log(len(__lowerCAmelCase     )      ,					2     )
							print('Optimal value : '      ,					end=''     )
							print(minimax(0      ,					0      ,					__lowerCAmelCase      ,					__lowerCAmelCase      ,					__lowerCAmelCase     )     )


if __name__ == "__main__":
						import doctest

						doctest.testmod()
						main()








from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


snake_case							: Optional[Any]      =   {'''configuration_focalnet''': ['''FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FocalNetConfig''']}


try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						snake_case							: Optional[int]      =   [
						    '''FOCALNET_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''FocalNetForImageClassification''',
						    '''FocalNetForMaskedImageModeling''',
						    '''FocalNetBackbone''',
						    '''FocalNetModel''',
						    '''FocalNetPreTrainedModel''',
						]

if TYPE_CHECKING:
						from .configuration_focalnet import FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP, FocalNetConfig

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_focalnet import (
												    FOCALNET_PRETRAINED_MODEL_ARCHIVE_LIST,
												    FocalNetBackbone,
												    FocalNetForImageClassification,
												    FocalNetForMaskedImageModeling,
												    FocalNetModel,
												    FocalNetPreTrainedModel,
												)

else:
						import sys

						snake_case							: Union[str, Any]      =   _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




