





from __future__ import annotations

import math







def  _SCREAMING_SNAKE_CASE				(   a					,						a					,						a					,						a					,						a  )      ->      int:

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

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

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







def  _SCREAMING_SNAKE_CASE				(   )      ->      None:
					__A	:						Union[str, Any]       =				[90, 23, 6, 33, 21, 65, 1_23, 3_44_23]
					__A	:						Tuple       =				math.log(len(a  )					,						2  )
					print('Optimal value : '					,						end=''  )
					print(minimax(0					,						0					,						a					,						a					,						a  )  )


if __name__ == "__main__":
				import doctest

				doctest.testmod()
				main()











from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


UpperCAmelCase						:   Any			  =     {
    '''configuration_falcon''': ['''FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FalconConfig'''],
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				UpperCAmelCase						:   Any			  =     [
				    '''FALCON_PRETRAINED_MODEL_ARCHIVE_LIST''',
				    '''FalconForCausalLM''',
				    '''FalconModel''',
				    '''FalconPreTrainedModel''',
				    '''FalconForSequenceClassification''',
				    '''FalconForTokenClassification''',
				    '''FalconForQuestionAnswering''',
				]


if TYPE_CHECKING:
				from .configuration_falcon import FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP, FalconConfig

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_falcon import (
								    FALCON_PRETRAINED_MODEL_ARCHIVE_LIST,
								    FalconForCausalLM,
								    FalconForQuestionAnswering,
								    FalconForSequenceClassification,
								    FalconForTokenClassification,
								    FalconModel,
								    FalconPreTrainedModel,
								)


else:
				import sys

				UpperCAmelCase						:   List[str]			  =     _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




