





"""simple docstring"""






from __future__ import annotations

import math

def       __A (     a_  :int				,    a_  :int				,    a_  :bool				,    a_  :list[int]				,    a_  :float)						->						int:




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

				if not scores:
								raise ValueError('''Scores cannot be empty''')

				if depth == height:
								return scores[node_index]

				return (
				    max(
				        minimax(depth + 1				,    node_index * 2				,    snake_case_				,    snake_case_				,    snake_case_)				,    minimax(depth + 1				,    node_index * 2 + 1				,    snake_case_				,    snake_case_				,    snake_case_)				,    )
				    if is_max
				    else min(
				        minimax(depth + 1				,    node_index * 2				,    snake_case_				,    snake_case_				,    snake_case_)				,    minimax(depth + 1				,    node_index * 2 + 1				,    snake_case_				,    snake_case_				,    snake_case_)				,    )
				)

def       __A (     )						->						None:
				__a	:  List[Any]         =					[90, 23, 6, 33, 21, 65, 1_23, 3_44_23]
				__a	:  Dict         =					math.log(len(snake_case_)				,    2)
				print(F"""Optimal value : {minimax(0				,    0				,    snake_case_				,    snake_case_				,    snake_case_)}""")


if __name__ == "__main__":
		import doctest

		doctest.testmod()
		main()






"""simple docstring"""






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


A	     =					{
    '''configuration_mvp''': ['''MVP_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MvpConfig''', '''MvpOnnxConfig'''],
    '''tokenization_mvp''': ['''MvpTokenizer'''],
}

try:
		if not is_tokenizers_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		A	     =					['''MvpTokenizerFast''']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		A	     =					[
		    '''MVP_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''MvpForCausalLM''',
		    '''MvpForConditionalGeneration''',
		    '''MvpForQuestionAnswering''',
		    '''MvpForSequenceClassification''',
		    '''MvpModel''',
		    '''MvpPreTrainedModel''',
		]

if TYPE_CHECKING:
		from .configuration_mvp import MVP_PRETRAINED_CONFIG_ARCHIVE_MAP, MvpConfig, MvpOnnxConfig
		from .tokenization_mvp import MvpTokenizer

		try:
				if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .tokenization_mvp_fast import MvpTokenizerFast

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_mvp import (
				    MVP_PRETRAINED_MODEL_ARCHIVE_LIST,
				    MvpForCausalLM,
				    MvpForConditionalGeneration,
				    MvpForQuestionAnswering,
				    MvpForSequenceClassification,
				    MvpModel,
				    MvpPreTrainedModel,
				)

else:
		import sys

		A	     =					_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)