



'''simple docstring'''





from __future__ import annotations

import math
def    _SCREAMING_SNAKE_CASE  (       UpperCamelCase							,    UpperCamelCase							,    UpperCamelCase							,    UpperCamelCase							,    UpperCamelCase			):



    """simple docstring"""





    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							,    UpperCamelCase							,    UpperCamelCase							,    UpperCamelCase			)							,    minimax(depth + 1							,    node_index * 2 + 1							,    UpperCamelCase							,    UpperCamelCase							,    UpperCamelCase			)							,    )
        if is_max
        else min(
            minimax(depth + 1							,    node_index * 2							,    UpperCamelCase							,    UpperCamelCase							,    UpperCamelCase			)							,    minimax(depth + 1							,    node_index * 2 + 1							,    UpperCamelCase							,    UpperCamelCase							,    UpperCamelCase			)							,    )
    )
def    _SCREAMING_SNAKE_CASE  (       ):



    """simple docstring"""





    lowerCAmelCase__ :  Tuple							      =					[90, 23, 6, 33, 21, 65, 123, 34423]
    lowerCAmelCase__ :  Optional[int]							      =					math.log(len(UpperCamelCase			)							,    2			)
    print(f"""Optimal value : {minimax(0							,    0							,    UpperCamelCase							,    UpperCamelCase							,    UpperCamelCase			)}"""			)


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 main()






from .glue import glue_convert_examples_to_features, glue_output_modes, glue_processors, glue_tasks_num_labels
from .squad import SquadExample, SquadFeatures, SquadVaProcessor, SquadVaProcessor, squad_convert_examples_to_features
from .utils import DataProcessor, InputExample, InputFeatures, SingleSentenceClassificationProcessor
from .xnli import xnli_output_modes, xnli_processors, xnli_tasks_num_labels