





'''simple docstring'''






from __future__ import annotations

import math


def 				snake_case_  (      _lowerCAmelCase						:		int     ,   _lowerCAmelCase						:		int     ,   _lowerCAmelCase						:		bool     ,   _lowerCAmelCase						:		list[int]     ,   _lowerCAmelCase						:		float						)   ->     int:

							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 				snake_case_  (      )   ->     None:
							UpperCAmelCase				: Tuple											=	[90, 23, 6, 33, 21, 65, 123, 34423]
							UpperCAmelCase				: Union[str, Any]											=	math.log(len(_lowerCAmelCase						)     ,   2						)
							print('''Optimal value : '''     ,   end=''''''						)
							print(minimax(0     ,   0     ,   _lowerCAmelCase     ,   _lowerCAmelCase     ,   _lowerCAmelCase						)						)


if __name__ == "__main__":
						import doctest

						doctest.testmod()
						main()










'''simple docstring'''






import pytest

from datasets.splits import SplitDict, SplitInfo
from datasets.utils.py_utils import asdict


@pytest.mark.parametrize(
    '''split_dict'''     ,   [
        SplitDict(),
        SplitDict({'''train''': SplitInfo(name='''train'''     ,   num_bytes=1337     ,   num_examples=42     ,   dataset_name='''my_dataset'''						)}						),
        SplitDict({'''train''': SplitInfo(name='''train'''     ,   num_bytes=1337     ,   num_examples=42						)}						),
        SplitDict({'''train''': SplitInfo()}						),
    ]     ,   )
def 				snake_case_  (      _lowerCAmelCase						:		SplitDict						)   ->     List[Any]:
							UpperCAmelCase				: str											=	split_dict._to_yaml_list()
							assert len(_lowerCAmelCase						) == len(_lowerCAmelCase						)
							UpperCAmelCase				: Optional[int]											=	SplitDict._from_yaml_list(_lowerCAmelCase						)
							for split_name, split_info in split_dict.items():
														# dataset_name field is deprecated, and is therefore not part of the YAML dump
														UpperCAmelCase				: Optional[Any]											=	None
														# the split name of split_dict takes over the name of the split info object
														UpperCAmelCase				: Dict											=	split_name
							assert split_dict == reloaded




@pytest.mark.parametrize(
    '''split_info'''     ,   [SplitInfo(), SplitInfo(dataset_name=_lowerCAmelCase						), SplitInfo(dataset_name='''my_dataset'''						)]						)
def 				snake_case_  (      _lowerCAmelCase						:		List[Any]						)   ->     Optional[Any]:
							# For backward compatibility, we need asdict(split_dict) to return split info dictrionaries with the "dataset_name"
							# field even if it's deprecated. This way old versionso of `datasets` can still reload dataset_infos.json files
							UpperCAmelCase				: Any											=	asdict(SplitDict({'''train''': split_info}						)						)
							assert "dataset_name" in split_dict_asdict["train"]
							assert split_dict_asdict["train"]["dataset_name"] == split_info.dataset_name





