


'''simple docstring'''



from __future__ import annotations

import math


def 				lowerCamelCase__				(	A       :      int				,       A       :      int				,       A       :      bool				,       A       :      list[int]				,       A       :      float					):




						'''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				,       A				,       A				,       A					)				,       minimax(depth + 1				,       node_index * 2 + 1				,       A				,       A				,       A					)				,       )
						    if is_max
						    else min(
						        minimax(depth + 1				,       node_index * 2				,       A				,       A				,       A					)				,       minimax(depth + 1				,       node_index * 2 + 1				,       A				,       A				,       A					)				,       )
						)


def 				lowerCamelCase__				(	):




						'''simple docstring'''






						UpperCAmelCase					    =     [90, 23, 6, 33, 21, 65, 1_23, 3_44_23]
						UpperCAmelCase					    =     math.log(len(A					)				,       2					)
						print(f"""Optimal value : {minimax(0				,       0				,       A				,       A				,       A					)}"""					)


if __name__ == "__main__":
	import doctest

	doctest.testmod()
	main()






'''simple docstring'''



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_lowercase      :      List[Any]            =					{
    """configuration_x_clip""": [
        """XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """XCLIPConfig""",
        """XCLIPTextConfig""",
        """XCLIPVisionConfig""",
    ],
    """processing_x_clip""": ["""XCLIPProcessor"""],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_lowercase      :      List[str]            =					[
	    """XCLIP_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """XCLIPModel""",
	    """XCLIPPreTrainedModel""",
	    """XCLIPTextModel""",
	    """XCLIPVisionModel""",
	]

if TYPE_CHECKING:
	from .configuration_x_clip import (
	    XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    XCLIPConfig,
	    XCLIPTextConfig,
	    XCLIPVisionConfig,
	)
	from .processing_x_clip import XCLIPProcessor

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_x_clip import (
		    XCLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
		    XCLIPModel,
		    XCLIPPreTrainedModel,
		    XCLIPTextModel,
		    XCLIPVisionModel,
		)

else:
	import sys

	_lowercase      :      List[Any]            =					_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)





