






from __future__ import annotations

import math

def    UpperCamelCase						(	_A,   _A,   _A,   _A,   _A			):






						"""simple docstring"""







						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    UpperCamelCase						(	):






						"""simple docstring"""







						__magic_name__      :       Optional[Any]       						= [90, 23, 6, 33, 21, 65, 123, 34423]
						__magic_name__      :       List[Any]       						= 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, is_vision_available


__magic_name__:					List[Any]							=     {
    "configuration_conditional_detr": [
        "CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "ConditionalDetrConfig",
        "ConditionalDetrOnnxConfig",
    ]
}

try:
		if not is_vision_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__magic_name__:					List[str]							=     ["ConditionalDetrFeatureExtractor"]
		__magic_name__:					int							=     ["ConditionalDetrImageProcessor"]

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__magic_name__:					List[Any]							=     [
		    "CONDITIONAL_DETR_PRETRAINED_MODEL_ARCHIVE_LIST",
		    "ConditionalDetrForObjectDetection",
		    "ConditionalDetrForSegmentation",
		    "ConditionalDetrModel",
		    "ConditionalDetrPreTrainedModel",
		]


if TYPE_CHECKING:
		from .configuration_conditional_detr import (
		    CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP,
		    ConditionalDetrConfig,
		    ConditionalDetrOnnxConfig,
		)

		try:
				if not is_vision_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .feature_extraction_conditional_detr import ConditionalDetrFeatureExtractor
				from .image_processing_conditional_detr import ConditionalDetrImageProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_conditional_detr import (
				    CONDITIONAL_DETR_PRETRAINED_MODEL_ARCHIVE_LIST,
				    ConditionalDetrForObjectDetection,
				    ConditionalDetrForSegmentation,
				    ConditionalDetrModel,
				    ConditionalDetrPreTrainedModel,
				)

else:
		import sys

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