"""simple docstring"""






from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


lowerCAmelCase__  :  Any						     =	logging.get_logger(__name__)

lowerCAmelCase__  :  Union[str, Any]						     =	{
    'google/mobilenet_v1_1.0_224': 'https://huggingface.co/google/mobilenet_v1_1.0_224/resolve/main/config.json',
    'google/mobilenet_v1_0.75_192': 'https://huggingface.co/google/mobilenet_v1_0.75_192/resolve/main/config.json',
    # See all MobileNetV1 models at https://huggingface.co/models?filter=mobilenet_v1
}
class 				snake_case       ( _UpperCamelCase				):




					"""simple docstring"""

					snake_case__				    = "mobilenet_v1"







					def __init__(				self   :	Optional[Any]    ,lowerCamelCase__   :	List[Any]=3    ,lowerCamelCase__   :	Tuple=224    ,lowerCamelCase__   :	List[Any]=1.0    ,lowerCamelCase__   :	List[Any]=8    ,lowerCamelCase__   :	int="relu6"    ,lowerCamelCase__   :	Tuple=True    ,lowerCamelCase__   :	Optional[Any]=0.9_9_9    ,lowerCamelCase__   :	Dict=0.0_2    ,lowerCamelCase__   :	Union[str, Any]=0.0_0_1    ,**lowerCamelCase__   :	Tuple    ,):
									super().__init__(**lowerCAmelCase_			)

									if depth_multiplier <= 0:
													raise ValueError('depth_multiplier must be greater than zero.'			)

									UpperCAmelCase__             =							num_channels
									UpperCAmelCase__             =							image_size
									UpperCAmelCase__             =							depth_multiplier
									UpperCAmelCase__             =							min_depth
									UpperCAmelCase__             =							hidden_act
									UpperCAmelCase__             =							tf_padding
									UpperCAmelCase__             =							classifier_dropout_prob
									UpperCAmelCase__             =							initializer_range
									UpperCAmelCase__             =							layer_norm_eps






class 				snake_case       ( _UpperCamelCase				):




					"""simple docstring"""

					snake_case__				    = version.parse("1.11"				)







					@property
					def 		__lowerCAmelCase						(				self   :	int			):
									return OrderedDict([('pixel_values', {0: 'batch'})]			)







					@property
					def 		__lowerCAmelCase						(				self   :	List[Any]			):
									if self.task == "image-classification":
													return OrderedDict([('logits', {0: 'batch'})]			)
									else:
													return OrderedDict([('last_hidden_state', {0: 'batch'}), ('pooler_output', {0: 'batch'})]			)







					@property
					def 		__lowerCAmelCase						(				self   :	Dict			):
									return 1e-4










from __future__ import annotations

import math

def   a_    ( lowerCAmelCase_      :			int,	lowerCAmelCase_      :			int,	lowerCAmelCase_      :			bool,	lowerCAmelCase_      :			list[int],	lowerCAmelCase_      :			float	):

   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   a_    ( ):
   __lowerCAmelCase								=	[90, 23, 6, 33, 21, 65, 123, 3_4423]
   __lowerCAmelCase								=	math.log(len(lowerCAmelCase_	),	2	)
   print('Optimal value : ',	end=''	)
   print(minimax(0,	0,	lowerCAmelCase_,	lowerCAmelCase_,	lowerCAmelCase_	)	)


if __name__ == "__main__":
     import doctest

     doctest.testmod()
     main()

