



"""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


__SCREAMING_SNAKE_CASE	:    List[Any]     				=   logging.get_logger(__name__)

__SCREAMING_SNAKE_CASE	:    List[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 				lowerCamelCase_( __lowercase     ):





					'''simple docstring'''



					lowercase__ :							int              =			"mobilenet_v1"

					def __init__(     self					,							lowerCamelCase__=3					,							lowerCamelCase__=2_2_4					,							lowerCamelCase__=1.0					,							lowerCamelCase__=8					,							lowerCamelCase__="relu6"					,							lowerCamelCase__=True					,							lowerCamelCase__=0.9_9_9					,							lowerCamelCase__=0.0_2					,							lowerCamelCase__=0.0_0_1					,							**lowerCamelCase__					,							):
									super().__init__(**_a )

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

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


class 				lowerCamelCase_( __lowercase     ):





					'''simple docstring'''



					lowercase__ :							str              =			version.parse('1.11'     )

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

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





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



from __future__ import annotations

from dataclasses import dataclass

@dataclass
class 							UpperCAmelCase_						:
							"""simple docstring"""







							UpperCAmelCase__			:		float
							UpperCAmelCase__			:		TreeNode | None             =       None
							UpperCAmelCase__			:		TreeNode | None             =       None



def   __UpperCAmelCase					(      __a :     TreeNode | None      )     ->	bool:

					"""simple docstring"""

					def is_valid_tree(__a :     TreeNode | None      ) -> bool:
										if node is None:
															return True

										if not isinstance(__a						,__a      ):
															return False

										try:
															float(node.data      )
										except (TypeError, ValueError):
															return False

										return is_valid_tree(node.left      ) and is_valid_tree(node.right      )

					if not is_valid_tree(__a      ):
										raise ValueError(
										    '''Each node should be type of TreeNode and data should be float.'''      )

					def is_binary_search_tree_recursive_check(
					    __a :     TreeNode | None						,__a :     float						,__a :     float      ) -> bool:

										if node is None:
															return True

										return (
										    left_bound < node.data < right_bound
										    and is_binary_search_tree_recursive_check(node.left						,__a						,node.data      )
										    and is_binary_search_tree_recursive_check(
										        node.right						,node.data						,__a      )
										)

					return is_binary_search_tree_recursive_check(__a						,-float('''inf'''      )						,float('''inf'''      )      )


if __name__ == "__main__":
			import doctest

			doctest.testmod()



