






from __future__ import annotations

import sys
from collections import deque
from typing import Generic, TypeVar

UpperCamelCase			    =     TypeVar('''T''')



class 				__UpperCAmelCase		(Generic[T]   ):
			__snake_case    :				deque[T]  # Cache store of keys
			__snake_case    :				set[T]  # References of the keys in cache
			__snake_case    :				int									=							10  # Maximum capacity of cache







			def __init__(     self:  Union[str, Any]				,     UpperCAmelCase_:  int					):







									'''simple docstring'''




									_SCREAMING_SNAKE_CASE     				=  deque()
									_SCREAMING_SNAKE_CASE     				=  set()
									if not n:
															_SCREAMING_SNAKE_CASE     				=  sys.maxsize
									elif n < 0:
															raise ValueError("""n should be an integer greater than 0."""					)
									else:
															_SCREAMING_SNAKE_CASE     				=  n







			def 							UpperCamelCase				(     self:  Union[str, Any]				,     UpperCAmelCase_:  T					):







									'''simple docstring'''




									if x not in self.key_reference:
															if len(self.dq_store					) == LRUCache._MAX_CAPACITY:
																					_SCREAMING_SNAKE_CASE     				=  self.dq_store.pop()
																					self.key_reference.remove(UpperCAmelCase_					)
									else:
															self.dq_store.remove(UpperCAmelCase_					)

									self.dq_store.appendleft(UpperCAmelCase_					)
									self.key_reference.add(UpperCAmelCase_					)







			def 							UpperCamelCase				(     self:  List[Any]					):







									'''simple docstring'''




									for k in self.dq_store:
															print(UpperCAmelCase_					)







			def __repr__(     self:  Union[str, Any]					):







									'''simple docstring'''




									return F'LRUCache({self._MAX_CAPACITY}) => {list(self.dq_store					)}'


if __name__ == "__main__":
		import doctest

		doctest.testmod()

		UpperCamelCase			    =     LRUCache(4)
		lru_cache.refer('''A''')
		lru_cache.refer(2)
		lru_cache.refer(3)
		lru_cache.refer('''A''')
		lru_cache.refer(4)
		lru_cache.refer(5)
		lru_cache.display()

		print(lru_cache)
		assert str(lru_cache) == "LRUCache(4) => [5, 4, 'A', 3]"









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


UpperCamelCase			    =     logging.get_logger(__name__)

UpperCamelCase			    =     {
    '''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 				__UpperCAmelCase		(_UpperCAmelCase   ):
			__snake_case    :				Any									=							"mobilenet_v1"







			def __init__(     self:  List[str]				,     UpperCAmelCase_:  List[Any]=3				,     UpperCAmelCase_:  List[str]=224				,     UpperCAmelCase_:  Optional[Any]=1.0				,     UpperCAmelCase_:  Dict=8				,     UpperCAmelCase_:  List[str]="relu6"				,     UpperCAmelCase_:  List[Any]=True				,     UpperCAmelCase_:  Dict=0.9_99				,     UpperCAmelCase_:  Union[str, Any]=0.02				,     UpperCAmelCase_:  Tuple=0.0_01				,     **UpperCAmelCase_:  List[str]				,     ):







									'''simple docstring'''




									super().__init__(**UpperCAmelCase_					)

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

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



class 				__UpperCAmelCase		(_UpperCAmelCase   ):
			__snake_case    :				List[Any]									=							version.parse("1.11"   )







			@property
			def 							UpperCamelCase				(     self:  Tuple					):







									'''simple docstring'''




									return OrderedDict([("""pixel_values""", {0: """batch"""})]					)







			@property
			def 							UpperCamelCase				(     self:  Dict					):







									'''simple docstring'''




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







			@property
			def 							UpperCamelCase				(     self:  int					):







									'''simple docstring'''




									return 1E-4

