

from __future__ import annotations

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

lowerCAmelCase__								=		TypeVar("""T""")







class 	lowercase    (				Generic[T]							):


		"""simple docstring"""




		a__					       =  42  # Cache store of keys
		a__					       =  42  # References of the keys in cache
		a__					       =  1_0  # Maximum capacity of cache


		def __init__(				self	,       __snake_case):
			_UpperCamelCase   :		str			=						deque()
			_UpperCamelCase   :		str			=						set()
			if not n:
				_UpperCamelCase   :		Union[str, Any]			=						sys.maxsize
			elif n < 0:
				raise ValueError('n should be an integer greater than 0.')
			else:
				_UpperCamelCase   :		Tuple			=						n


		def 		A__					(				self	,       __snake_case):
			if x not in self.key_reference:
				if len(self.dq_store) == LRUCache._MAX_CAPACITY:
					_UpperCamelCase   :		Any			=						self.dq_store.pop()
					self.key_reference.remove(__snake_case)
			else:
				self.dq_store.remove(__snake_case)

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


		def 		A__					(				self):
			for k in self.dq_store:
				print(__snake_case)






		def __repr__(				self):
			return f'''LRUCache({self._MAX_CAPACITY}) => {list(self.dq_store)}'''


if __name__ == "__main__":
							import doctest

							doctest.testmod()

							lowerCAmelCase__								=		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 typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


lowerCAmelCase__								=		{
    """configuration_canine""": ["""CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """CanineConfig"""],
    """tokenization_canine""": ["""CanineTokenizer"""],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowerCAmelCase__								=		[
							    """CANINE_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """CanineForMultipleChoice""",
							    """CanineForQuestionAnswering""",
							    """CanineForSequenceClassification""",
							    """CanineForTokenClassification""",
							    """CanineLayer""",
							    """CanineModel""",
							    """CaninePreTrainedModel""",
							    """load_tf_weights_in_canine""",
							]


if TYPE_CHECKING:
							from .configuration_canine import CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP, CanineConfig
							from .tokenization_canine import CanineTokenizer

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_canine import (
														    CANINE_PRETRAINED_MODEL_ARCHIVE_LIST,
														    CanineForMultipleChoice,
														    CanineForQuestionAnswering,
														    CanineForSequenceClassification,
														    CanineForTokenClassification,
														    CanineLayer,
														    CanineModel,
														    CaninePreTrainedModel,
														    load_tf_weights_in_canine,
														)


else:
							import sys

							lowerCAmelCase__								=		_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)




