code: 
  
  
  '''simple docstring'''
  
  
  
  from __future__ import annotations
  
  from collections.abc import Callable
  from typing import Generic, TypeVar
  
  A__	:      Dict				=						TypeVar("""T""")
  A__	:      int				=						TypeVar("""U""")
  
  
  
  
  
  class      UpperCAmelCase_						(Generic[T, U]						):
  
  
  
  
  
      """simple docstring"""
  
  
  
  
  
  
      def __init__(							self    ,  SCREAMING_SNAKE_CASE_    ,  SCREAMING_SNAKE_CASE_			)       ->  Union[str, Any]:
           __lowerCamelCase     :			List[Any]              =	key
           __lowerCamelCase     :			str              =	val
           __lowerCamelCase     :			int              =	0
           __lowerCamelCase     :			DoubleLinkedListNode[T, U] | None              =	None
           __lowerCamelCase     :			DoubleLinkedListNode[T, U] | None              =	None
  
  
  
  
  
  
  
      def __repr__(							self			)       ->  str:
           return "Node: key: {}, val: {}, freq: {}, has next: {}, has prev: {}".format(
               self.key    ,  self.val    ,  self.freq    ,  self.next is not None    ,  self.prev is not None			)
  
  
  
  
  
  
  
  class      UpperCAmelCase_						(Generic[T, U]						):
  
  
  
  
  
      """simple docstring"""
  
  
  
  
  
  
      def __init__(							self			)       ->  None:
           __lowerCamelCase     :			DoubleLinkedListNode[T, U]              =	DoubleLinkedListNode(SCREAMING_SNAKE_CASE_    ,  SCREAMING_SNAKE_CASE_			)
           __lowerCamelCase     :			DoubleLinkedListNode[T, U]              =	DoubleLinkedListNode(SCREAMING_SNAKE_CASE_    ,  SCREAMING_SNAKE_CASE_			)
           __lowerCamelCase       , __lowerCamelCase     :			int              =	self.rear, self.head
  
  
  
  
  
  
  
      def __repr__(							self			)       ->  str:
           __lowerCamelCase     :			Dict              =	['DoubleLinkedList']
           __lowerCamelCase     :			Union[str, Any]              =	self.head
           while node.next is not None:
                rep.append(str(SCREAMING_SNAKE_CASE_			)			)
                __lowerCamelCase     :			str              =	node.next
           rep.append(str(self.rear			)			)
           return ",\n    ".join(SCREAMING_SNAKE_CASE_			)
  
  
  
  
  
  
  
      def    lowercase_       (							self    ,  SCREAMING_SNAKE_CASE_			)       ->  None:
           __lowerCamelCase     :			Tuple              =	self.rear.prev
  
           # All nodes other than self.head are guaranteed to have non-None previous
           assert previous is not None
  
           __lowerCamelCase     :			List[str]              =	node
           __lowerCamelCase     :			Optional[int]              =	previous
           __lowerCamelCase     :			int              =	node
           __lowerCamelCase     :			List[str]              =	self.rear
           node.freq += 1
           self._position_node(SCREAMING_SNAKE_CASE_			)
  
  
  
  
  
  
  
      def    lowercase_       (							self    ,  SCREAMING_SNAKE_CASE_			)       ->  None:
  
           while node.prev is not None and node.prev.freq > node.freq:
                # swap node with previous node
                __lowerCamelCase     :			int              =	node.prev
  
                __lowerCamelCase     :			str              =	previous_node.prev
                __lowerCamelCase     :			Any              =	node.prev
                __lowerCamelCase     :			str              =	previous_node
                __lowerCamelCase     :			Dict              =	node
  
  
  
  
  
  
  
      def    lowercase_       (							self    ,  SCREAMING_SNAKE_CASE_			)       ->  DoubleLinkedListNode[T, U] | None:
  
           if node.prev is None or node.next is None:
                return None
  
           __lowerCamelCase     :			Tuple              =	node.next
           __lowerCamelCase     :			Any              =	node.prev
           __lowerCamelCase     :			List[str]              =	None
           __lowerCamelCase     :			Dict              =	None
           return node
  
  
  
  
  
  
  
  class      UpperCAmelCase_						(Generic[T, U]						):
  
  
  
  
  
      """simple docstring"""
  
  
  
  
  
  
      lowerCamelCase						:      dict[Callable[[T], U], LFUCache[T, U]]							  =    {}
  
  
  
  
  
  
  
      def __init__(							self    ,  SCREAMING_SNAKE_CASE_			)       ->  Any:
           __lowerCamelCase     :			DoubleLinkedList[T, U]              =	DoubleLinkedList()
           __lowerCamelCase     :			int              =	capacity
           __lowerCamelCase     :			Union[str, Any]              =	0
           __lowerCamelCase     :			Dict              =	0
           __lowerCamelCase     :			Optional[int]              =	0
           __lowerCamelCase     :			dict[T, DoubleLinkedListNode[T, U]]              =	{}
  
  
  
  
  
  
  
      def __repr__(							self			)       ->  str:
           return (
               f'CacheInfo(hits={self.hits}, misses={self.miss}, '
               f'capacity={self.capacity}, current_size={self.num_keys})'
           )
  
  
  
  
  
  
  
      def __contains__(							self    ,  SCREAMING_SNAKE_CASE_			)       ->  bool:
           return key in self.cache
  
  
  
  
  
  
  
      def    lowercase_       (							self    ,  SCREAMING_SNAKE_CASE_			)       ->  U | None:
  
           if key in self.cache:
                self.hits += 1
                __lowerCamelCase     :			DoubleLinkedListNode[T, U]              =	self.cache[key]
                __lowerCamelCase     :			List[Any]              =	self.list.remove(self.cache[key]			)
                assert node == value_node
  
                # node is guaranteed not None because it is in self.cache
                assert node is not None
                self.list.add(SCREAMING_SNAKE_CASE_			)
                return node.val
           self.miss += 1
           return None
  
  
  
  
  
  
  
      def    lowercase_       (							self    ,  SCREAMING_SNAKE_CASE_    ,  SCREAMING_SNAKE_CASE_			)       ->  None:
  
           if key not in self.cache:
                if self.num_keys >= self.capacity:
                     # delete first node when over capacity
                     __lowerCamelCase     :			Any              =	self.list.head.next
  
                     # guaranteed to have a non-None first node when num_keys > 0
                     # explain to type checker via assertions
                     assert first_node is not None
                     assert first_node.key is not None
                     assert self.list.remove(SCREAMING_SNAKE_CASE_			) is not None
                     # first_node guaranteed to be in list
  
                     del self.cache[first_node.key]
                     self.num_keys -= 1
                __lowerCamelCase     :			Optional[int]              =	DoubleLinkedListNode(SCREAMING_SNAKE_CASE_    ,  SCREAMING_SNAKE_CASE_			)
                self.list.add(self.cache[key]			)
                self.num_keys += 1
  
           else:
                __lowerCamelCase     :			Optional[int]              =	self.list.remove(self.cache[key]			)
                assert node is not None  # node guaranteed to be in list
                __lowerCamelCase     :			List[str]              =	value
                self.list.add(SCREAMING_SNAKE_CASE_			)
  
  
  
  
  
  
  
      @classmethod
      def    lowercase_       (							cls    ,  SCREAMING_SNAKE_CASE_ = 1_28			)       ->  Callable[[Callable[[T], U]], Callable[..., U]]:
  
           def cache_decorator_inner(SCREAMING_SNAKE_CASE_			) -> Callable[..., U]:
                def cache_decorator_wrapper(*SCREAMING_SNAKE_CASE_			) -> U:
                     if func not in cls.decorator_function_to_instance_map:
                          __lowerCamelCase     :			int              =	LFUCache(SCREAMING_SNAKE_CASE_			)
  
                     __lowerCamelCase     :			Union[str, Any]              =	cls.decorator_function_to_instance_map[func].get(args[0]			)
                     if result is None:
                          __lowerCamelCase     :			str              =	func(*SCREAMING_SNAKE_CASE_			)
                          cls.decorator_function_to_instance_map[func].put(args[0]    ,  SCREAMING_SNAKE_CASE_			)
                     return result
  
                def cache_info() -> LFUCache[T, U]:
                     return cls.decorator_function_to_instance_map[func]
  
                setattr(SCREAMING_SNAKE_CASE_    ,  'cache_info'    ,  SCREAMING_SNAKE_CASE_			)  # noqa: B010
  
                return cache_decorator_wrapper
  
           return cache_decorator_inner
  
  
  if __name__ == "__main__":
        import doctest
  
        doctest.testmod()
  
  
  
  
  
  
  
style_context: 
  
  
  '''simple docstring'''
  
  
  
  from typing import TYPE_CHECKING
  
  from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_torch_available
  
  
  A__	:      Optional[Any]				=						{
      """configuration_xlm_prophetnet""": ["""XLM_PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP""", """XLMProphetNetConfig"""],
  }
  
  try:
        if not is_sentencepiece_available():
              raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
        pass
  else:
        A__	:      List[Any]				=						["""XLMProphetNetTokenizer"""]
  
  try:
        if not is_torch_available():
              raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
        pass
  else:
        A__	:      Optional[Any]				=						[
            """XLM_PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST""",
            """XLMProphetNetDecoder""",
            """XLMProphetNetEncoder""",
            """XLMProphetNetForCausalLM""",
            """XLMProphetNetForConditionalGeneration""",
            """XLMProphetNetModel""",
            """XLMProphetNetPreTrainedModel""",
        ]
  
  
  if TYPE_CHECKING:
        from .configuration_xlm_prophetnet import XLM_PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP, XLMProphetNetConfig
  
        try:
              if not is_sentencepiece_available():
                    raise OptionalDependencyNotAvailable()
        except OptionalDependencyNotAvailable:
              pass
        else:
              from .tokenization_xlm_prophetnet import XLMProphetNetTokenizer
  
        try:
              if not is_torch_available():
                    raise OptionalDependencyNotAvailable()
        except OptionalDependencyNotAvailable:
              pass
        else:
              from .modeling_xlm_prophetnet import (
                  XLM_PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST,
                  XLMProphetNetDecoder,
                  XLMProphetNetEncoder,
                  XLMProphetNetForCausalLM,
                  XLMProphetNetForConditionalGeneration,
                  XLMProphetNetModel,
                  XLMProphetNetPreTrainedModel,
              )
  
  else:
        import sys
  
        A__	:      List[str]				=						_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
  
  
  
  
  
  
  