



'''simple docstring'''





from __future__ import annotations

from collections.abc import Callable
from typing import Generic, TypeVar

lowercase_									=    TypeVar("T")
lowercase_									=    TypeVar("U")






class __A     (    Generic[T, U]		):



 '''simple docstring'''







 def __init__(self					,  A					,  A			)       ->	Optional[int]:


      """simple docstring"""



      _a           =    key
      _a           =    val
      _a           =    None
      _a           =    None



 def __repr__(self			)       ->	str:


      """simple docstring"""



      return (
          f'''Node: key: {self.key}, val: {self.val}, '''
          f'''has next: {bool(self.next			)}, has prev: {bool(self.prev			)}'''
      )






class __A     (    Generic[T, U]		):



 '''simple docstring'''







 def __init__(self			)       ->	None:


      """simple docstring"""



      _a           =    DoubleLinkedListNode(A					,  A			)
      _a           =    DoubleLinkedListNode(A					,  A			)
      _a    ,       _a           =    self.rear, self.head



 def __repr__(self			)       ->	str:


      """simple docstring"""



      _a           =    ['''DoubleLinkedList''']
      _a           =    self.head
      while node.next is not None:
           rep.append(str(A			)			)
           _a           =    node.next
      rep.append(str(self.rear			)			)
      return ",\n    ".join(A			)



 def    a__    (self					,  A			)       ->	None:


      """simple docstring"""



      _a           =    self.rear.prev

      # All nodes other than self.head are guaranteed to have non-None previous
      assert previous is not None

      _a           =    node
      _a           =    previous
      _a           =    node
      _a           =    self.rear



 def    a__    (self					,  A			)       ->	DoubleLinkedListNode[T, U] | None:


      """simple docstring"""



      if node.prev is None or node.next is None:
           return None

      _a           =    node.next
      _a           =    node.prev
      _a           =    None
      _a           =    None
      return node






class __A     (    Generic[T, U]		):



 '''simple docstring'''







 __lowerCamelCase       :			dict[Callable[[T], U], LRUCache[T, U]]		=			{}



 def __init__(self					,  A			)       ->	List[Any]:


      """simple docstring"""



      _a           =    DoubleLinkedList()
      _a           =    capacity
      _a           =    0
      _a           =    0
      _a           =    0
      _a           =    {}



 def __repr__(self			)       ->	str:


      """simple docstring"""



      return (
          f'''CacheInfo(hits={self.hits}, misses={self.miss}, '''
          f'''capacity={self.capacity}, current size={self.num_keys})'''
      )



 def __contains__(self					,  A			)       ->	bool:


      """simple docstring"""



      return key in self.cache



 def    a__    (self					,  A			)       ->	U | None:


      """simple docstring"""



      if key in self.cache:
           self.hits += 1
           _a           =    self.cache[key]
           _a           =    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(A			)
           return node.val
      self.miss += 1
      return None



 def    a__    (self					,  A					,  A			)       ->	None:


      """simple docstring"""



      if key not in self.cache:
           if self.num_keys >= self.capacity:
                # delete first node (oldest) when over capacity
                _a           =    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(A			) is not None
                )  # node guaranteed to be in list assert node.key is not None

                del self.cache[first_node.key]
                self.num_keys -= 1
           _a           =    DoubleLinkedListNode(A					,  A			)
           self.list.add(self.cache[key]			)
           self.num_keys += 1

      else:
           # bump node to the end of the list, update value
           _a           =    self.list.remove(self.cache[key]			)
           assert node is not None  # node guaranteed to be in list
           _a           =    value
           self.list.add(A			)



 @classmethod
 def    a__    (cls					,  A = 128			)       ->	Callable[[Callable[[T], U]], Callable[..., U]]:


      """simple docstring"""



      def cache_decorator_inner(A			) -> Callable[..., U]:
           def cache_decorator_wrapper(*A			) -> U:
                if func not in cls.decorator_function_to_instance_map:
                     _a           =    LRUCache(A			)

                _a           =    cls.decorator_function_to_instance_map[func].get(args[0]			)
                if result is None:
                     _a           =    func(*A			)
                     cls.decorator_function_to_instance_map[func].put(args[0]					,  A			)
                return result

           def cache_info() -> LRUCache[T, U]:
                return cls.decorator_function_to_instance_map[func]

           setattr(A					,  '''cache_info'''					,  A			)  # noqa: B010

           return cache_decorator_wrapper

      return cache_decorator_inner


if __name__ == "__main__":
  import doctest

  doctest.testmod()








'''simple docstring'''





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


lowercase_									=    {
    "configuration_blip": [
        "BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "BlipConfig",
        "BlipTextConfig",
        "BlipVisionConfig",
    ],
    "processing_blip": ["BlipProcessor"],
}

try:
  if not is_vision_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase_									=    ["BlipImageProcessor"]


try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase_									=    [
      "BLIP_PRETRAINED_MODEL_ARCHIVE_LIST",
      "BlipModel",
      "BlipPreTrainedModel",
      "BlipForConditionalGeneration",
      "BlipForQuestionAnswering",
      "BlipVisionModel",
      "BlipTextModel",
      "BlipForImageTextRetrieval",
  ]

try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase_									=    [
      "TF_BLIP_PRETRAINED_MODEL_ARCHIVE_LIST",
      "TFBlipModel",
      "TFBlipPreTrainedModel",
      "TFBlipForConditionalGeneration",
      "TFBlipForQuestionAnswering",
      "TFBlipVisionModel",
      "TFBlipTextModel",
      "TFBlipForImageTextRetrieval",
  ]

if TYPE_CHECKING:
  from .configuration_blip import BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP, BlipConfig, BlipTextConfig, BlipVisionConfig
  from .processing_blip import BlipProcessor

  try:
    if not is_vision_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .image_processing_blip import BlipImageProcessor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_blip import (
        BLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
        BlipForConditionalGeneration,
        BlipForImageTextRetrieval,
        BlipForQuestionAnswering,
        BlipModel,
        BlipPreTrainedModel,
        BlipTextModel,
        BlipVisionModel,
    )

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_blip import (
        TF_BLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
        TFBlipForConditionalGeneration,
        TFBlipForImageTextRetrieval,
        TFBlipForQuestionAnswering,
        TFBlipModel,
        TFBlipPreTrainedModel,
        TFBlipTextModel,
        TFBlipVisionModel,
    )

else:
  import sys

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



