

'''simple docstring'''




from __future__ import annotations

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

_lowerCAmelCase         =						TypeVar("T")






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



 def __init__(   self		:   List[str]			,				a__		:   int      ):
      __magic_name__						       =    deque()
      __magic_name__						       =    set()
      if not n:
           __magic_name__						       =    sys.maxsize
      elif n < 0:
           raise ValueError('''n should be an integer greater than 0.'''      )
      else:
           __magic_name__						       =    n



 def 			snake_case__  (   self		:   Optional[Any]			,				a__		:   T      ):
      if x not in self.key_reference:
           if len(self.dq_store      ) == LRUCache._MAX_CAPACITY:
                __magic_name__						       =    self.dq_store.pop()
                self.key_reference.remove(__a      )
      else:
           self.dq_store.remove(__a      )

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



 def 			snake_case__  (   self		:   Optional[int]      ):
      for k in self.dq_store:
           print(__a      )



 def __repr__(   self		:   List[Any]      ):
      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]"









'''simple docstring'''




from typing import TYPE_CHECKING

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


_lowerCAmelCase         =						{"configuration_glpn": ["GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP", "GLPNConfig"]}

try:
      if not is_vision_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      _lowerCAmelCase         =						["GLPNFeatureExtractor"]
      _lowerCAmelCase         =						["GLPNImageProcessor"]

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      _lowerCAmelCase         =						[
          "GLPN_PRETRAINED_MODEL_ARCHIVE_LIST",
          "GLPNForDepthEstimation",
          "GLPNLayer",
          "GLPNModel",
          "GLPNPreTrainedModel",
      ]


if TYPE_CHECKING:
      from .configuration_glpn import GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP, GLPNConfig

      try:
            if not is_vision_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .feature_extraction_glpn import GLPNFeatureExtractor
            from .image_processing_glpn import GLPNImageProcessor

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_glpn import (
                GLPN_PRETRAINED_MODEL_ARCHIVE_LIST,
                GLPNForDepthEstimation,
                GLPNLayer,
                GLPNModel,
                GLPNPreTrainedModel,
            )


else:
      import sys

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






