





"""simple docstring"""






from ...configuration_utils import PretrainedConfig
from ...utils import logging


A	     =					logging.get_logger(__name__)

A	     =					{
    '''vinvino02/glpn-kitti''': '''https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.json''',
    # See all GLPN models at https://huggingface.co/models?filter=glpn
}




class 			__lowercase     (     _UpperCamelCase							):







     '''simple docstring'''




     __lowerCAmelCase					=					'''glpn'''







     def __init__(  self		,     _UpperCAmelCase=3		,     _UpperCAmelCase=4		,     _UpperCAmelCase=[2, 2, 2, 2]		,     _UpperCAmelCase=[8, 4, 2, 1]		,     _UpperCAmelCase=[32, 64, 160, 256]		,     _UpperCAmelCase=[7, 3, 3, 3]		,     _UpperCAmelCase=[4, 2, 2, 2]		,     _UpperCAmelCase=[1, 2, 5, 8]		,     _UpperCAmelCase=[4, 4, 4, 4]		,     _UpperCAmelCase="gelu"		,     _UpperCAmelCase=0.0		,     _UpperCAmelCase=0.0		,     _UpperCAmelCase=0.0_2		,     _UpperCAmelCase=0.1		,     _UpperCAmelCase=1e-6		,     _UpperCAmelCase=64		,     _UpperCAmelCase=10		,     _UpperCAmelCase=-1		,     **_UpperCAmelCase		,     ):
         super().__init__(**lowerCAmelCase__       )

         __a	:  Dict         =					num_channels
         __a	:  str         =					num_encoder_blocks
         __a	:  Tuple         =					depths
         __a	:  int         =					sr_ratios
         __a	:  Union[str, Any]         =					hidden_sizes
         __a	:  List[Any]         =					patch_sizes
         __a	:  Dict         =					strides
         __a	:  List[str]         =					mlp_ratios
         __a	:  int         =					num_attention_heads
         __a	:  List[str]         =					hidden_act
         __a	:  Dict         =					hidden_dropout_prob
         __a	:  Dict         =					attention_probs_dropout_prob
         __a	:  int         =					initializer_range
         __a	:  List[Any]         =					drop_path_rate
         __a	:  List[str]         =					layer_norm_eps
         __a	:  Any         =					decoder_hidden_size
         __a	:  Optional[int]         =					max_depth
         __a	:  List[Any]         =					head_in_index






"""simple docstring"""






from __future__ import annotations

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

A	     =					TypeVar('''T''')




class 			__lowercase     (     Generic[T]							):







					'''simple docstring'''




					__lowerCAmelCase					=					42  # Cache store of keys
					__lowerCAmelCase					=					42  # References of the keys in cache
					__lowerCAmelCase					=					10  # Maximum capacity of cache







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







					def 	_lowerCamelCase						(  self		,     _UpperCAmelCase       ):
									if x not in self.key_reference:
													if len(self.dq_store       ) == LRUCache._MAX_CAPACITY:
																	__a	:  int         =					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 	_lowerCamelCase						(  self       ):
									for k in self.dq_store:
													print(_UpperCAmelCase       )







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


if __name__ == "__main__":
		import doctest

		doctest.testmod()

		A	     =					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]"