



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


__lowerCamelCase  :				Any					=					logging.get_logger(__name__)

# TODO: upload to AWS
__lowerCamelCase  :				Any					=					{
    "yjernite/retribert-base-uncased": (
        "https://huggingface.co/yjernite/retribert-base-uncased/resolve/main/config.json"
    ),
}





class 			__magic_name__ (				lowerCAmelCase__    ):
		lowercase   :							Union[str, Any]        ="""retribert"""






		def __init__(    self   :  Dict					,		UpperCamelCase__   :  Union[str, Any]=3_05_22					,		UpperCamelCase__   :  Union[str, Any]=7_68					,		UpperCamelCase__   :  List[Any]=8					,		UpperCamelCase__   :  str=12					,		UpperCamelCase__   :  List[Any]=30_72					,		UpperCamelCase__   :  Any="gelu"					,		UpperCamelCase__   :  List[Any]=0.1					,		UpperCamelCase__   :  Tuple=0.1					,		UpperCamelCase__   :  Tuple=5_12					,		UpperCamelCase__   :  Dict=2					,		UpperCamelCase__   :  List[Any]=0.02					,		UpperCamelCase__   :  Tuple=1e-1_2					,		UpperCamelCase__   :  Union[str, Any]=True					,		UpperCamelCase__   :  Union[str, Any]=1_28					,		UpperCamelCase__   :  Optional[Any]=0					,		**UpperCamelCase__   :  Optional[Any]					,		)					->       Optional[Any]:
								'''simple docstring'''







								super().__init__(pad_token_id=__a					,		**__a   )

								UpperCAmelCase								=  vocab_size
								UpperCAmelCase								=  hidden_size
								UpperCAmelCase								=  num_hidden_layers
								UpperCAmelCase								=  num_attention_heads
								UpperCAmelCase								=  hidden_act
								UpperCAmelCase								=  intermediate_size
								UpperCAmelCase								=  hidden_dropout_prob
								UpperCAmelCase								=  attention_probs_dropout_prob
								UpperCAmelCase								=  max_position_embeddings
								UpperCAmelCase								=  type_vocab_size
								UpperCAmelCase								=  initializer_range
								UpperCAmelCase								=  layer_norm_eps
								UpperCAmelCase								=  share_encoders
								UpperCAmelCase								=  projection_dim







"""simple docstring"""


from __future__ import annotations
class     _UpperCamelCase    :
							'''simple docstring'''







							def __init__(	self       ,  __a=None      ):
										__lowerCAmelCase							       =     data
										__lowerCAmelCase							       =     None



							def __repr__(	self      ):
										__lowerCAmelCase							       =     []
										__lowerCAmelCase							       =     self
										while temp:
													string_rep.append(f"{temp.data}"      )
													__lowerCAmelCase							       =     temp.next
										return "->".join(__a      )


def _lowerCamelCase      (						_UpperCamelCase ):

			'''simple docstring'''




			if not elements_list:
						raise Exception("The Elements List is empty" )

			__lowerCAmelCase							       =     __lowerCAmelCase							       =     Node(elements_list[0] )
			for i in range(1       ,					len(_UpperCamelCase ) ):
						__lowerCAmelCase							       =     Node(elements_list[i] )
						__lowerCAmelCase							       =     current.next
			return head


def _lowerCamelCase      (						_UpperCamelCase ):

			'''simple docstring'''




			if head_node is not None and isinstance(_UpperCamelCase       ,					_UpperCamelCase ):
						print_reverse(head_node.next )
						print(head_node.data )


def _lowerCamelCase      (						):

			'''simple docstring'''




			from doctest import testmod

			testmod()

			__lowerCAmelCase							       =     make_linked_list([14, 52, 14, 12, 43] )
			print("Linked List:" )
			print(_UpperCamelCase )
			print("Elements in Reverse:" )
			print_reverse(_UpperCamelCase )


if __name__ == "__main__":
	main()




