



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


UpperCAmelCase_							:      Tuple      =  logging.get_logger(__name__)

UpperCAmelCase_							:      Tuple      =  {
    "unc-nlp/lxmert-base-uncased": "https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/config.json",
}






class      UpperCamelCase    (						_UpperCAmelCase     ):
	lowerCAmelCase	:   Optional[Any]				=	"""lxmert"""
	lowerCAmelCase	:   Dict				=	{}



	def __init__(       self			,	UpperCAmelCase__=30_522			,	UpperCAmelCase__=768			,	UpperCAmelCase__=12			,	UpperCAmelCase__=9_500			,	UpperCAmelCase__=1_600			,	UpperCAmelCase__=400			,	UpperCAmelCase__=3_072			,	UpperCAmelCase__="gelu"			,	UpperCAmelCase__=0.1			,	UpperCAmelCase__=0.1			,	UpperCAmelCase__=512			,	UpperCAmelCase__=2			,	UpperCAmelCase__=0.02			,	UpperCAmelCase__=1e-1_2			,	UpperCAmelCase__=9			,	UpperCAmelCase__=5			,	UpperCAmelCase__=5			,	UpperCAmelCase__=2_048			,	UpperCAmelCase__=4			,	UpperCAmelCase__=6.67			,	UpperCAmelCase__=True			,	UpperCAmelCase__=True			,	UpperCAmelCase__=True			,	UpperCAmelCase__=True			,	UpperCAmelCase__=True			,	UpperCAmelCase__=True			,	UpperCAmelCase__=True			,	**UpperCAmelCase__			,	):
							A__							=       vocab_size
							A__							=       hidden_size
							A__							=       num_attention_heads
							A__							=       hidden_act
							A__							=       intermediate_size
							A__							=       hidden_dropout_prob
							A__							=       attention_probs_dropout_prob
							A__							=       max_position_embeddings
							A__							=       type_vocab_size
							A__							=       initializer_range
							A__							=       layer_norm_eps
							A__							=       num_qa_labels
							A__							=       num_object_labels
							A__							=       num_attr_labels
							A__							=       l_layers
							A__							=       x_layers
							A__							=       r_layers
							A__							=       visual_feat_dim
							A__							=       visual_pos_dim
							A__							=       visual_loss_normalizer
							A__							=       task_matched
							A__							=       task_mask_lm
							A__							=       task_obj_predict
							A__							=       task_qa
							A__							=       visual_obj_loss
							A__							=       visual_attr_loss
							A__							=       visual_feat_loss
							A__							=       {"vision": r_layers, "cross_encoder": x_layers, "language": l_layers}
							super().__init__(**UpperCAmelCase__		)










from __future__ import annotations






class      UpperCamelCase    :



	def __init__(       self			,	UpperCAmelCase__=None		):
							A__							=       data
							A__							=       None



	def __repr__(       self		):
							A__							=       []
							A__							=       self
							while temp:
													string_rep.append(F"""{temp.data}"""		)
													A__							=       temp.next
							return "->".join(UpperCAmelCase__		)





def  UpperCamelCase						(       _A			:				list    )->       Dict:





						"""simple docstring"""





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

						A__							=       A__							=       Node(elements_list[0]    )
						for i in range(1			,							len(_A    )    ):
												A__							=       Node(elements_list[i]    )
												A__							=       current.next
						return head
def  UpperCamelCase						(       _A			:				Node    )->       None:





						"""simple docstring"""





						if head_node is not None and isinstance(_A			,							_A    ):
												print_reverse(head_node.next    )
												print(head_node.data    )
def  UpperCamelCase						(       )->       Tuple:





						"""simple docstring"""





						from doctest import testmod

						testmod()

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


if __name__ == "__main__":
						main()





