


import logging

from transformers.configuration_utils import PretrainedConfig


UpperCAmelCase_  							=				logging.getLogger(__name__)






class 					lowercase__ (			__lowerCamelCase       ):

   '''simple docstring'''


   a		:							List[Any]     	=	"masked_bert"




   def __init__(					self,	__magic_name__=30522,	__magic_name__=768,	__magic_name__=12,	__magic_name__=12,	__magic_name__=3072,	__magic_name__="gelu",	__magic_name__=0.1,	__magic_name__=0.1,	__magic_name__=512,	__magic_name__=2,	__magic_name__=0.02,	__magic_name__=1E-12,	__magic_name__=0,	__magic_name__="topK",	__magic_name__="constant",	__magic_name__=0.0,	**__magic_name__,	)				->   Optional[int]:






       """simple docstring"""
       super().__init__(pad_token_id=__magic_name__,	**__magic_name__							)

       UpperCamelCase__							:       List[Any]      =   vocab_size
       UpperCamelCase__							:       Tuple      =   hidden_size
       UpperCamelCase__							:       Optional[int]      =   num_hidden_layers
       UpperCamelCase__							:       List[Any]      =   num_attention_heads
       UpperCamelCase__							:       str      =   hidden_act
       UpperCamelCase__							:       Any      =   intermediate_size
       UpperCamelCase__							:       Dict      =   hidden_dropout_prob
       UpperCamelCase__							:       Union[str, Any]      =   attention_probs_dropout_prob
       UpperCamelCase__							:       Optional[int]      =   max_position_embeddings
       UpperCamelCase__							:       Tuple      =   type_vocab_size
       UpperCamelCase__							:       Union[str, Any]      =   initializer_range
       UpperCamelCase__							:       Optional[int]      =   layer_norm_eps
       UpperCamelCase__							:       Optional[Any]      =   pruning_method
       UpperCamelCase__							:       Optional[int]      =   mask_init
       UpperCamelCase__							:       Optional[Any]      =   mask_scale








def 	lowerCAmelCase_					(						__UpperCAmelCase:    dict   )   ->			set:
    UpperCamelCase__							:       int      =   set()
    # edges = list of graph's edges
    UpperCamelCase__							:       str      =   get_edges(__UpperCAmelCase   )

    # While there are still elements in edges list, take an arbitrary edge
    # (from_node, to_node) and add his extremity to chosen_vertices and then
    # remove all arcs adjacent to the from_node and to_node
    while edges:
        UpperCamelCase__     ,UpperCamelCase__							:       List[Any]      =   edges.pop()
        chosen_vertices.add(__UpperCAmelCase   )
        chosen_vertices.add(__UpperCAmelCase   )
        for edge in edges.copy():
            if from_node in edge or to_node in edge:
                edges.discard(__UpperCAmelCase   )
    return chosen_vertices




def 	lowerCAmelCase_					(						__UpperCAmelCase:    dict   )   ->			set:
    UpperCamelCase__							:       Optional[int]      =   set()
    for from_node, to_nodes in graph.items():
        for to_node in to_nodes:
            edges.add((from_node, to_node)   )
    return edges


if __name__ == "__main__":
  import doctest

  doctest.testmod()

  # graph = {0: [1, 3], 1: [0, 3], 2: [0, 3, 4], 3: [0, 1, 2], 4: [2, 3]}
  # print(f"Matching vertex cover:\n{matching_min_vertex_cover(graph)}")

