


'''simple docstring'''







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


A__:       Optional[int]          =			logging.get_logger(__name__)

A__:       List[Any]          =			{
    "microsoft/markuplm-base": "https://huggingface.co/microsoft/markuplm-base/resolve/main/config.json",
    "microsoft/markuplm-large": "https://huggingface.co/microsoft/markuplm-large/resolve/main/config.json",
}







class A__			(		a_ ):
      __UpperCamelCase			:    Optional[Any]      			=				'''markuplm'''






      def __init__(					self     :Any	,		SCREAMING_SNAKE_CASE     :List[str]=3_0_5_2_2	,		SCREAMING_SNAKE_CASE     :Optional[int]=7_6_8	,		SCREAMING_SNAKE_CASE     :int=1_2	,		SCREAMING_SNAKE_CASE     :List[str]=1_2	,		SCREAMING_SNAKE_CASE     :int=3_0_7_2	,		SCREAMING_SNAKE_CASE     :List[str]="gelu"	,		SCREAMING_SNAKE_CASE     :Dict=0.1	,		SCREAMING_SNAKE_CASE     :int=0.1	,		SCREAMING_SNAKE_CASE     :List[str]=5_1_2	,		SCREAMING_SNAKE_CASE     :Optional[Any]=2	,		SCREAMING_SNAKE_CASE     :List[Any]=0.02	,		SCREAMING_SNAKE_CASE     :Any=1e-12	,		SCREAMING_SNAKE_CASE     :Optional[int]=0	,		SCREAMING_SNAKE_CASE     :Union[str, Any]=0	,		SCREAMING_SNAKE_CASE     :Optional[Any]=2	,		SCREAMING_SNAKE_CASE     :str=2_5_6	,		SCREAMING_SNAKE_CASE     :List[Any]=1_0_2_4	,		SCREAMING_SNAKE_CASE     :Dict=2_1_6	,		SCREAMING_SNAKE_CASE     :Optional[Any]=1_0_0_1	,		SCREAMING_SNAKE_CASE     :str=3_2	,		SCREAMING_SNAKE_CASE     :Any=5_0	,		SCREAMING_SNAKE_CASE     :str="absolute"	,		SCREAMING_SNAKE_CASE     :List[str]=True	,		SCREAMING_SNAKE_CASE     :str=None	,		**SCREAMING_SNAKE_CASE     :Union[str, Any]	,		)			->   int:




             '''simple docstring'''
             super().__init__(
                 pad_token_id=_SCREAMING_SNAKE_CASE	,		bos_token_id=_SCREAMING_SNAKE_CASE	,		eos_token_id=_SCREAMING_SNAKE_CASE	,		**_SCREAMING_SNAKE_CASE	,		)
             _a       :					List[str]	   =vocab_size
             _a       :					Any	   =hidden_size
             _a       :					Any	   =num_hidden_layers
             _a       :					str	   =num_attention_heads
             _a       :					List[str]	   =hidden_act
             _a       :					Dict	   =intermediate_size
             _a       :					Any	   =hidden_dropout_prob
             _a       :					Optional[Any]	   =attention_probs_dropout_prob
             _a       :					Dict	   =max_position_embeddings
             _a       :					Dict	   =type_vocab_size
             _a       :					Any	   =initializer_range
             _a       :					str	   =layer_norm_eps
             _a       :					str	   =position_embedding_type
             _a       :					List[Any]	   =use_cache
             _a       :					str	   =classifier_dropout
             # additional properties
             _a       :					Union[str, Any]	   =max_depth
             _a       :					List[str]	   =max_xpath_tag_unit_embeddings
             _a       :					List[str]	   =max_xpath_subs_unit_embeddings
             _a       :					Any	   =tag_pad_id
             _a       :					List[Any]	   =subs_pad_id
             _a       :					Tuple	   =xpath_unit_hidden_size





'''simple docstring'''



def       snake_case   (	snake_case      : dict			) ->  set:


    """simple docstring"""


    lowerCAmelCase 						=							set()
    # edges = list of graph's edges
    lowerCAmelCase 						=							get_edges(snake_case			)

    # 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:
        lowerCAmelCase						,   lowerCAmelCase 						=							edges.pop()
        chosen_vertices.add(snake_case			)
        chosen_vertices.add(snake_case			)
        for edge in edges.copy():
            if from_node in edge or to_node in edge:
                edges.discard(snake_case			)
    return chosen_vertices


def       snake_case   (	snake_case      : dict			) ->  set:


    """simple docstring"""


    lowerCAmelCase 						=							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)}")





