import warnings

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


SCREAMING_SNAKE_CASE__		:					List[str]						=					logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__		:					Union[str, Any]						=					{
    "RUCAIBox/mvp": "https://huggingface.co/RUCAIBox/mvp/resolve/main/config.json",
}

class       snake_case					(      UpperCamelCase_						):
		lowercase_			=     'mvp'
		lowercase_			=     ['past_key_values']
		lowercase_			=     {'num_attention_heads': 'encoder_attention_heads', 'hidden_size': 'd_model'}




		def __init__(      self     :	List[Any]     , a_     :	Dict=5_0267     , a_     :	Tuple=1024     , a_     :	Dict=12     , a_     :	str=4096     , a_     :	List[Any]=16     , a_     :	Optional[Any]=12     , a_     :	Optional[int]=4096     , a_     :	str=16     , a_     :	int=0.0     , a_     :	Dict=0.0     , a_     :	List[Any]="gelu"     , a_     :	List[str]=1024     , a_     :	Any=0.1     , a_     :	List[Any]=0.0     , a_     :	Dict=0.0     , a_     :	Union[str, Any]=0.02     , a_     :	Union[str, Any]=0.0     , a_     :	Optional[Any]=False     , a_     :	Tuple=True     , a_     :	Optional[Any]=1     , a_     :	Dict=0     , a_     :	str=2     , a_     :	Dict=True     , a_     :	str=2     , a_     :	Optional[int]=2     , a_     :	Any=False     , a_     :	Optional[Any]=100     , a_     :	int=800     , **a_     :	Union[str, Any]     , )->       str:




							"""simple docstring"""
							SCREAMING_SNAKE_CASE__				:				Any			=		vocab_size
							SCREAMING_SNAKE_CASE__				:				List[str]			=		max_position_embeddings
							SCREAMING_SNAKE_CASE__				:				Optional[Any]			=		d_model
							SCREAMING_SNAKE_CASE__				:				List[str]			=		encoder_ffn_dim
							SCREAMING_SNAKE_CASE__				:				int			=		encoder_layers
							SCREAMING_SNAKE_CASE__				:				Dict			=		encoder_attention_heads
							SCREAMING_SNAKE_CASE__				:				List[Any]			=		decoder_ffn_dim
							SCREAMING_SNAKE_CASE__				:				Union[str, Any]			=		decoder_layers
							SCREAMING_SNAKE_CASE__				:				Union[str, Any]			=		decoder_attention_heads
							SCREAMING_SNAKE_CASE__				:				Tuple			=		dropout
							SCREAMING_SNAKE_CASE__				:				Optional[Any]			=		attention_dropout
							SCREAMING_SNAKE_CASE__				:				List[str]			=		activation_dropout
							SCREAMING_SNAKE_CASE__				:				Optional[Any]			=		activation_function
							SCREAMING_SNAKE_CASE__				:				List[str]			=		init_std
							SCREAMING_SNAKE_CASE__				:				Optional[int]			=		encoder_layerdrop
							SCREAMING_SNAKE_CASE__				:				Optional[Any]			=		decoder_layerdrop
							SCREAMING_SNAKE_CASE__				:				Optional[Any]			=		classifier_dropout
							SCREAMING_SNAKE_CASE__				:				List[Any]			=		use_cache
							SCREAMING_SNAKE_CASE__				:				List[Any]			=		encoder_layers
							SCREAMING_SNAKE_CASE__				:				List[Any]			=		scale_embedding  # scale factor will be sqrt(d_model) if True
							SCREAMING_SNAKE_CASE__				:				Union[str, Any]			=		use_prompt
							SCREAMING_SNAKE_CASE__				:				Any			=		prompt_length
							SCREAMING_SNAKE_CASE__				:				int			=		prompt_mid_dim

							super().__init__(
							    pad_token_id=a_     , bos_token_id=a_     , eos_token_id=a_     , is_encoder_decoder=a_     , decoder_start_token_id=a_     , forced_eos_token_id=a_     , **a_     , )

							if self.forced_bos_token_id is None and kwargs.get('force_bos_token_to_be_generated'     , a_				):
												SCREAMING_SNAKE_CASE__				:				Any			=		self.bos_token_id
												warnings.warn(
												    F'''Please make sure the config includes `forced_bos_token_id={self.bos_token_id}` in future versions. '''
												    'The config can simply be saved and uploaded again to be fixed.'				)




import heapq as hq
import math
from collections.abc import Iterator

class       snake_case					:




  def __init__(      self     :	str     , a_     :	str				)->       Any:




       """simple docstring"""
       SCREAMING_SNAKE_CASE__				:				List[str]			=		str(id_				)
       SCREAMING_SNAKE_CASE__				:				Any			=		None
       SCREAMING_SNAKE_CASE__				:				Optional[Any]			=		None
       SCREAMING_SNAKE_CASE__				:				Any			=		[]
       SCREAMING_SNAKE_CASE__				:				Union[str, Any]			=		{}  # {vertex:distance}




  def __lt__(      self     :	int     , a_     :	Tuple				)->       Union[str, Any]:




       """simple docstring"""
       return self.key < other.key




  def __repr__(      self     :	Any				)->       Dict:




       """simple docstring"""
       return self.id




  def 	__lowercase(      self     :	Optional[Any]     , a_     :	int				)->       List[str]:




       """simple docstring"""
       self.neighbors.append(a_				)




  def 	__lowercase(      self     :	int     , a_     :	int     , a_     :	Optional[Any]				)->       Any:




       """simple docstring"""
       SCREAMING_SNAKE_CASE__				:				Tuple			=		weight







def     _a				(      lowercase__  :			Optional[Any]     ,  lowercase__  :			Union[str, Any]     ,  lowercase__  :			Tuple     ,  lowercase__  :			Dict ):







     '''simple docstring'''


     graph[a - 1].add_neighbor(graph[b - 1] )
     graph[b - 1].add_neighbor(graph[a - 1] )
     # add the edges:
     graph[a - 1].add_edge(graph[b - 1]     ,  lowercase__ )
     graph[b - 1].add_edge(graph[a - 1]     ,  lowercase__ )







def     _a				(      lowercase__  :			list     ,  lowercase__  :			Vertex ):







     '''simple docstring'''


     SCREAMING_SNAKE_CASE__				:				Any			=		[]
     for u in graph:
          SCREAMING_SNAKE_CASE__				:				Dict			=		math.inf
          SCREAMING_SNAKE_CASE__				:				str			=		None
     SCREAMING_SNAKE_CASE__				:				List[str]			=		0
     SCREAMING_SNAKE_CASE__				:				int			=		graph[:]
     while q:
          SCREAMING_SNAKE_CASE__				:				Optional[Any]			=		min(lowercase__ )
          q.remove(lowercase__ )
          for v in u.neighbors:
               if (v in q) and (u.edges[v.id] < v.key):
                    SCREAMING_SNAKE_CASE__				:				int			=		u
                    SCREAMING_SNAKE_CASE__				:				Any			=		u.edges[v.id]
     for i in range(1     ,  len(lowercase__ ) ):
          a.append((int(graph[i].id ) + 1, int(graph[i].pi.id ) + 1) )
     return a







def     _a				(      lowercase__  :			list     ,  lowercase__  :			Vertex ):







     '''simple docstring'''


     for u in graph:
          SCREAMING_SNAKE_CASE__				:				List[str]			=		math.inf
          SCREAMING_SNAKE_CASE__				:				int			=		None
     SCREAMING_SNAKE_CASE__				:				Optional[Any]			=		0

     SCREAMING_SNAKE_CASE__				:				Tuple			=		list(lowercase__ )
     hq.heapify(lowercase__ )

     while h:
          SCREAMING_SNAKE_CASE__				:				Optional[int]			=		hq.heappop(lowercase__ )
          for v in u.neighbors:
               if (v in h) and (u.edges[v.id] < v.key):
                    SCREAMING_SNAKE_CASE__				:				List[str]			=		u
                    SCREAMING_SNAKE_CASE__				:				Dict			=		u.edges[v.id]
                    hq.heapify(lowercase__ )

     for i in range(1     ,  len(lowercase__ ) ):
          yield (int(graph[i].id ) + 1, int(graph[i].pi.id ) + 1)







def     _a				(      ):







     '''simple docstring'''




if __name__ == "__main__":
      import doctest

      doctest.testmod()



