
"""simple docstring"""

def 				A		(							snake_case :Optional[int]							,   snake_case :int						) ->      str:
 print('\nVertex Distance'						)
 for i in range(UpperCamelCase__						):
  if dist[i] != float('inf'						):
   print(UpperCamelCase__							,   '\t'							,   int(dist[i]						)							,   end='\t'						)
  else:
   print(UpperCamelCase__							,   '\t'							,   'INF'							,   end='\t'						)
  print()






def 				A		(							snake_case :List[Any]							,   snake_case :Optional[int]							,   snake_case :int						) ->      Union[str, Any]:
 __UpperCamelCase							    =			float('inf'						)
 __UpperCamelCase							    =			-1
 for i in range(UpperCamelCase__						):
  if (not vset[i]) and mdist[i] < min_val:
   __UpperCamelCase							    =			i
   __UpperCamelCase							    =			mdist[i]
 return min_ind






def 				A		(							snake_case :Any							,   snake_case :Dict							,   snake_case :str						) ->      List[Any]:
 __UpperCamelCase							    =			[float('inf'						) for _ in range(UpperCamelCase__						)]
 __UpperCamelCase							    =			[False for _ in range(UpperCamelCase__						)]
 __UpperCamelCase							    =			0.0

 for _ in range(v - 1						):
  __UpperCamelCase							    =			min_dist(UpperCamelCase__							,   UpperCamelCase__							,   UpperCamelCase__						)
  __UpperCamelCase							    =			True

  for i in range(UpperCamelCase__						):
   if (
       (not vset[i])
       and graph[u][i] != float('inf'						)
       and mdist[u] + graph[u][i] < mdist[i]
   ):
    __UpperCamelCase							    =			mdist[u] + graph[u][i]

 print_dist(UpperCamelCase__							,   UpperCamelCase__						)


if __name__ == "__main__":
      UpperCamelCase      :							Tuple          =					int(input("Enter number of vertices: ").strip())
      UpperCamelCase      :							Union[str, Any]          =					int(input("Enter number of edges: ").strip())

      UpperCamelCase      :							str          =					[[float("inf") for i in range(V)] for j in range(V)]

      for i in range(V):
            UpperCamelCase      :							Tuple          =					0.0

      for i in range(E):
            print("\nEdge ", i + 1)
            UpperCamelCase      :							Optional[int]          =					int(input("Enter source:").strip())
            UpperCamelCase      :							Union[str, Any]          =					int(input("Enter destination:").strip())
            UpperCamelCase      :							Optional[int]          =					float(input("Enter weight:").strip())
            UpperCamelCase      :							Tuple          =					weight

      UpperCamelCase      :							Optional[int]          =					int(input("\nEnter shortest path source:").strip())
      dijkstra(graph, V, gsrc)




"""simple docstring"""




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


__lowerCamelCase									=	logging.get_logger(__name__)

__lowerCamelCase									=	{
    "dandelin/vilt-b32-mlm": "https://huggingface.co/dandelin/vilt-b32-mlm/blob/main/config.json"
}
class      UpperCamelCase__(      __A			):
						lowerCAmelCase__	:    str    				=		'vilt'





						def __init__(							self		,__UpperCAmelCase=3_05_22		,__UpperCAmelCase=2		,__UpperCAmelCase=2		,__UpperCAmelCase=40		,__UpperCAmelCase=7_68		,__UpperCAmelCase=12		,__UpperCAmelCase=12		,__UpperCAmelCase=30_72		,__UpperCAmelCase="gelu"		,__UpperCAmelCase=0.0		,__UpperCAmelCase=0.0		,__UpperCAmelCase=0.0_2		,__UpperCAmelCase=1e-12		,__UpperCAmelCase=3_84		,__UpperCAmelCase=32		,__UpperCAmelCase=3		,__UpperCAmelCase=True		,__UpperCAmelCase=-1		,__UpperCAmelCase=False		,__UpperCAmelCase=-1		,**__UpperCAmelCase		,)       ->					Tuple:
													super().__init__(tie_word_embeddings=__UpperCAmelCase		,**__UpperCAmelCase  )

													A__						  =				vocab_size
													A__						  =				type_vocab_size
													A__						  =				modality_type_vocab_size
													A__						  =				max_position_embeddings

													A__						  =				hidden_size
													A__						  =				num_hidden_layers
													A__						  =				num_attention_heads
													A__						  =				intermediate_size
													A__						  =				hidden_act
													A__						  =				hidden_dropout_prob
													A__						  =				attention_probs_dropout_prob
													A__						  =				initializer_range
													A__						  =				layer_norm_eps

													A__						  =				image_size
													A__						  =				patch_size
													A__						  =				num_channels
													A__						  =				qkv_bias
													A__						  =				max_image_length
													A__						  =				num_images





