
"""simple docstring"""
from ... import PretrainedConfig


lowercase_       :						Union[str, Any]     					=	{
    "sijunhe/nezha-cn-base": "https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json",
}
class 			UpperCamelCase      (							__UpperCAmelCase  ):
     A__      =			NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP
     A__      =			"""nezha"""
     def __init__(     self  ,     snake_case__=21128  ,     snake_case__=768  ,     snake_case__=12  ,     snake_case__=12  ,     snake_case__=3072  ,     snake_case__="gelu"  ,     snake_case__=0.1  ,     snake_case__=0.1  ,     snake_case__=512  ,     snake_case__=64  ,     snake_case__=2  ,     snake_case__=0.02  ,     snake_case__=1E-12  ,     snake_case__=0.1  ,     snake_case__=0  ,     snake_case__=2  ,     snake_case__=3  ,     snake_case__=True  ,     **snake_case__  ,     ):




       """simple docstring"""


       super().__init__(pad_token_id=lowerCAmelCase_  ,     bos_token_id=lowerCAmelCase_  ,     eos_token_id=lowerCAmelCase_  ,     **lowerCAmelCase_				)

       _SCREAMING_SNAKE_CASE   :				Dict							    = vocab_size
       _SCREAMING_SNAKE_CASE   :				Optional[Any]							    = hidden_size
       _SCREAMING_SNAKE_CASE   :				List[str]							    = num_hidden_layers
       _SCREAMING_SNAKE_CASE   :				Optional[Any]							    = num_attention_heads
       _SCREAMING_SNAKE_CASE   :				Union[str, Any]							    = hidden_act
       _SCREAMING_SNAKE_CASE   :				Union[str, Any]							    = intermediate_size
       _SCREAMING_SNAKE_CASE   :				Union[str, Any]							    = hidden_dropout_prob
       _SCREAMING_SNAKE_CASE   :				str							    = attention_probs_dropout_prob
       _SCREAMING_SNAKE_CASE   :				Any							    = max_position_embeddings
       _SCREAMING_SNAKE_CASE   :				Any							    = max_relative_position
       _SCREAMING_SNAKE_CASE   :				Union[str, Any]							    = type_vocab_size
       _SCREAMING_SNAKE_CASE   :				Tuple							    = initializer_range
       _SCREAMING_SNAKE_CASE   :				List[Any]							    = layer_norm_eps
       _SCREAMING_SNAKE_CASE   :				Tuple							    = classifier_dropout
       _SCREAMING_SNAKE_CASE   :				Dict							    = use_cache





"""simple docstring"""
def    _lowerCAmelCase    (     lowerCamelCase__							:							str,						lowerCamelCase__							:							str				)  ->    Union[str, Any]:
  print("\nThe shortest path matrix using Floyd Warshall algorithm\n"				)
  for i in range(lowerCamelCase__				):
    for j in range(lowerCamelCase__				):
      if dist[i][j] != float("inf"				):
        print(int(dist[i][j]				),						end="\t"				)
      else:
        print("INF",						end="\t"				)
    print()





def    _lowerCAmelCase    (     lowerCamelCase__							:							Dict,						lowerCamelCase__							:							Any				)  ->    List[str]:
  _SCREAMING_SNAKE_CASE   :				List[Any]							    = [[float("inf"				) for _ in range(lowerCamelCase__				)] for _ in range(lowerCamelCase__				)]

  for i in range(lowerCamelCase__				):
    for j in range(lowerCamelCase__				):
      _SCREAMING_SNAKE_CASE   :				List[Any]							    = graph[i][j]

      # check vertex k against all other vertices (i, j)
  for k in range(lowerCamelCase__				):
    # looping through rows of graph array
    for i in range(lowerCamelCase__				):
      # looping through columns of graph array
      for j in range(lowerCamelCase__				):
        if (
            dist[i][k] != float("inf"				)
            and dist[k][j] != float("inf"				)
            and dist[i][k] + dist[k][j] < dist[i][j]
        ):
          _SCREAMING_SNAKE_CASE   :				List[Any]							    = dist[i][k] + dist[k][j]

  _print_dist(lowerCamelCase__,						lowerCamelCase__				)
  return dist, v


if __name__ == "__main__":
      lowercase_       :						Tuple     					=	int(input('''Enter number of vertices: '''))
      lowercase_       :						List[Any]     					=	int(input('''Enter number of edges: '''))

      lowercase_       :						Optional[Any]     					=	[[float('''inf''') for i in range(v)] for j in range(v)]

      for i in range(v):
            lowercase_       :						Tuple     					=	0.0

            # src and dst are indices that must be within the array size graph[e][v]
            # failure to follow this will result in an error
      for i in range(e):
            print('''\nEdge ''', i + 1)
            lowercase_       :						str     					=	int(input('''Enter source:'''))
            lowercase_       :						Optional[Any]     					=	int(input('''Enter destination:'''))
            lowercase_       :						Union[str, Any]     					=	float(input('''Enter weight:'''))
            lowercase_       :						str     					=	weight

      floyd_warshall(graph, v)

      # Example Input
      # Enter number of vertices: 3
      # Enter number of edges: 2

      # # generated graph from vertex and edge inputs
      # [[inf, inf, inf], [inf, inf, inf], [inf, inf, inf]]
      # [[0.0, inf, inf], [inf, 0.0, inf], [inf, inf, 0.0]]

      # specify source, destination and weight for edge #1
      # Edge  1
      # Enter source:1
      # Enter destination:2
      # Enter weight:2

      # specify source, destination and weight for edge #2
      # Edge  2
      # Enter source:2
      # Enter destination:1
      # Enter weight:1

      # # Expected Output from the vertice, edge and src, dst, weight inputs!!
      # 0		INF	INF
      # INF	0	2
      # INF	1	0



