'''simple docstring'''




from __future__ import annotations


class    UpperCAmelCase__	:






   """simple docstring"""
   def __init__(self							,					_a					)     ->  None:
        lowercase_       :							List[str]  					=       vertices
        lowercase_       :							int  					=       [[0] * vertices for _ in range(_a					)]
   def 		_lowerCamelCase			(self							,					_a					)     ->  None:
        print('Vertex \t Distance from Source'					)
        for vertex in range(self.vertices					):
             print(_a							,					'\t\t'							,					distances_from_source[vertex]					)
   def 		_lowerCamelCase			(self							,					_a							,					_a					)     ->  int:
        lowercase_       :							Union[str, Any]  					=       1e7
        lowercase_       :							List[Any]  					=       0

        # Search not nearest vertex not in the shortest path tree
        for vertex in range(self.vertices					):
             if distances_from_source[vertex] < minimum and visited[vertex] is False:
                  lowercase_       :							List[str]  					=       distances_from_source[vertex]
                  lowercase_       :							Dict  					=       vertex
        return min_index





   def 		_lowerCamelCase			(self							,					_a					)     ->  None:
        lowercase_       :							int  					=       [int(1e7					)] * self.vertices  # distances from the source
        lowercase_       :							str  					=       0
        lowercase_       :							Any  					=       [False] * self.vertices

        for _ in range(self.vertices					):
             lowercase_       :							int  					=       self.minimum_distance(_a							,					_a					)
             lowercase_       :							Tuple  					=       True

             # Update dist value of the adjacent vertices
             # of the picked vertex only if the current
             # distance is greater than new distance and
             # the vertex in not in the shortest path tree
             for v in range(self.vertices					):
                  if (
                      self.graph[u][v] > 0
                      and visited[v] is False
                      and distances[v] > distances[u] + self.graph[u][v]
                  ):
                       lowercase_       :							Union[str, Any]  					=       distances[u] + self.graph[u][v]

        self.print_solution(_a					)


if __name__ == "__main__":
 _A										= Graph(9)
 _A										= [
     [0, 4, 0, 0, 0, 0, 0, 8, 0],
     [4, 0, 8, 0, 0, 0, 0, 1_1, 0],
     [0, 8, 0, 7, 0, 4, 0, 0, 2],
     [0, 0, 7, 0, 9, 1_4, 0, 0, 0],
     [0, 0, 0, 9, 0, 1_0, 0, 0, 0],
     [0, 0, 4, 1_4, 1_0, 0, 2, 0, 0],
     [0, 0, 0, 0, 0, 2, 0, 1, 6],
     [8, 1_1, 0, 0, 0, 0, 1, 0, 7],
     [0, 0, 2, 0, 0, 0, 6, 7, 0],
 ]
 graph.dijkstra(0)





'''simple docstring'''




_A										= '\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'

_A										= [{'type': 'code', 'content': INSTALL_CONTENT}]
_A										= {
    '{processor_class}': 'FakeProcessorClass',
    '{model_class}': 'FakeModelClass',
    '{object_class}': 'FakeObjectClass',
}




