


from __future__ import annotations


def      a	(							SCREAMING_SNAKE_CASE_      :		list[float]							,			SCREAMING_SNAKE_CASE_      :		Optional[Any]       ):






       """simple docstring"""





       print(F"""Vertex\tShortest Distance from vertex {src}"""       )
       for i, d in enumerate(SCREAMING_SNAKE_CASE_       ):
              print(F"""{i}\t\t{d}"""       )


def      a	(							SCREAMING_SNAKE_CASE_      :		list[dict[str, int]]							,			SCREAMING_SNAKE_CASE_      :		list[float]							,			SCREAMING_SNAKE_CASE_      :		int       ):






       """simple docstring"""





       for j in range(SCREAMING_SNAKE_CASE_       ):
              UpperCamelCase	, UpperCamelCase	, UpperCamelCase    :	Optional[int]   	=		(graph[j][k] for k in ['''src''', '''dst''', '''weight'''])
              if distance[u] != float('''inf'''       ) and distance[u] + w < distance[v]:
                     return True
       return False


def      a	(							SCREAMING_SNAKE_CASE_      :		list[dict[str, int]]							,			SCREAMING_SNAKE_CASE_      :		int							,			SCREAMING_SNAKE_CASE_      :		int							,			SCREAMING_SNAKE_CASE_      :		int       ):






       """simple docstring"""





       UpperCamelCase    :	Union[str, Any]   	=		[float('''inf'''       )] * vertex_count
       UpperCamelCase    :	Tuple   	=		0.0

       for _ in range(vertex_count - 1       ):
              for j in range(SCREAMING_SNAKE_CASE_       ):
                     UpperCamelCase	, UpperCamelCase	, UpperCamelCase    :	str   	=		(graph[j][k] for k in ['''src''', '''dst''', '''weight'''])

                     if distance[u] != float('''inf'''       ) and distance[u] + w < distance[v]:
                            UpperCamelCase    :	str   	=		distance[u] + w

       UpperCamelCase    :	str   	=		check_negative_cycle(SCREAMING_SNAKE_CASE_							,			SCREAMING_SNAKE_CASE_							,			SCREAMING_SNAKE_CASE_       )
       if negative_cycle_exists:
              raise Exception('''Negative cycle found'''       )

       return distance


if __name__ == "__main__":
  import doctest

  doctest.testmod()

  __UpperCAmelCase : Optional[Any] 			=				int(input("Enter number of vertices: ").strip())
  __UpperCAmelCase : Any 			=				int(input("Enter number of edges: ").strip())

  __UpperCAmelCase : list[dict[str, int]] 			=				[{} for _ in range(E)]

  for i in range(E):
    print("Edge ", i + 1)
    __UpperCAmelCase			,    __UpperCAmelCase			,    __UpperCAmelCase : str 			=				(
        int(x)
        for x in input("Enter source, destination, weight: ").strip().split(" ")
    )
    __UpperCAmelCase : List[str] 			=				{"src": src, "dst": dest, "weight": weight}

  __UpperCAmelCase : Optional[int] 			=				int(input("\nEnter shortest path source:").strip())
  __UpperCAmelCase : List[str] 			=				bellman_ford(graph, V, E, source)
  print_distance(shortest_distance, 0)





from .imports import is_tqdm_available


if is_tqdm_available():
  from tqdm.auto import tqdm as _tqdm

from ..state import PartialState


def      a	(							SCREAMING_SNAKE_CASE_      :		bool = True							,			*SCREAMING_SNAKE_CASE_      :		List[str]							,			**SCREAMING_SNAKE_CASE_      :		Tuple       ):






       """simple docstring"""





       if not is_tqdm_available():
              raise ImportError('''Accelerate\'s `tqdm` module requires `tqdm` to be installed. Please run `pip install tqdm`.'''       )
       UpperCamelCase    :	int   	=		False
       if main_process_only:
              UpperCamelCase    :	int   	=		PartialState().local_process_index == 0
       return _tqdm(*SCREAMING_SNAKE_CASE_							,			**SCREAMING_SNAKE_CASE_							,			disable=SCREAMING_SNAKE_CASE_       )

