

from __future__ import annotations

class  a     :


						def __init__(				self  ,    A_		):







										'''simple docstring'''


										_UpperCAmelCase				:						List[Any]       						=			vertices
										_UpperCAmelCase				:						List[str]       						=			[[0] * vertices for _ in range(A_		)]


						def 				_UpperCAmelCase (				self  ,    A_		):







										'''simple docstring'''


										print("Vertex \t Distance from Source"		)
										for vertex in range(self.vertices		):
														print(A_  ,    "\t\t"  ,    distances_from_source[vertex]		)


						def 				_UpperCAmelCase (				self  ,    A_  ,    A_		):







										'''simple docstring'''


										_UpperCAmelCase				:						Tuple       						=			1e7
										_UpperCAmelCase				:						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:
																		_UpperCAmelCase				:						List[Any]       						=			distances_from_source[vertex]
																		_UpperCAmelCase				:						Tuple       						=			vertex
										return min_index





						def 				_UpperCAmelCase (				self  ,    A_		):







										'''simple docstring'''


										_UpperCAmelCase				:						Union[str, Any]       						=			[int(1e7		)] * self.vertices  # distances from the source
										_UpperCAmelCase				:						Optional[Any]       						=			0
										_UpperCAmelCase				:						List[str]       						=			[False] * self.vertices

										for _ in range(self.vertices		):
														_UpperCAmelCase				:						str       						=			self.minimum_distance(A_  ,    A_		)
														_UpperCAmelCase				:						str       						=			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]
																		):
																						_UpperCAmelCase				:						str       						=			distances[u] + self.graph[u][v]

										self.print_solution(A_		)


if __name__ == "__main__":
					SCREAMING_SNAKE_CASE_						=					Graph(9)
					SCREAMING_SNAKE_CASE_						=					[
					    [0, 4, 0, 0, 0, 0, 0, 8, 0],
					    [4, 0, 8, 0, 0, 0, 0, 11, 0],
					    [0, 8, 0, 7, 0, 4, 0, 0, 2],
					    [0, 0, 7, 0, 9, 14, 0, 0, 0],
					    [0, 0, 0, 9, 0, 10, 0, 0, 0],
					    [0, 0, 4, 14, 10, 0, 2, 0, 0],
					    [0, 0, 0, 0, 0, 2, 0, 1, 6],
					    [8, 11, 0, 0, 0, 0, 1, 0, 7],
					    [0, 0, 2, 0, 0, 0, 6, 7, 0],
					]
					graph.dijkstra(0)





'''simple docstring'''
import os
import unittest

import pytest
from parameterized import parameterized

from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device


# skipping in unittest tests

_lowerCamelCase	 =			[(1,)]


def       a__    (  )			-> str:


	"""simple docstring"""





	UpperCAmelCase_			:	Optional[int]      =   bool(os.getenv("RUN_SLOW"     ,							0							)							)
	if run_slow:
		assert True
	else:
		assert False, "should have been skipped"


def       a__    (  )			-> str:


	"""simple docstring"""





	UpperCAmelCase_			:	Optional[Any]      =   bool(os.getenv("RUN_SLOW"     ,							0							)							)
	if run_slow and torch_device == "cuda":
		assert True
	else:
		assert False, "should have been skipped"
@require_torch
class  _snake_case						(unittest.TestCase):






			@slow
			@require_torch_gpu
			def 						UpperCamelCase__				(   self			):
				check_slow_torch_cuda()






			@require_torch_gpu
			@slow
			def 						UpperCamelCase__				(   self			):
				check_slow_torch_cuda()






			@parameterized.expand(_snake_case			)
			@slow
			def 						UpperCamelCase__				(   self       ,_snake_case=None			):
				check_slow()




@slow
@require_torch_gpu
def       a__    (  )			-> List[Any]:


	"""simple docstring"""





	check_slow_torch_cuda()


@require_torch_gpu
@slow
def       a__    (  )			-> List[str]:


	"""simple docstring"""





	check_slow_torch_cuda()


@slow
@pytest.mark.parametrize("param"     ,							[1]							)
def       a__    (  _SCREAMING_SNAKE_CASE					:    int							)			-> List[Any]:


	"""simple docstring"""





	check_slow()





@pytest.mark.parametrize("param"     ,							[1]							)
@slow
def       a__    (  _SCREAMING_SNAKE_CASE					:    List[str]							)			-> Any:


	"""simple docstring"""





	check_slow()




