





'''simple docstring'''






def        UpperCamelCase__		(						__magic_name__  :   Tuple		,       __magic_name__  :   int      )				->			str:
 '''simple docstring'''






 print("""\nThe shortest path matrix using Floyd Warshall algorithm\n"""      )
 for i in range(__magic_name__      ):
  for j in range(__magic_name__      ):
   if dist[i][j] != float("""inf"""      ):
    print(int(dist[i][j]      )		,       end="""\t"""      )
   else:
    print("""INF"""		,       end="""\t"""      )
  print()



def        UpperCamelCase__		(						__magic_name__  :   Tuple		,       __magic_name__  :   Union[str, Any]      )				->			str:
 '''simple docstring'''






 snake_case__     :					Optional[Any]    =  [[float("""inf"""      ) for _ in range(__magic_name__      )] for _ in range(__magic_name__      )]

 for i in range(__magic_name__      ):
  for j in range(__magic_name__      ):
   snake_case__     :					str    =  graph[i][j]

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

 _print_dist(__magic_name__		,       __magic_name__      )
 return dist, v


if __name__ == "__main__":
    A_		:  Optional[int]		 =						int(input("Enter number of vertices: "))
    A_		:  str		 =						int(input("Enter number of edges: "))

    A_		:  List[str]		 =						[[float("inf") for i in range(v)] for j in range(v)]

    for i in range(v):
        A_		:  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)
        A_		:  Any		 =						int(input("Enter source:"))
        A_		:  List[str]		 =						int(input("Enter destination:"))
        A_		:  int		 =						float(input("Enter weight:"))
        A_		:  int		 =						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











import unittest
from dataclasses import dataclass

import pytest

from accelerate.commands.config.config_args import SageMakerConfig
from accelerate.utils import ComputeEnvironment
from accelerate.utils.launch import _convert_nargs_to_dict




@dataclass
class        SCREAMING_SNAKE_CASE__					(		UpperCamelCase__ ):
 __SCREAMING_SNAKE_CASE							=      ComputeEnvironment.AMAZON_SAGEMAKER
 __SCREAMING_SNAKE_CASE							=      True
 __SCREAMING_SNAKE_CASE							=      '''ml.p3.2xlarge'''
 __SCREAMING_SNAKE_CASE							=      '''accelerate_sagemaker_execution_role'''
 __SCREAMING_SNAKE_CASE							=      '''hf-sm'''
 __SCREAMING_SNAKE_CASE							=      '''us-east-1'''
 __SCREAMING_SNAKE_CASE							=      1
 __SCREAMING_SNAKE_CASE							=      '''accelerate-sagemaker-1'''
 __SCREAMING_SNAKE_CASE							=      '''1.6'''
 __SCREAMING_SNAKE_CASE							=      '''4.4'''
 __SCREAMING_SNAKE_CASE							=      '''train.py'''
 __SCREAMING_SNAKE_CASE							=      [
     '''--model_name_or_path''',
     '''bert''',
     '''--do_train''',
     '''False''',
     '''--epochs''',
     '''3''',
     '''--learning_rate''',
     '''5e-5''',
     '''--max_steps''',
     '''50.5''',
 ]
 __SCREAMING_SNAKE_CASE							=      [
     '''--model_name_or_path''',
     '''bert''',
     '''--do_train''',
     '''--do_test''',
     '''False''',
     '''--do_predict''',
     '''--epochs''',
     '''3''',
     '''--learning_rate''',
     '''5e-5''',
     '''--max_steps''',
     '''50.5''',
 ]




class        SCREAMING_SNAKE_CASE__					(		unittest.TestCase ):



 def 							UpperCamelCase     (				self					):
        # If no defaults are changed, `to_kwargs` returns an empty dict.
        A__		   =		_convert_nargs_to_dict(MockLaunchConfig.success_training_script_args					)
        assert isinstance(converted_args['''model_name_or_path'''],__lowerCamelCase					)
        assert isinstance(converted_args['''do_train'''],__lowerCamelCase					)
        assert isinstance(converted_args['''epochs'''],__lowerCamelCase					)
        assert isinstance(converted_args['''learning_rate'''],__lowerCamelCase					)
        assert isinstance(converted_args['''max_steps'''],__lowerCamelCase					)

        with pytest.raises(__lowerCamelCase					):
               _convert_nargs_to_dict(MockLaunchConfig.fail_training_script_args					)





