

__A    	=			{
    0: '''underwear''',
    1: '''pants''',
    2: '''belt''',
    3: '''suit''',
    4: '''shoe''',
    5: '''socks''',
    6: '''shirt''',
    7: '''tie''',
    8: '''watch''',
}

__A    	=			[[1, 4], [2, 4], [3], [], [], [4], [2, 7], [3], []]

__A    	=			[0 for x in range(len(graph))]
__A    	=			[]



def    snake_case_(_UpperCamelCase				, _UpperCamelCase  )							->			Tuple:



  """simple docstring"""






  _snake_case		=							1
  while stack:
    _snake_case		=							stack.pop()
    print(_UpperCamelCase				, clothes[current_clothing]  )
    order += 1



def    snake_case_(_UpperCamelCase				, _UpperCamelCase				, _UpperCamelCase  )							->			Any:



  """simple docstring"""






  _snake_case		=							1
  for v in graph[u]:
    if not visited[v]:
      depth_first_search(_UpperCamelCase				, _UpperCamelCase				, _UpperCamelCase  )

  stack.append(_UpperCamelCase  )



def    snake_case_(_UpperCamelCase				, _UpperCamelCase  )							->			List[Any]:



  """simple docstring"""






  for v in range(len(_UpperCamelCase  )  ):
    if not visited[v]:
      depth_first_search(_UpperCamelCase				, _UpperCamelCase				, _UpperCamelCase  )


if __name__ == "__main__":
 topological_sort(graph, visited)
 print(stack)
 print_stack(stack, clothes)




import numpy as np



def    snake_case_(_UpperCamelCase  )							->			Any:



  """simple docstring"""






  _snake_case		=							np.exp(_UpperCamelCase  )

  # Add up the all the exponentials
  _snake_case		=							np.sum(_UpperCamelCase  )

  # Divide every exponent by the sum of all exponents
  _snake_case		=							exponent_vector / sum_of_exponents

  return softmax_vector


if __name__ == "__main__":
 print(softmax((0,)))

