





"""simple docstring"""


from sklearn.neural_network import MLPClassifier

A_     :      str								=[[0.0, 0.0], [1.0, 1.0], [1.0, 0.0], [0.0, 1.0]]
A_     :      Optional[int]								=[0, 1, 0, 0]


A_     :      List[Any]								=MLPClassifier(
    solver="""lbfgs""", alpha=1E-5, hidden_layer_sizes=(5, 2), random_state=1
)

clf.fit(X, y)


A_     :      str								=[[0.0, 0.0], [0.0, 1.0], [1.0, 1.0]]
A_     :      List[Any]								=clf.predict(test)





def SCREAMING_SNAKE_CASE_   (       snake_case   :					str		)->		Optional[int]:
       return list(snake_case		)


if __name__ == "__main__":
      import doctest

      doctest.testmod()













"""simple docstring"""


def SCREAMING_SNAKE_CASE_   (       )->		Tuple:
       _lowerCamelCase    	=					1

       while True:
              if (
                  sorted(str(snake_case		)		)
                  == sorted(str(2 * i		)		)
                  == sorted(str(3 * i		)		)
                  == sorted(str(4 * i		)		)
                  == sorted(str(5 * i		)		)
                  == sorted(str(6 * i		)		)
              ):
                     return i

              i += 1


if __name__ == "__main__":
      print(solution())






