

from sklearn.neural_network import MLPClassifier

_lowerCamelCase       :     Tuple           =							[[0.0, 0.0], [1.0, 1.0], [1.0, 0.0], [0.0, 1.0]]
_lowerCamelCase       :     Tuple           =							[0, 1, 0, 0]


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

clf.fit(X, y)


_lowerCamelCase       :     Dict           =							[[0.0, 0.0], [0.0, 1.0], [1.0, 1.0]]
_lowerCamelCase       :     Optional[Any]           =							clf.predict(test)

def     a__  (	UpperCAmelCase							:    List[Any]    )						->		Any:
  return list(UpperCAmelCase    )


if __name__ == "__main__":
     import doctest

     doctest.testmod()








def     a__  (	UpperCAmelCase							:    str    )						->		str:
  return " ".join([word[::-1] for word in input_str.split()]    )


if __name__ == "__main__":
     import doctest

     doctest.testmod()





