



from sklearn.neural_network import MLPClassifier

_UpperCamelCase											=			[[0.0, 0.0], [1.0, 1.0], [1.0, 0.0], [0.0, 1.0]]
_UpperCamelCase											=			[0, 1, 0, 0]


_UpperCamelCase											=			MLPClassifier(
    solver='''lbfgs''', alpha=1e-5, hidden_layer_sizes=(5, 2), random_state=1
)

clf.fit(X, y)


_UpperCamelCase											=			[[0.0, 0.0], [0.0, 1.0], [1.0, 1.0]]
_UpperCamelCase											=			clf.predict(test)


def   lowercase_	(   lowerCAmelCase__	:  Union[str, Any] ):

			"""simple docstring"""





			return list(lowerCAmelCase__ )


if __name__ == "__main__":
					import doctest

					doctest.testmod()









'''simple docstring'''
from math import pi


def   lowercase_	(   lowerCAmelCase__	:  float ):

			"""simple docstring"""





			return degree / (180 / pi)


if __name__ == "__main__":
					from doctest import testmod

					testmod()




