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from sklearn.neural_network import MLPClassifier

X = [[0.0, 0.0], [1.0, 1.0], [1.0, 0.0], [0.0, 1.0]]

y = [0, 1, 0, 0]

clf = MLPClassifier(

solver="lbfgs", alpha=1e-5, hidden_layer_sizes=(5, 2), random_state=1

)

clf.fit(X, y)

test = [[0.0, 0.0], [0.0, 1.0], [1.0, 1.0]]

Y = clf.predict(test)

def wrapper(y):

"""

>>> [int(x) for x in wrapper(Y)]

[0, 0, 1]

"""

return list(y)

if __name__ == "__main__":

import doctest

doctest.testmod()

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