def test_lasagne_functional_regression(boston):
    from nolearn.lasagne import NeuralNet

    X, y = boston

    layer1 = InputLayer(shape=(128, 13))
    layer2 = DenseLayer(layer1, num_units=100)
    output = DenseLayer(layer2, num_units=1, nonlinearity=identity)

    nn = NeuralNet(
        layers=output,
        update_learning_rate=0.01,
        update_momentum=0.1,
        regression=True,
        max_epochs=50,
        )

    nn.fit(X[:300], y[:300])
    assert 3.0 < mean_absolute_error(nn.predict(X[300:]), y[300:])
dataset/ETHPy150Open dnouri/nolearn/nolearn/lasagne/tests/test_base.py/test_lasagne_functional_regression/swapped operands of `<`