def METHOD_NAME():
    """Test proper thresholding."""
    y = np.random.rand(10, 2)
    y = y / np.sum(y, axis=1)[:, np.newaxis]
    y = np.expand_dims(y, 1)
    y_expected = np.expand_dims(
        to_one_hot(np.argmax(np.squeeze(y), axis=1), n_classes=2), 1)
    y_out = handle_classification_mode(y,
                                       "threshold-one-hot",
                                       threshold_value=0.5)
    assert y_out.shape == (10, 1, 2)
    assert np.array_equal(y_out, y_expected)