How to use the fairlearn.metrics.mean_overprediction function in fairlearn

def test_mean_overprediction_weighted_single():
    y_pred = [1]
    y_true = [0]
    weight = [1]

    result = metrics.mean_overprediction(y_true, y_pred, weight)

    assert result == 1

def test_mean_overprediction_unweighted_single():
    y_pred = [1]
    y_true = [0]

    result = metrics.mean_overprediction(y_true, y_pred)

    assert result == 1

def test_mean_overprediction_weighted():
    y_pred = [0, 1, 2, 3, 4]
    y_true = [1, 1, 5, 0, 2]
    weight = [3, 1, 7, 1, 2]

    result = metrics.mean_overprediction(y_true, y_pred, weight)

    assert result == 0.5

def test_mean_overprediction_unweighted():
    y_pred = [0, 1, 2, 3, 4]
    y_true = [1, 1, 5, 0, 2]

    result = metrics.mean_overprediction(y_true, y_pred)

    assert result == 1