def METHOD_NAME(self):
    output = np.array([[0.7, 0.8, 0.4], [0.8, 0.1, 0.1]])
    target = np.array([[1, 0, 0], [1, 0, 1]])
    mask = np.array([[True, True, True], [True, True, True]])
    thr = 0.5
    acc = multilabel_classification_accuracy(output, target, mask, thr)
    self.assertEqual(acc, 0)
    output = np.array([[0.7, 0.2, 0.4], [0.8, 0.1, 0.9]])
    thr = 0.5
    acc = multilabel_classification_accuracy(output, target, mask, thr)
    self.assertEqual(acc, 1)
    thr = 0.3
    acc = multilabel_classification_accuracy(output, target, mask, thr)
    self.assertEqual(acc, 0.5)
    mask = np.array([[True, True, False], [True, True, True]])
    acc = multilabel_classification_accuracy(output, target, mask, thr)
    self.assertEqual(acc, 1)