def METHOD_NAME(self):
    # check loss of inputs with duplicate rows doesn't change
    sample_weight = np.array([0.4, 0.3, 0.2, 0.1])
    y_true = np.array([1.0, 0.0, 1.0, 0.0])
    y_pred = np.array([0.1, 0.2, 0.3, 0.4])
    mask = np.array([True, False, True, True])
    mask = ops.convert_to_tensor(mask)
    y_true = ops.convert_to_tensor(y_true)
    y_pred = ops.convert_to_tensor(y_pred)
    y_pred._keras_mask = mask
    loss_fn = ExampleLoss()
    rank1_loss = loss_fn(y_true, y_pred, sample_weight=sample_weight)
    # duplicate rows
    mask = ops.tile(ops.expand_dims(mask, axis=0), (2, 1))
    y_true = ops.tile(ops.expand_dims(y_true, axis=0), (2, 1))
    y_pred = ops.tile(ops.expand_dims(y_pred, axis=0), (2, 1))
    sample_weight = ops.tile(ops.expand_dims(sample_weight, axis=0), (2, 1))
    y_pred._keras_mask = mask
    rank2_loss = loss_fn(y_true, y_pred, sample_weight=sample_weight)
    self.assertAllClose(rank1_loss, rank2_loss)