def METHOD_NAME(use_torch):
    """test negstoi loss rowcolnorn"""
    torch.manual_seed(0)
    x_size = [3, 100, 100]
    x = torch.rand(x_size)
    y = NegSTOILoss.rowcol_norm(x)
    assert y.shape == torch.Size(x_size)
    y_array = y.cpu().detach().numpy()
    assert np.sum(np.abs(y_array)) == pytest.approx(
        2589.76416015625, rel=pytest.rel_tolerance, abs=pytest.abs_tolerance
    )