def METHOD_NAME(loader):
    model.eval()
    correct = 0
    loss_all = 0
    for data in loader:
        data = data.to(device)
        pred, mc_loss, o_loss = model(data.x, data.edge_index, data.batch)
        loss = F.nll_loss(pred, data.y.view(-1)) + mc_loss + o_loss
        loss_all += data.y.size(0) * float(loss)
        correct += int(pred.max(dim=1)[1].eq(data.y.view(-1)).sum())
    return loss_all / len(loader.dataset), correct / len(loader.dataset)