def METHOD_NAME():
    model.METHOD_NAME()
    total_loss = correct_nodes = total_nodes = 0
    for i, data in enumerate(train_loader):
        data = data.to(device)
        optimizer.zero_grad()
        out = model(data)
        loss = F.nll_loss(out, data.y)
        loss.backward()
        optimizer.step()
        total_loss += loss.item()
        correct_nodes += out.argmax(dim=1).eq(data.y).sum().item()
        total_nodes += data.num_nodes
        if (i + 1) % 10 == 0:
            print(f'[{i+1}/{len(train_loader)}] Loss: {total_loss / 10:.4f} '
                  f'Train Acc: {correct_nodes / total_nodes:.4f}')
            total_loss = correct_nodes = total_nodes = 0