def METHOD_NAME(node_index, node_label, gnn_model, graph, criterion, optim):
    gnn_model.METHOD_NAME()
    pred = gnn_model(graph, graph.node_feat["words"])
    pred = paddle.gather(pred, node_index)
    loss = criterion(pred, node_label)
    loss.backward()
    acc = paddle.metric.accuracy(input=pred, label=node_label, k=1)
    for op in optim:
        op.step()
        op.clear_grad()
    #optim.step()
    #optim.clear_grad()
    return loss, acc