code: def update(self, aggr_out):
      # aggr_out has shape [N, out_channels]
  
      return aggr_out
  
imports: import copy
  import time
  import argparse
  import torch
  import torch.nn
  import torch.nn.functional
  import networkx
  import numpy
  import sklearn.metrics
  import torch_geometric.nn
  from torch.utils.data import DataLoader
  from deepsnap.dataset import GraphDataset
  from deepsnap.batch import Batch
  from deepsnap.graph import Graph
label_desc: Use image node_id 4 for calling the MlpMessageConv obj's underlying member method code with example usage: obj.update(aggr_out) and returns: aggr_out