code: def message_aggr(self, x, edge_index):
      target_idx, source_idx = edge_index
      message_inputs = torch.cat(
          (
              x.index_select(0, source_idx),
              x.index_select(0, target_idx),
          ),
          dim=-1,
      )
      messages = self.message_net(message_inputs)
      aggregation = scatter(
          messages,
          target_idx,
          dim=0,
          dim_size=x.shape[0],
          reduce=ReduceType.ADD.value,
      )
  
      if hasattr(self, "message_norm"):
          aggregation = self.message_norm(aggregation)
      return aggregation
  
file_path: DIG/dig/auggraph/method/GraphAug/aug/aug_encoder.py
imports: import torch
  from torch.nn import Linear, Sequential, ReLU, BatchNorm1d
  from torch_geometric.nn import GINConv
  from torch_scatter import scatter
  from ..constants import *
label_desc: Use image node_id 4 for calling the GEMBConv obj's underlying member method code with example usage: obj.message_aggr(x, edge_index) and returns: aggregation