code: def forward(self, x, edge_index, edge_attr):
      x = self.node_encoder(x)
      edge_attr = self.edge_encoder(edge_attr)
  
      x = self.layers[0].conv(x, edge_index, edge_attr)
  
      for layer in self.layers[1:]:
          x = layer(x, edge_index, edge_attr)
  
      x = self.layers[0].act(self.layers[0].norm(x))
      x = F.dropout(x, p=0.1, training=self.training)
  
      return self.lin(x)
  
file_path: pytorch_geometric/examples/ogbn_proteins_deepgcn.py
imports: import torch
  import torch.nn.functional
  from ogb.nodeproppred import Evaluator, PygNodePropPredDataset
  from torch.nn import LayerNorm, Linear, ReLU
  from tqdm import tqdm
  from torch_geometric.loader import RandomNodeLoader
  from torch_geometric.nn import DeepGCNLayer, GENConv
  from torch_geometric.utils import scatter
label_desc: Use image node_id 2 for calling the DeeperGCN obj's underlying member method code with example usage: obj.forward(x, edge_index, edge_attr) and returns: self