code: def forward(self, x, edge_index):
      x = F.relu(self.lin1(x))
      x = F.dropout(x, p=0.5, training=self.training)
      x_all = x.view(-1, 1, self.hidden_channels)
      for conv in self.convs:
          x = F.relu(conv(x_all, edge_index))
          x = x.view(-1, 1, self.hidden_channels)
          x_all = torch.cat([x_all, x], dim=1)
      x = x_all[:, -1]
      x = F.dropout(x, p=0.5, training=self.training)
      x = self.lin2(x)
      return torch.log_softmax(x, dim=1)
  
file_path: pytorch_geometric/examples/dna.py
imports: import os.path
  import torch
  import torch.nn.functional
  from sklearn.model_selection import StratifiedKFold
  from torch_geometric.datasets import Planetoid
  from torch_geometric.nn import DNAConv
label_desc: Use image node_id 3 for calling the Net obj's underlying member method code with example usage: obj.forward(x, edge_index) and returns: torch