code: def forward(self, xs):
      hs = []
      for x, lin in zip(xs, self.lins):
          h = lin(x).relu()
          h = F.dropout(h, p=0.5, training=self.training)
          hs.append(h)
      h = torch.cat(hs, dim=-1)
      h = self.lin(h)
      return h.log_softmax(dim=-1)
  
file_path: pytorch_geometric/examples/sign.py
imports: import os.path
  import torch
  import torch.nn.functional
  from torch.nn import Linear
  from torch.utils.data import DataLoader
  import torch_geometric.transforms
  from torch_geometric.datasets import Flickr
label_desc: Use image node_id 2 for calling the Net obj's underlying member method code with example usage: obj.forward(xs) and returns: h