code: def forward(self, x, edge_index):
      for conv, norm in zip(self.convs[:-1], self.norms):
          x = norm(conv(x, edge_index))
          x = F.dropout(x, p=self.dropout, training=self.training)
      x = self.convs[-1](x, edge_index)
      return x
  
file_path: pytorch_geometric/examples/film.py
imports: import os.path
  import torch
  import torch.nn.functional
  from sklearn.metrics import f1_score
  from torch.nn import BatchNorm1d
  from torch_geometric.datasets import PPI
  from torch_geometric.loader import DataLoader
  from torch_geometric.nn import FiLMConv
label_desc: Use image node_id 2 for calling the Net obj's underlying member method code with example usage: obj.forward(x, edge_index) and returns: x