code: def forward(self, x, edge_index):
      for conv, batch_norm in zip(self.convs[:-1], self.batch_norms):
          x = conv(x, edge_index)
          x = batch_norm(x)
          x = F.relu(x)
          x = F.dropout(x, p=0.2, training=self.training)
      return self.convs[-1](x, edge_index)
  
file_path: pytorch_geometric/examples/cluster_gcn_ppi.py
imports: import os.path
  import time
  import torch
  import torch.nn.functional
  from sklearn.metrics import f1_score
  from torch_geometric.data import Batch
  from torch_geometric.datasets import PPI
  from torch_geometric.loader import ClusterData, ClusterLoader, DataLoader
  from torch_geometric.nn import BatchNorm, SAGEConv
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: self