code: def train(epoch):
      model.train()
  
      total_loss = total_examples = 0
      for batch in tqdm(train_loader, desc=f"Epoch {epoch:02d}"):
          optimizer.zero_grad()
          pos_z, neg_z, summary = model(
              batch.x, batch.edge_index, batch.batch_size
          )
          loss = model.loss(pos_z, neg_z, summary)
          loss.backward()
          optimizer.step()
          total_loss += float(loss) * pos_z.size(0)
          total_examples += pos_z.size(0)
  
      return total_loss / total_examples
  
file_path: pytorch_geometric/examples/infomax_inductive.py
imports: import os.path
  import torch
  from tqdm import tqdm
  from torch_geometric.datasets import Reddit
  from torch_geometric.loader import NeighborLoader
  from torch_geometric.nn import DeepGraphInfomax, SAGEConv
label_desc: Use image node_id 2 for calling a global function with example usage: train(epoch) and returns: unknown