code: def train():
      model.train()
  
      total_loss = total_nodes = 0
      for batch in train_loader:
          batch = batch.to(device)
          optimizer.zero_grad()
          out = model(batch.x, batch.edge_index)
          loss = F.nll_loss(
              out[batch.train_mask], batch.y[batch.train_mask]
          )
          loss.backward()
          optimizer.step()
  
          nodes = batch.train_mask.sum().item()
          total_loss += loss.item() * nodes
          total_nodes += nodes
  
      return total_loss / total_nodes
  
file_path: pytorch_geometric/examples/cluster_gcn_reddit.py
imports: import time
  import torch
  import torch.nn.functional
  from torch.nn import ModuleList
  from tqdm import tqdm
  from torch_geometric.datasets import Reddit
  from torch_geometric.loader import ClusterData, ClusterLoader, NeighborLoader
  from torch_geometric.nn import SAGEConv
label_desc: Use image node_id 1 for calling a global function with example usage: train() and returns: unknown