code: def train():
      model.train()
  
      total_loss = total_examples = 0
      for idx in train_loader:
          xs = [data.x[idx].to(device)]
          xs += [data[f"x{i}"][idx].to(device) for i in range(1, K + 1)]
          y = data.y[idx].to(device)
  
          optimizer.zero_grad()
          out = model(xs)
          loss = F.nll_loss(out, y)
          loss.backward()
          optimizer.step()
  
          total_loss += float(loss) * idx.numel()
          total_examples += idx.numel()
  
      return total_loss / total_examples
  
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 1 for calling a global function with example usage: train() and returns: unknown