code: def train():
      model.train()
      optimizer.zero_grad()
      out = model(data.x, data.edge_index)
      loss = F.nll_loss(out[data.train_idx], data.y[data.train_idx])
      loss.backward()
      optimizer.step()
  
file_path: pytorch_geometric/examples/dna.py
imports: import os.path
  import torch
  import torch.nn.functional
  from sklearn.model_selection import StratifiedKFold
  from torch_geometric.datasets import Planetoid
  from torch_geometric.nn import DNAConv
label_desc: Use image node_id 2 for calling a global function with example usage: train() without return types