code: def train(model, optimizer, train_loader, device):
      model.train()
  
      for data in train_loader:
          optimizer.zero_grad()
          data = data.to(device)
          out = model(data.pos, data.batch)
          loss = F.nll_loss(out, data.y)
          loss.backward()
          optimizer.step()
  
file_path: pytorch_geometric/benchmark/points/train_eval.py
imports: import time
  import torch
  import torch.nn.functional
  from torch.optim import Adam
  from torch_geometric.loader import DataLoader
  from torch_geometric.profile import timeit, torch_profile
label_desc: Use image node_id 4 for calling a global function with example usage: train(model, optimizer, train_loader, device) without return types