code: def test(model, test_loader, device):
      model.eval()
  
      correct = 0
      for data in test_loader:
          data = data.to(device)
          pred = model(data.pos, data.batch).max(1)[1]
          correct += pred.eq(data.y).sum().item()
      test_acc = correct / len(test_loader.dataset)
  
      return test_acc
  
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 5 for calling a global function with example usage: test(model, test_loader, device) and returns: test_acc