code: def test(loader):
      model.eval()
      error = 0
  
      for data in loader:
          data = data.to(device)
          error += (
              (model(data) * std - data.y * std).abs().sum().item()
          )  # MAE
      return error / len(loader.dataset)
  
file_path: pytorch_geometric/examples/qm9_nn_conv.py
imports: import copy
  import os.path
  import torch
  import torch.nn.functional
  from torch.nn import GRU, Linear, ReLU, Sequential
  import torch_geometric.transforms
  from torch_geometric.datasets import QM9
  from torch_geometric.loader import DataLoader
  from torch_geometric.nn import NNConv, Set2Set
  from torch_geometric.utils import remove_self_loops
label_desc: Use image node_id 2 for calling a global function with example usage: test(loader) and returns: unknown