code: def test():
      model.eval()
      out = model(data.x, data.edge_index).cpu()
  
      clf = LogisticRegression()
      clf.fit(out[data.train_mask], data.y[data.train_mask])
  
      val_acc = clf.score(out[data.val_mask], data.y[data.val_mask])
      test_acc = clf.score(out[data.test_mask], data.y[data.test_mask])
  
      return val_acc, test_acc
  
file_path: pytorch_geometric/examples/graph_sage_unsup.py
imports: import os.path
  import time
  import torch
  import torch.nn.functional
  from sklearn.linear_model import LogisticRegression
  import torch_geometric.transforms
  from torch_geometric.datasets import Planetoid
  from torch_geometric.loader import LinkNeighborLoader
  from torch_geometric.nn import GraphSAGE
label_desc: Use image node_id 2 for calling a global function with example usage: test() and returns: val_acc,  test_acc