code: def test_teacher():
      gnn.eval()
      pred = gnn(data.x, data.edge_index).argmax(dim=-1)
      accs = []
      for _, mask in data("train_mask", "val_mask", "test_mask"):
          accs.append(
              int((pred[mask] == data.y[mask]).sum()) / int(mask.sum())
          )
      return accs
  
file_path: pytorch_geometric/examples/glnn.py
imports: import argparse
  import os.path
  import time
  import torch
  import torch.nn.functional
  import torch_geometric.transforms
  from torch_geometric.datasets import Planetoid
  from torch_geometric.nn import GCN, MLP
label_desc: Use image node_id 2 for calling a global function with example usage: test_teacher() and returns: accs