code: def test():
      model.eval()
      pred = model(data.edge_index, data.edge_type).argmax(dim=-1)
      train_acc = float(
          (pred[data.train_idx] == data.train_y).float().mean()
      )
      test_acc = float(
          (pred[data.test_idx] == data.test_y).float().mean()
      )
      return train_acc, test_acc
  
file_path: pytorch_geometric/examples/rgcn.py
imports: import argparse
  import os.path
  import time
  import torch
  import torch.nn.functional
  from torch_geometric.datasets import Entities
  from torch_geometric.nn import FastRGCNConv, RGCNConv
  from torch_geometric.utils import k_hop_subgraph
label_desc: Use image node_id 2 for calling a global function with example usage: test() and returns: train_acc,  test_acc