code: def test():
      model.eval()
      z = model.encode(data.edge_index, data.edge_type)
  
      valid_mrr = compute_mrr(
          z, data.valid_edge_index, data.valid_edge_type
      )
      test_mrr = compute_mrr(
          z, data.test_edge_index, data.test_edge_type
      )
  
      return valid_mrr, test_mrr
  
imports: import os.path
  import time
  import torch
  import torch.nn.functional
  from torch.nn import Parameter
  from tqdm import tqdm
  from torch_geometric.datasets import RelLinkPredDataset
  from torch_geometric.nn import GAE, RGCNConv
label_desc: Use image node_id 3 for calling a global function with example usage: test() and returns: valid_mrr,  test_mrr