code: def test():
      model.eval()
  
      zs = []
      for batch in tqdm(test_loader, desc="Evaluating"):
          pos_z, _, _ = model(
              batch.x, batch.edge_index, batch.batch_size
          )
          zs.append(pos_z.cpu())
      z = torch.cat(zs, dim=0)
      train_val_mask = data.train_mask | data.val_mask
      acc = model.test(
          z[train_val_mask],
          data.y[train_val_mask],
          z[data.test_mask],
          data.y[data.test_mask],
          max_iter=10000,
      )
      return acc
  
file_path: pytorch_geometric/examples/infomax_inductive.py
imports: import os.path
  import torch
  from tqdm import tqdm
  from torch_geometric.datasets import Reddit
  from torch_geometric.loader import NeighborLoader
  from torch_geometric.nn import DeepGraphInfomax, SAGEConv
label_desc: Use image node_id 3 for calling a global function with example usage: test() and returns: acc