code: def test():
      model.eval()
      y_hat = model.inference(data.x, subgraph_loader).argmax(dim=-1)
      y = data.y.to(y_hat.device)
  
      accs = []
      for mask in [data.train_mask, data.val_mask, data.test_mask]:
          accs.append(
              int((y_hat[mask] == y[mask]).sum()) / int(mask.sum())
          )
      return accs
  
file_path: pytorch_geometric/examples/reddit.py
imports: import copy
  import os.path
  import time
  import torch
  import torch.nn.functional
  from tqdm import tqdm
  from torch_geometric.datasets import Reddit
  from torch_geometric.loader import NeighborLoader
  from torch_geometric.nn import SAGEConv
label_desc: Use image node_id 2 for calling a global function with example usage: test() and returns: accs