code: def test():
      model.eval()
  
      out = model.inference(x)
  
      y_true = y.cpu().unsqueeze(-1)
      y_pred = out.argmax(dim=-1, keepdim=True)
  
      results = []
      for mask in [data.train_mask, data.val_mask, data.test_mask]:
          results += [
              int(y_pred[mask].eq(y_true[mask]).sum()) / int(mask.sum())
          ]
  
      return results
  
file_path: pytorch_geometric/examples/quiver/single_gpu_quiver.py
imports: import os.path
  import quiver
  import torch
  import torch.nn.functional
  from tqdm import tqdm
  from torch_geometric.datasets import Reddit
  from torch_geometric.loader import NeighborSampler
  from torch_geometric.nn import SAGEConv
label_desc: Use image node_id 2 for calling a global function with example usage: test() and returns: results