code: def test():
      model.eval()
      pred = model(data.x, data.edge_index).argmax(dim=-1)
  
      accs = []
      for mask in [data.train_mask, data.val_mask, data.test_mask]:
          accs.append(
              int((pred[mask] == data.y[mask]).sum()) / int(mask.sum())
          )
      return accs
  
file_path: pytorch_geometric/examples/mixhop.py
imports: import os.path
  import torch
  import torch.nn.functional
  from torch_geometric.datasets import Planetoid
  from torch_geometric.nn import BatchNorm, Linear, MixHopConv
label_desc: Use image node_id 2 for calling a global function with example usage: test() and returns: accs