code: def test():
      model.eval()
      out, accs = model(data.x, data.edge_index), []
      for _, idx in data("train_idx", "val_idx", "test_idx"):
          pred = out[idx].argmax(1)
          acc = pred.eq(data.y[idx]).sum().item() / idx.numel()
          accs.append(acc)
      return accs
  
file_path: pytorch_geometric/examples/dna.py
imports: import os.path
  import torch
  import torch.nn.functional
  from sklearn.model_selection import StratifiedKFold
  from torch_geometric.datasets import Planetoid
  from torch_geometric.nn import DNAConv
label_desc: Use image node_id 3 for calling a global function with example usage: test() and returns: accs