code: def evaluate(label, val_idx, test_idx, pred):
      # Compute accuracy on validation/test set.
      val_acc = (pred[val_idx] == label[val_idx]).float().mean()
      test_acc = (pred[test_idx] == label[test_idx]).float().mean()
      return val_acc, test_acc
  
imports: import pickle
  import dgl.sparse
  import torch
  import torch.nn
  import torch.nn.functional
  from dgl.data.utils import _get_dgl_url, download, get_download_dir
  from torch.optim import Adam
label_desc: Use image node_id 1 for calling a global function with example usage: evaluate(label, val_idx, test_idx, pred) and returns: val_acc,  test_acc