code: def evaluate(labels, pred, train_idx, val_idx, test_idx, evaluator):
      return (
          evaluator(pred[train_idx], labels[train_idx]),
          evaluator(pred[val_idx], labels[val_idx]),
          evaluator(pred[test_idx], labels[test_idx]),
      )
  
file_path: dgl/examples/pytorch/ogb/ogbn-arxiv/correct_and_smooth.py
imports: import argparse
  import glob
  import numpy
  import torch
  import torch.nn.functional
  from dgl import function
  from ogb.nodeproppred import DglNodePropPredDataset, Evaluator
label_desc: Use image node_id 4 for calling a global function with example usage: evaluate(labels, pred, train_idx, val_idx, test_idx, evaluator) and returns: evaluator,  evaluator,  evaluator