code: def prepare_pretrain_npz_dataset(filename, allow_pickle=False):
      """Create dataset based on the numpy npz file"""
      if isinstance(filename, (list, tuple)):
          assert len(filename) == 1, (
              "When .npy/.npz data file is loaded, len(filename) must be 1."
              " Received len(filename)={}.".format(len(filename))
          )
          filename = filename[0]
      logging.debug("start to load file %s ...", filename)
      return NumpyDataset(filename, allow_pickle=allow_pickle)
  
imports: import time
  import os
  import sys
  import logging
  import random
  import numpy
  import mxnet
  from mxnet.gluon.metric import EvalMetric
  import gluonnlp.data.batchify
  from gluonnlp.utils.misc import glob
  from gluonnlp.data.loading import NumpyDataset, DatasetLoader
  from gluonnlp.data.sampler import SplitSampler, FixedBucketSampler
  from create_pretraining_data import create_training_instances
label_desc: Use image node_id 1 for calling a global function with example usage: prepare_pretrain_npz_dataset(filename, allow_pickle) and returns: NumpyDataset