code: def get_data(dataset):
      from bigdl.dllib.feature.dataset import mnist
  
      (images_data, labels_data) = mnist.read_data_sets(
          "/tmp/mnist", dataset
      )
      images_data = (images_data - mnist.TRAIN_MEAN) / mnist.TRAIN_STD
      return (images_data, labels_data.astype(np.int32))
  
file_path: BigDL/python/orca/example/tfpark/estimator/estimator_dataset.py
imports: import tensorflow
  import numpy
  from bigdl.dllib.nncontext import init_nncontext
  from bigdl.orca.tfpark import TFDataset, TFEstimator
  from bigdl.orca.tfpark import ZooOptimizer
  from bigdl.dllib.utils.common import *
  from bigdl.dllib.utils.log4Error import invalidInputError
  import os
  import argparse
label_desc: Use image node_id 1 for calling a global function with example usage: get_data(dataset) and returns: images_data,  labels_data