code: def prepare_data(batch_size):
      train_data = gluon.data.DataLoader(
          gluon.data.vision.MNIST(
              "/tmp", train=True, transform=transformer
          ),
          batch_size=batch_size,
          shuffle=True,
          last_batch="discard",
      )
  
      val_data = gluon.data.DataLoader(
          gluon.data.vision.MNIST(
              "/tmp", train=False, transform=transformer
          ),
          batch_size=batch_size,
          shuffle=False,
      )
      return train_data, val_data
  
file_path: sagemaker-python-sdk/tests/data/mxnet_mnist/mnist_gluon.py
imports: import argparse
  import random
  import mxnet
  import numpy
  from mxnet import autograd, gluon
  from mxnet.gluon import nn
label_desc: Use image node_id 5 for calling a global function with example usage: prepare_data(batch_size) and returns: train_data,  val_data