code: def __init__(self, batch_size, data_shape, batches=100):
      super(DummyIter, self).__init__(batch_size)
      self.data_shape = (batch_size,) + data_shape
      self.label_shape = (batch_size,)
      self.provide_data = [("data", self.data_shape)]
      self.provide_label = [("softmax_label", self.label_shape)]
      self.batch = mx.io.DataBatch(
          data=[mx.nd.zeros(self.data_shape)],
          label=[mx.nd.zeros(self.label_shape)],
      )
      self._batches = 0
      self.batches = batches
  
imports: import os
  import random
  import tarfile
  import logging
  import tarfile
  import mxnet
  from mxnet.test_utils import get_cifar10
  from mxnet.gluon.data.vision import ImageFolderDataset
  from mxnet.gluon.data import DataLoader
  from mxnet.contrib.io import DataLoaderIter
label_desc: Use image node_id 1 to create a new DummyIter object from inherited base classes: mx.io with example: obj = DummyIter(batch_size, data_shape, batches)