code: def __init__(self, size=32, shape=(1,)):
      super(DummySequentialDataset, self).__init__()
      self.size = size
      self.shape = shape
  
imports: from __future__ import print_function
  from __future__ import division
  import mxnet
  import numpy
  import gluoncv
  from gluoncv.data.batchify import *
  from gluoncv.data import DetectionDataLoader, RandomTransformDataLoader
label_desc: Use image node_id 1 to create a new DummySequentialDataset object from inherited base classes: mx.gluon.data with example: obj = DummySequentialDataset(size, shape)