code: def test_random_transform_dataloader():
      dataset = DummySequentialDataset(20)
      loader = RandomTransformDataLoader(
          dataset=dataset,
          shuffle=True,
          batch_size=4,
          transform_fns=[_fn0, _fn0],
          last_batch="keep",
          interval=1,
          num_workers=2,
      )
  
      for i in range(4):
          results = []
          for batch in loader:
              results += batch.asnumpy().astype("int").tolist()
              print(batch.asnumpy().astype("int").tolist())
  
          xx = np.sort(np.array(results).flatten())
          assert (xx == list(range(len(dataset)))).all(), "{}".format(
              xx
          )
  
      # sanity test for rollover
      for last_batch in ["rollover", "keep", "discard"]:
          loader = RandomTransformDataLoader(
              dataset=dataset,
              shuffle=True,
              batch_size=4,
              transform_fns=[_fn1, _fn2],
              last_batch=last_batch,
              interval=2,
              num_workers=2,
          )
          for i in range(4):
              results = []
              for batch in loader:
                  results += batch.asnumpy().astype("int").tolist()
  
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 5 for calling a global function with example usage: test_random_transform_dataloader() without return types