code: def __init__(self, start, end):
      super().__init__()
      assert (
          end > start
      ), "this example code only works with end >= start"
      self.start = start
      self.end = end
      self.samples = list(range(self.start, self.end))
  
file_path: apex/tests/L0/run_transformer/test_batch_sampler.py
imports: import torch
  from torch.testing._internal import common_utils
  from torch.utils.data import Dataset
  from torch.utils.data import DataLoader
  from apex.transformer.pipeline_parallel.utils import _split_batch_into_microbatch
label_desc: Use image node_id 1 to create a new MyIterableDataset object from inherited base classes: Dataset with example: obj = MyIterableDataset(start, end)