code: def __init__(self, num_of_data=100, reverse=False):
      self.data = np.arange(num_of_data)
      if reverse:
          self.data = self.data[::-1]
  
imports: import numpy
  import pytest
  from functools import partial
  from itertools import chain
  from copy import deepcopy
  from fastNLP.core.samplers.reproducible_sampler import RandomSampler, SortedSampler, SequentialSampler
  from tests.helpers.datasets.torch_data import TorchNormalDataset
label_desc: Use image node_id 1 to create a new DatasetWithVaryLength object  with example: obj = DatasetWithVaryLength(num_of_data, reverse)