code: def test_single(self):
      num_of_data = 100
      data = DatasetWithVaryLength(num_of_data)
      sampler = SequentialSampler(data)
      indexes = list(sampler)
      assert indexes == list(range(num_of_data))
  
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 for calling the TestSequentialSampler obj's underlying member method code with example usage: obj.test_single() without return types