code: def test_len(self):
      from tests.helpers.datasets.torch_data import TorchNormalDataset
      from torch.utils.data import DataLoader
  
      bses = [8, 16, 40]
      all_sanity_batches = [4, 7, 10]
      length = []
      for bs in bses:
          for sanity_batches in all_sanity_batches:
              dataset = TorchNormalDataset(num_of_data=1000)
              dataloader = DataLoader(
                  dataset, batch_size=bs, shuffle=True
              )
              wrapper = _TruncatedDataLoader(
                  dataloader, num_batches=sanity_batches
              )
              length.append(len(wrapper))
      assert length == reduce(
          lambda x, y: x + y,
          [all_sanity_batches for _ in range(len(bses))],
      )
  
imports: from functools import reduce
  import pytest
  from fastNLP.core.controllers.utils.utils import _TruncatedDataLoader
  from tests.helpers.datasets.normal_data import NormalSampler
label_desc: Use image node_id 3 for calling the Test_WrapDataLoader obj's underlying member method code with example usage: obj.test_len() without return types