code: def test_version_111(self):
      if parse_version(torch.__version__) <= parse_version("1.7"):
          pytest.skip("Torch version smaller than 1.7")
      logger.set_stdout()
      ds = DataSet(
          {
              "x": [[1, 2], [2, 3, 4], [4, 5, 6, 7]] * 10,
              "y": [1, 0, 1] * 10,
          }
      )
      with Capturing() as out:
          dl = TorchDataLoader(
              ds,
              batch_size=1,
              num_workers=0,
              prefetch_factor=2,
              generator=torch.Generator(),
              shuffle=False,
          )
          for idx, batch in enumerate(dl):
              assert len(batch["x"]) == 1
              assert batch["x"][0].tolist() == ds[idx]["x"]
  
      assert "Parameter:prefetch_factor" not in out[0]
  
file_path: fastNLP/tests/core/dataloaders/torch_dataloader/test_fdl.py
imports: import pytest
  from fastNLP.core.dataloaders.torch_dataloader import TorchDataLoader, prepare_torch_dataloader
  from fastNLP.core.dataset import DataSet
  from fastNLP.io.data_bundle import DataBundle
  from fastNLP.envs.imports import _NEED_IMPORT_TORCH
  from pkg_resources import parse_version
  from tests.helpers.utils import Capturing, recover_logger
  from fastNLP import logger
  import numpy
label_desc: Use image node_id 10 for calling the TestFdl obj's underlying member method code with example usage: obj.test_version_111() without return types