docstr: 测试 set_dist_repro_dataloader 中 dist 为 None、reproducible 为 False 、dataloader 为一般情况时的表现
  此时直接返回原来的 dataloader，不做任何处理。
docstr_tok: ["\u6d4b\u8bd5","set_dist_repro_dataloader","\u4e2d","dist","\u4e3a","None\u3001reproducible","\u4e3a","False","\u3001dataloader","\u4e3a\u4e00\u822c\u60c5\u51b5\u65f6\u7684\u8868\u73b0","\u6b64\u65f6\u76f4\u63a5\u8fd4\u56de\u539f\u6765\u7684","dataloader\uff0c\u4e0d\u505a\u4efb\u4f55\u5904\u7406\u3002"]
code: def test_with_dist_none_reproducible_false_dataloader_normal(
      self, shuffle
  ):
      """
      测试 set_dist_repro_dataloader 中 dist 为 None、reproducible 为 False 、dataloader 为一般情况时的表现
      此时直接返回原来的 dataloader，不做任何处理。
      """
      driver = generate_driver(10, 10, device=self.device)
      dataloader = DataLoader(
          self.dataset, batch_size=4, shuffle=shuffle
      )
      replaced_loader = driver.set_dist_repro_dataloader(
          dataloader, None, False
      )
  
      assert replaced_loader is dataloader
      comm.barrier()
  
imports: import os
  import sys
  import pytest
  from pathlib import Path
  from fastNLP.core.drivers.oneflow_driver.ddp import OneflowDDPDriver
  from fastNLP import prepare_oneflow_dataloader
  from fastNLP.core.samplers import RandomSampler, UnrepeatedSampler, BucketedBatchSampler, UnrepeatedRandomSampler, UnrepeatedSequentialSampler
  from tests.helpers.models.oneflow_model import OneflowNormalModel_Classification_1
  from tests.helpers.datasets.oneflow_data import OneflowNormalDataset, OneflowNormalXYDataset
  from tests.helpers.utils import recover_logger
  from fastNLP.envs.distributed import rank_zero_rm
  from fastNLP import logger
  from fastNLP.core.drivers.oneflow_driver.dist_utils import fastnlp_oneflow_all_gather
  from fastNLP.envs.imports import _NEED_IMPORT_ONEFLOW
label_desc: Use image node_id 8 for calling the TestSetDistReproDataloader obj's underlying member method code with example usage: obj.test_with_dist_none_reproducible_false_dataloader_normal(shuffle) without return types