docstr: 测试 set_dist_repro_dataloader 中 dist 为 None、reproducible 为 False 、dataloader 有 BucketedBatchSampler 
  时的表现
  此时传入的 dataloader 的 batch_sampler 应该已经执行了 set_distributed，产生一个新的 dataloader，其 batch_sampler
  和原 dataloader 相同
docstr_tok: ["\u6d4b\u8bd5","set_dist_repro_dataloader","\u4e2d","dist","\u4e3a","None\u3001reproducible","\u4e3a","False","\u3001dataloader","\u6709","BucketedBatchSampler","\u65f6\u7684\u8868\u73b0","\u6b64\u65f6\u4f20\u5165\u7684","dataloader","\u7684","batch_sampler","\u5e94\u8be5\u5df2\u7ecf\u6267\u884c\u4e86","set_distributed\uff0c\u4ea7\u751f\u4e00\u4e2a\u65b0\u7684","dataloader\uff0c\u5176","batch_sampler","\u548c\u539f","dataloader","\u76f8\u540c"]
code: def test_with_dist_none_reproducible_false_dataloader_reproducible_batch_sampler(
      self, shuffle
  ):
      """
      测试 set_dist_repro_dataloader 中 dist 为 None、reproducible 为 False 、dataloader 有 BucketedBatchSampler
      时的表现
      此时传入的 dataloader 的 batch_sampler 应该已经执行了 set_distributed，产生一个新的 dataloader，其 batch_sampler
      和原 dataloader 相同
      """
      driver = generate_driver(10, 10, device=self.device)
      dataloader = dataloader_with_bucketedbatchsampler(
          self.dataset, self.dataset._data, 4, shuffle, False
      )
      dataloader.batch_sampler.set_distributed(
          num_replicas=driver.world_size,
          rank=driver.global_rank,
          pad=True,
      )
      replaced_loader = driver.set_dist_repro_dataloader(
          dataloader, None, False
      )
  
      assert not (replaced_loader is dataloader)
      assert isinstance(
          replaced_loader.batch_sampler, BucketedBatchSampler
      )
      assert replaced_loader.batch_sampler.batch_size == 4
      self.check_distributed_sampler(dataloader.batch_sampler)
      self.check_set_dist_repro_dataloader(
          driver, dataloader, replaced_loader, shuffle
      )
  
      dist.barrier()
      if dist.is_initialized():
          dist.destroy_process_group()
  
imports: import os
  import pytest
  from pathlib import Path
  from fastNLP.core.drivers.torch_driver.ddp import TorchDDPDriver
  from fastNLP import prepare_torch_dataloader
  from fastNLP.core.samplers import RandomSampler, UnrepeatedSampler, BucketedBatchSampler, UnrepeatedRandomSampler, UnrepeatedSequentialSampler
  from tests.helpers.models.torch_model import TorchNormalModel_Classification_1
  from tests.helpers.datasets.torch_data import TorchNormalDataset, TorchNormalXYDataset
  from tests.helpers.utils import magic_argv_env_context, recover_logger, Capturing
  from fastNLP.envs.distributed import rank_zero_rm
  from fastNLP import logger
  from fastNLP.core.drivers.torch_driver.dist_utils import fastnlp_torch_all_gather
  from fastNLP.envs.imports import _NEED_IMPORT_TORCH
label_desc: Use image node_id 6 for calling the TestSetDistReproDataloader obj's underlying member method code with example usage: obj.test_with_dist_none_reproducible_false_dataloader_reproducible_batch_sampler(shuffle) without return types