docstr: 测试 set_dist_repro_dataloader 中 dist 为 None、reproducible 为 True 时的表现
  当用户在 driver 之外初始化了分布式环境时，fastnlp 不支持进行断点重训，此时应该报错
docstr_tok: ["\u6d4b\u8bd5","set_dist_repro_dataloader","\u4e2d","dist","\u4e3a","None\u3001reproducible","\u4e3a","True","\u65f6\u7684\u8868\u73b0","\u5f53\u7528\u6237\u5728","driver","\u4e4b\u5916\u521d\u59cb\u5316\u4e86\u5206\u5e03\u5f0f\u73af\u5883\u65f6\uff0cfastnlp","\u4e0d\u652f\u6301\u8fdb\u884c\u65ad\u70b9\u91cd\u8bad\uff0c\u6b64\u65f6\u5e94\u8be5\u62a5\u9519"]
code: def test_with_dist_none_reproducible_true(self):
      """
      测试 set_dist_repro_dataloader 中 dist 为 None、reproducible 为 True 时的表现
      当用户在 driver 之外初始化了分布式环境时，fastnlp 不支持进行断点重训，此时应该报错
      """
      dataloader = DataLoader(self.dataset, batch_size=4, shuffle=True)
      with pytest.raises(RuntimeError):
          # 应当抛出 RuntimeError
          replaced_loader = self.driver.set_dist_repro_dataloader(
              dataloader, None, True
          )
  
      dist.barrier()
  
imports: import pytest
  from pathlib import Path
  from fastNLP.core.drivers.paddle_driver.fleet import PaddleFleetDriver
  from fastNLP.core.samplers import RandomSampler, UnrepeatedSampler, BucketedBatchSampler, UnrepeatedRandomSampler, UnrepeatedSequentialSampler
  from tests.helpers.models.paddle_model import PaddleNormalModel_Classification_1
  from tests.helpers.datasets.paddle_data import PaddleNormalDataset, PaddleNormalXYDataset
  from tests.helpers.utils import magic_argv_env_context, recover_logger
  from fastNLP.envs.distributed import rank_zero_rm
  from fastNLP import prepare_paddle_dataloader
  from fastNLP.core.drivers.paddle_driver.dist_utils import fastnlp_paddle_all_gather
  from fastNLP.envs.imports import _NEED_IMPORT_PADDLE
  from fastNLP import logger
label_desc: Use image node_id 5 for calling the TestSetDistReproDataloader obj's underlying member method code with example usage: obj.test_with_dist_none_reproducible_true() without return types