class_docstr: 执行 ``Jittor`` 框架下分布式训练的 ``Driver``。
  
  .. note::
  
      这是一个正在开发中的功能，敬请期待。
  
  .. todo:
  
      实现断点重训中替换 dataloader 的 set_dist_repro_dataloader 函数
class_docstr_tok: ["\u6267\u884c","``","Jittor","``","\u6846\u67b6\u4e0b\u5206\u5e03\u5f0f\u8bad\u7ec3\u7684","``","Driver","``","\u3002","..","note",":",":","\u8fd9\u662f\u4e00\u4e2a\u6b63\u5728\u5f00\u53d1\u4e2d\u7684\u529f\u80fd\uff0c\u656c\u8bf7\u671f\u5f85\u3002","..","todo",":","\u5b9e\u73b0\u65ad\u70b9\u91cd\u8bad\u4e2d\u66ff\u6362","dataloader","\u7684","set_dist_repro_dataloader","\u51fd\u6570"]
docstr: :return: 数据所在的设备。
docstr_tok: [":","return",":","\u6570\u636e\u6240\u5728\u7684\u8bbe\u5907\u3002"]
code: def data_device(self) -> str:
      """
      :return: 数据所在的设备。
      """
      return self.model_device
  
imports: import os
  from typing import Optional, Union, Callable, Dict, Tuple
  from .jittor_driver import JittorDriver
  from fastNLP.core.utils import auto_param_call
  from fastNLP.core.utils.utils import _get_fun_msg
  from fastNLP.envs.imports import _NEED_IMPORT_JITTOR
  from fastNLP.core.samplers import ReproducibleBatchSampler, ReproducibleSampler
  from fastNLP.core.log import logger
label_desc: Use image node_id 20 for calling the JittorMPIDriver obj's underlying member method code with example usage: obj.data_device() and returns: self