class_docstr: 经过处理的数据信息，包括一系列数据集（比如：分开的训练集、验证集和测试集）以及各个 field 对应的 vocabulary。该对象一般由
  **fastNLP** 中各种 :class:`~fastNLP.io.loader.Loader` 的 :meth:`load` 函数生成，可以通过以下的方法获取里面的内容::
  
      data_bundle = YelpLoader().load({'train':'/path/to/train', 'dev': '/path/to/dev'})
      train_vocabs = data_bundle.vocabs['train']
      train_data = data_bundle.datasets['train']
      dev_data = data_bundle.datasets['train']
  
  :param vocabs: 从名称（字符串）到 :class:`~fastNLP.core.Vocabulary` 类型的字典
  :param datasets: 从名称（字符串）到 :class:`~fastNLP.core.dataset.DataSet` 类型的字典。建议不要将相同的 ``DataSet`` 对象重复传入，
      否则可能会在使用 :class:`~fastNLP.io.pipe.Pipe` 处理数据的时候遇到问题，若多个数据集确需一致，请手动 ``deepcopy`` 后传入。
docstr: 对 :class:`~fastNLP.io.DataBundle` 中所有的 dataset 使用 :meth:`~fastNLP.DataSet.apply_more` 方法
  
  .. note::
      ``apply_more`` 与 ``apply`` 的区别参考 :meth:`fastNLP.core.DataSet.apply_more` 中关于 ``apply_more`` 与
      ``apply`` 区别的介绍。
  
  :param func: 参数是 ``DataSet`` 中的 ``Instance`` ，返回值是一个字典，key 是field 的名字，value 是对应的结果
  :param modify_fields: 是否用结果修改 ``DataSet`` 中的 ``Field`` ， 默认为 ``True``
  :param num_proc: 使用进程的数量。
  
      .. note::
  
          由于 ``python`` 语言的特性，设置该参数后会导致相应倍数的内存增长，这可能会对您程序的执行带来一定的影响。另外，使用多进程时，
          ``func`` 函数中的打印将不会输出。
  
  :param progress_desc: 当 progress_bar 不为 ``None`` 时，可以显示当前正在处理的进度条名称
  :param progress_bar: 显示进度条的方式，支持 ``["rich", "tqdm", None]``。
  
  :return: 一个字典套字典，第一层的 key 是 dataset 的名字，第二层的 key 是 field 的名字
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code: def apply_more(
      self,
      func: Callable,
      modify_fields: bool = True,
      num_proc: int = 0,
      progress_desc: str = "",
      progress_bar: str = "rich",
  ):
      r"""
      对 :class:`~fastNLP.io.DataBundle` 中所有的 dataset 使用 :meth:`~fastNLP.DataSet.apply_more` 方法
  
      .. note::
          ``apply_more`` 与 ``apply`` 的区别参考 :meth:`fastNLP.core.DataSet.apply_more` 中关于 ``apply_more`` 与
          ``apply`` 区别的介绍。
  
      :param func: 参数是 ``DataSet`` 中的 ``Instance`` ，返回值是一个字典，key 是field 的名字，value 是对应的结果
      :param modify_fields: 是否用结果修改 ``DataSet`` 中的 ``Field`` ， 默认为 ``True``
      :param num_proc: 使用进程的数量。
  
          .. note::
  
              由于 ``python`` 语言的特性，设置该参数后会导致相应倍数的内存增长，这可能会对您程序的执行带来一定的影响。另外，使用多进程时，
              ``func`` 函数中的打印将不会输出。
  
      :param progress_desc: 当 progress_bar 不为 ``None`` 时，可以显示当前正在处理的进度条名称
      :param progress_bar: 显示进度条的方式，支持 ``["rich", "tqdm", None]``。
  
      :return: 一个字典套字典，第一层的 key 是 dataset 的名字，第二层的 key 是 field 的名字
      """
      res = {}
      _progress_desc = progress_desc
      for name, dataset in self.datasets.items():
          if len(_progress_desc) == 0:
              _progress_desc = "Processing"
          progress_desc = _progress_desc + f" for `{name}`"
          res[name] = dataset.apply_more(
              func,
              modify_fields=modify_fields,
              num_proc=num_proc,
              progress_bar=progress_bar,
              progress_desc=progress_desc,
          )
      return res
  
imports: from typing import Union, List, Callable, Dict
  from ..core.dataset import DataSet
  from fastNLP.core.vocabulary import Vocabulary
  from fastNLP.core import logger
label_desc: Use image node_id 22 for calling the DataBundle obj's underlying member method code with example usage: obj.apply_more(func, modify_fields, num_proc, progress_desc, progress_bar) and returns: res