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: 将所有的 dataset 中名为 ``field_name`` 的 Field 复制一份并命名为 ``new_field_name``。
  
  :param field_name:
  :param new_field_name:
  :param ignore_miss_dataset: 如果为 ``True`` ，则当 ``field_name`` 在某个 dataset 内不存在时，直接忽略该 dataset，
      如果为 ``False`` 则会报错。
  :return: self
docstr_tok: ["\u5c06\u6240\u6709\u7684","dataset","\u4e2d\u540d\u4e3a","``","field_name","``","\u7684","Field","\u590d\u5236\u4e00\u4efd\u5e76\u547d\u540d\u4e3a","``","new_field_name","``","\u3002",":","param","field_name",":",":","param","new_field_name",":",":","param","ignore_miss_dataset",":","\u5982\u679c\u4e3a","``","True","``","\uff0c\u5219\u5f53","``","field_name","``","\u5728\u67d0\u4e2a","dataset","\u5185\u4e0d\u5b58\u5728\u65f6\uff0c\u76f4\u63a5\u5ffd\u7565\u8be5","dataset\uff0c","\u5982\u679c\u4e3a","``","False","``","\u5219\u4f1a\u62a5\u9519\u3002",":","return",":","self"]
code: def copy_field(
      self,
      field_name: str,
      new_field_name: str,
      ignore_miss_dataset: bool = True,
  ):
      r"""
      将所有的 dataset 中名为 ``field_name`` 的 Field 复制一份并命名为 ``new_field_name``。
  
      :param field_name:
      :param new_field_name:
      :param ignore_miss_dataset: 如果为 ``True`` ，则当 ``field_name`` 在某个 dataset 内不存在时，直接忽略该 dataset，
          如果为 ``False`` 则会报错。
      :return: self
      """
      for name, dataset in self.datasets.items():
          if dataset.has_field(field_name=field_name):
              dataset.copy_field(
                  field_name=field_name, new_field_name=new_field_name
              )
          elif not ignore_miss_dataset:
              raise KeyError(f"{field_name} not found DataSet:{name}.")
      return self
  
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 12 for calling the DataBundle obj's underlying member method code with example usage: obj.copy_field(field_name, new_field_name, ignore_miss_dataset) and returns: self