class_docstr: A dataset fetching the data in a meta-level.
  
  A Meta Dataset is responsible for
  
  - input tasks(e.g. Qlib tasks) and prepare meta tasks
  
      - meta task contains more information than normal tasks (e.g. input data for meta model)
  
  The learnt pattern could transfer to other meta dataset. The following cases should be supported
  
  - A meta-model trained on meta-dataset A and then applied to meta-dataset B
  
      - Some pattern are shared between meta-dataset A and B, so meta-input on meta-dataset A are used when meta model are applied on meta-dataset-B
docstr: prepare a single segment of data for training data
  
  Parameters
  ----------
  seg : Text
      the name of the segment
docstr_tok: ["prepare","a","single","segment","of","data","for","training","data","Parameters","--","--","--","--","--","seg",":","Text","the","name","of","the","segment"]
code: def _prepare_seg(self, segment: Text):
      """
      prepare a single segment of data for training data
  
      Parameters
      ----------
      seg : Text
          the name of the segment
      """
  
file_path: qlib/qlib/model/meta/dataset.py
imports: import abc
  from qlib.model.meta.task import MetaTask
  from typing import Dict, Union, List, Tuple, Text
  from ...utils.serial import Serializable
label_desc: Use image node_id 3 for calling the MetaTaskDataset obj's underlying member method code with example usage: obj._prepare_seg(segment) without return types