class_docstr: Teacher that builds up Message objects based on child `question and answer` and
  `reason` classes.
  
  Also handles making exemplars.
class_docstr_tok: ["Teacher","that","builds","up","Message","objects","based","on","child","`","question","and","answer","`","and","`","reason","`","classes",".","Also","handles","making","exemplars","."]
code: def _load_data_batch(
      self,
      example_batch: List[Dict],
      prompt_and_examplars: str,
      inner_separator: str,
  ) -> List[Message]:
      full_reason_texts = [None] * len(example_batch)
      if self.opt.get("include_reason", True):
          full_reason_texts = (
              self.reason_instance.batch_get_full_reason_text(
                  example_batch
              )
          )
      message_list = [
          self._message_from_example(
              example=example,
              prompt_and_examplars=prompt_and_examplars,
              inner_separator=inner_separator,
              reason_tuple=full_reason,
          )
          for example, full_reason in zip(
              example_batch, full_reason_texts
          )
      ]
      return message_list
  
imports: from parlai.core.opt import Opt
  from parlai.core.message import Message
  from parlai.core.params import ParlaiParser
  from parlai.core.teachers import DialogTeacher
  from tqdm import tqdm
  from typing import Any, Dict, Iterable, List, Optional, Tuple
label_desc: Use image node_id 12 for calling the AbstractReasoningTeacher obj's underlying member method code with example usage: obj._load_data_batch(example_batch, prompt_and_examplars, inner_separator) and returns: message_list