code: def training_docs(self):
      if self.has_training_docs():
          # We cache training documents in `self._training_docs` for faster
          # few-shot processing. If the data is too large to fit in memory,
          # return the training data as a generator instead of a list.
          if self._training_docs is None:
              dataset = self._preprocess_dataset("train")
              self._training_docs = list(
                  map(self._process_doc, dataset)
              )
          return self._training_docs
  
file_path: lm-evaluation-harness/lm_eval/tasks/toxigen.py
imports: from lm_eval.base import MultipleChoiceTask
  import numpy
  import pandas
label_desc: Use image node_id 4 for calling the ToxiGen obj's underlying member method code with example usage: obj.training_docs() and returns: self