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:
              # TODO: Return the training document generator from `self.dataset`.
              # If you need to process the data, `map` over the documents with
              # the custom processing function, `self._process_doc`. E.g.
              # `map(self._process_doc, self.dataset["validation"])`
              # In most case you can leave this as is unless the dataset split is
              # named differently than the default `"train"`.
              self._training_docs = list(self.dataset["train"])
          return self._training_docs
  
file_path: lm-evaluation-harness/templates/new_task.py
imports: from lm_eval.base import Task
label_desc: Use image node_id 4 for calling the NewTask obj's underlying member method code with example usage: obj.training_docs() and returns: self