code: def load_data(
      self,
      hf_dataset: Dataset,
      question_column_name: str = "question",
      context_column_name: str = "context",
      answer_column_name: str = "answer",
  ) -> Dataset:
      column_names = hf_dataset.column_names
  
      if self.training or self.validating or self.testing:
          if (
              answer_column_name == "answer"
              and "answer" not in column_names
          ):
              if (
                  "answer_text" in column_names
                  and "answer_start" in column_names
              ):
                  hf_dataset = hf_dataset.map(
                      self._reshape_answer_column, batched=False
                  )
              else:
                  raise KeyError(
                      """Dataset must contain either \"answer\" key as dict type or "answer_text" and
                              "answer_start" as string and integer types."""
                  )
          if not isinstance(hf_dataset[answer_column_name][0], Dict):
              raise TypeError(
                  f'{answer_column_name} column should be of type dict with keys "text" and "answer_start"'
              )
  
          if (
              answer_column_name in column_names
              and answer_column_name != "answer"
          ):
              hf_dataset = hf_dataset.rename_column(
                  answer_column_name, "answer"
              )
  
      if (
          question_column_name in column_names
          and question_column_name != "question"
      ):
          hf_dataset = hf_dataset.rename_column(
              question_column_name, "question"
          )
  
      if (
          context_column_name in column_names
          and context_column_name != "context"
      ):
          hf_dataset = hf_dataset.rename_column(
              context_column_name, "context"
          )
  
      if flash._IS_TESTING:
          # NOTE: must subset in this way to return a Dataset
          hf_dataset = list(hf_dataset)[:40]
  
      return hf_dataset
  
imports: import json
  from pathlib import Path
  from typing import Any, Dict
  import flash
  from flash.core.data.io.input import Input
  from flash.core.data.utilities.loading import load_data_frame
  from flash.core.data.utilities.paths import PATH_TYPE
  from flash.core.utilities.imports import _TOPIC_TEXT_AVAILABLE, requires
label_desc: Use image node_id 2 for calling the QuestionAnsweringInputBase obj's underlying member method code with example usage: obj.load_data(hf_dataset, question_column_name, context_column_name, answer_column_name) and returns: hf_dataset