code: def get_data_for_fold(self, fold):
      domains = self.opt.get("math_dataset_domains", DOMAINS)
      convert = self.opt.get("math_latex_converter", False)
      extrinsic_step = self.opt.get("extrinsic_step", False)
      data = self.load_data(domains)
  
      if "test" not in self.datatype:
          # Synthetically split some of train out so we get a valid set.
          # MATHS has 7.5k train, 5k test, 12.5 total.
          split_size = len(data) // 10
          if "valid" in self.datatype:
              data = data[:split_size]
          elif "train" in self.datatype:
              data = data[split_size:]
          else:
              raise RuntimeError(
                  f"Not a viable datatype {self.datatype}!"
              )
  
      for problem in data:
          question = problem["problem"]
          answer_blob = problem["solution"]
          final_answer = self.get_boxed_answer(answer_blob)
          answer_blob = self._clean_steps(answer_blob)
          steps = answer_blob.split(". ")
          if extrinsic_step:
              random_step = self._find_nonempty_random_step(data)
          if convert:
              question = self._latex_conversion(question)
              final_answer = self._latex_conversion(final_answer)
              final_steps = []
              for step in steps:
                  final_steps.append(self._latex_conversion(step))
              if extrinsic_step:
                  random_step = self._latex_conversion(random_step)
          else:
              final_steps = steps
          while len(final_steps) > 0 and (
              final_steps[-1] == "" or final_steps[-1] == " "
          ):
              final_steps = final_steps[:-1]
          if extrinsic_step:
              yield {
                  "question": question,
                  "answer": final_answer,
                  "steps": final_steps,
                  "extrinsic_step": random_step,
              }
              continue
          yield {
              "question": question,
              "answer": final_answer,
              "steps": final_steps,
          }
  
imports: import glob
  import json
  import os
  import random
  import re
  from parlai.tasks.math_dataset.build import build
  from parlai.core.opt import Opt
  from parlai.core.params import ParlaiParser
  from parlai.utils.io import PathManager
  from typing import List, Optional
  from parlai.tasks.reasoning.agents import MWPStepsReasoningTeacher
label_desc: Use image node_id 4 for calling the MathDatasetStepByStepReasoningTeacher obj's underlying member method code with example usage: obj.get_data_for_fold(fold) without return types