code: def __init__(self, params: CrossFoldTrainerParams):
      self.params = params
      # locate the training script (must be in the same dir as "this")
      self.train_script_path = os.path.abspath(
          os.path.join(
              this_absdir, "../..", "scripts", "train_from_params.py"
          )
      )
      self.cf_split_script_path = os.path.abspath(
          os.path.join(
              this_absdir, "standalone_cross_fold_split_script.py"
          )
      )
      # location of best models output
      if not os.path.exists(self.params.best_models_dir):
          os.makedirs(self.params.best_models_dir)
  
      if not os.path.exists(self.train_script_path):
          raise FileNotFoundError(
              "Missing train script path. Expected 'train.py' at {}".format(
                  self.train_script_path
              )
          )
  
      if not isinstance(self.params.trainer, TrainerParams):
          raise TypeError("Train args must be type of TrainerParams")
  
imports: import inspect
  import json
  import logging
  import multiprocessing
  import os
  import sys
  import tempfile
  from copy import deepcopy
  from dataclasses import dataclass, field
  from subprocess import check_call
  from typing import Optional, List
  from paiargparse import pai_dataclass, pai_meta
  from tfaip.util.tfaipargparse import post_init
  from calamari_ocr.ocr import CrossFold, SavedCalamariModel
  from calamari_ocr.ocr.dataset.datareader.hdf5.reader import Hdf5
  from calamari_ocr.ocr.scenario import CalamariScenario
  from calamari_ocr.ocr.training.params import TrainerParams, CalamariDefaultTrainerPipelineParams
  from calamari_ocr.utils.multiprocessing import prefix_run_command, run
label_desc: Use image node_id 1 to create a new CrossFoldTrainer object  with example: obj = CrossFoldTrainer(params)