code: def transform_files(self, file_paths: List[str]) -> List[str]:
      for dataset in ["training", "testing"]:
          labels, images = self.read_source_dataset(
              dataset, self.raw_dataset_dir
          )
          self.write_output_dataset(
              labels,
              images,
              os.path.join(self.raw_dataset_dir, dataset),
          )
      return super().transform_files(file_paths)
  
file_path: ludwig/ludwig/datasets/loaders/mnist.py
imports: import logging
  import os
  import struct
  from multiprocessing.pool import ThreadPool
  from typing import List, Optional
  import numpy
  import pandas
  import torch
  from ludwig.datasets.dataset_config import DatasetConfig
  from ludwig.datasets.loaders.dataset_loader import DatasetLoader
  from ludwig.utils.fs_utils import makedirs
label_desc: Use image node_id 2 for calling the MNISTLoader obj's underlying member method code with example usage: obj.transform_files(file_paths) and returns: super