code: def create_dataset(input_folder: str, output_folder: str):
      """
      Read the dSprites dataset and split it into a training split and a validation split
      which follows the disk_folder format of VISSL
      """
      for split in ["train", "test"]:
          print(f"Processing '{split}' split...")
          dataset = StanfordCars(root=input_folder, split=split)
          mapper = StandfordCarsMapper(
              dataset, output_path=output_folder
          )
          mapper.init_folders()
          loader = DataLoader(
              mapper,
              num_workers=8,
              batch_size=1,
              collate_fn=lambda x: x[0],
          )
          with tqdm(total=len(dataset)) as progress_bar:
              for _ in loader:
                  progress_bar.update(1)
  
imports: import argparse
  import os
  import shutil
  from scipy import io
  from torch.utils.data import DataLoader
  from tqdm import tqdm
  from vissl.utils.download import download_and_extract_archive, download_url
  from vissl.utils.io import cleanup_dir
label_desc: Use image node_id 3 for calling a global function with example usage: create_dataset(input_folder, output_folder) without return types