code: def main():
      for split in ["train", "test"]:
          out_dir = f"cifar_{split}"
          if os.path.exists(out_dir):
              print(
                  f"skipping split {split} since {out_dir} already exists."
              )
              continue
  
          print("downloading...")
          with tempfile.TemporaryDirectory() as tmp_dir:
              dataset = torchvision.datasets.CIFAR10(
                  root=tmp_dir, train=split == "train", download=True
              )
  
          print("dumping images...")
          os.mkdir(out_dir)
          for i in tqdm(range(len(dataset))):
              image, label = dataset[i]
              filename = os.path.join(
                  out_dir, f"{CLASSES[label]}_{i:05d}.png"
              )
              image.save(filename)
  
imports: import os
  import tempfile
  import torchvision
  from tqdm.auto import tqdm
label_desc: Use image node_id 1 for calling a global function with example usage: main() without return types