code: def download(self):
      import zipfile
      import shutil
  
      if self._check_integrity():
          return
  
      for name in self.zips_md5:
          zip_filename = "{0}.zip".format(name)
          filename = os.path.join(self.root, zip_filename)
          if os.path.isfile(filename):
              continue
  
          url = "{0}/{1}".format(self.download_url_prefix, zip_filename)
          download_url(
              url, self.root, zip_filename, self.zips_md5[name]
          )
  
          with zipfile.ZipFile(filename, "r") as f:
              f.extractall(self.root)
  
      filename = os.path.join(self.root, self.filename)
      with h5py.File(filename, "w") as f:
          for name in self.zips_md5:
              group = f.create_group(name)
  
              alphabets = list_dir(os.path.join(self.root, name))
              characters = [
                  (name, alphabet, character)
                  for alphabet in alphabets
                  for character in list_dir(
                      os.path.join(self.root, name, alphabet)
                  )
              ]
  
              split = "train" if name == "images_background" else "test"
              labels_filename = os.path.join(
                  self.root, self.filename_labels.format("", split)
              )
              with open(labels_filename, "w") as f_labels:
                  labels = sorted(characters)
                  json.dump(labels, f_labels)
  
              for _, alphabet, character in characters:
                  filenames = glob.glob(
                      os.path.join(
                          self.root, name, alphabet, character, "*.png"
                      )
                  )
                  dataset = group.create_dataset(
                      "{0}/{1}".format(alphabet, character),
                      (len(filenames), 105, 105),
                      dtype="uint8",
                  )
  
                  for i, char_filename in enumerate(filenames):
                      image = Image.open(
                          char_filename, mode="r"
                      ).convert("L")
                      dataset[i] = ImageOps.invert(image)
  
              shutil.rmtree(os.path.join(self.root, name))
  
      for split in ["train", "val", "test"]:
          filename = os.path.join(
              self.root, self.filename_labels.format("vinyals_", split)
          )
          data = get_asset(
              self.folder, "{0}.json".format(split), dtype="json"
          )
  
          with open(filename, "w") as f:
              labels = sorted(
                  [
                      ("images_{0}".format(name), alphabet, character)
                      for (name, alphabets) in data.items()
                      for (alphabet, characters) in alphabets.items()
                      for character in characters
                  ]
              )
              json.dump(labels, f)
  
imports: import os
  import json
  import glob
  import h5py
  from PIL import Image, ImageOps
  from torchmeta.utils.data import Dataset, ClassDataset, CombinationMetaDataset
  from torchvision.datasets.utils import list_dir, download_url
  from torchmeta.datasets.utils import get_asset
label_desc: Use image node_id 8 for calling the OmniglotClassDataset obj's underlying member method code with example usage: obj.download() without return types