code: def download(self):
      if self._check_integrity():
          return
      super(FC100ClassDataset, self).download()
  
      subfolder = os.path.join(self.root, self.subfolder)
      if not os.path.exists(subfolder):
          os.makedirs(subfolder)
  
      filename_fine_names = os.path.join(
          self.root, self.filename_fine_names
      )
      with open(filename_fine_names, "r") as f:
          fine_names = json.load(f)
  
      for split in ["train", "val", "test"]:
          split_filename_labels = os.path.join(
              subfolder, self.filename_labels.format(split)
          )
          if os.path.isfile(split_filename_labels):
              continue
  
          data = get_asset(
              self.folder,
              self.subfolder,
              "{0}.json".format(split),
              dtype="json",
          )
          with open(split_filename_labels, "w") as f:
              labels = [
                  [coarse_name, fine_name]
                  for coarse_name in data
                  for fine_name in fine_names[coarse_name]
              ]
              json.dump(labels, f)
  
file_path: pytorch-meta/torchmeta/datasets/cifar100/fc100.py
imports: import os
  import json
  from torchmeta.datasets.cifar100.base import CIFAR100ClassDataset
  from torchmeta.datasets.utils import get_asset
  from torchmeta.utils.data import ClassDataset, CombinationMetaDataset
label_desc: Use image node_id 2 for calling the FC100ClassDataset obj's underlying member method code with example usage: obj.download() without return types