code: def __init__(
      self, root, transform=None, target_transform=None, download=False
  ):
      self.root = root
      self.transform = transform
      self.target_transform = target_transform
  
      if not self._check_exists():
          if download:
              self.download()
          else:
              raise RuntimeError(
                  "Dataset not found."
                  + " You can use download=True to download it"
              )
  
      self.all_items = find_classes(
          os.path.join(self.root, self.processed_folder)
      )
      self.idx_classes = index_classes(self.all_items)
  
imports: import torchvision.transforms
  from PIL import Image
  import numpy
  import torch
  import torch.utils.data
  import os
  import os.path
  import errno
label_desc: Use image node_id 1 to create a new Omniglot object from inherited base classes: data with example: obj = Omniglot(root, transform, target_transform, download)