class_docstr: Custom class used to adapt Omniglot (from Torchvision) and make it
  compatible with the Avalanche API.
class_docstr_tok: ["Custom","class","used","to","adapt","Omniglot","(","from","Torchvision",")","and","make","it","compatible","with","the","Avalanche","API","."]
code: def __init__(
      self,
      root: str,
      train: bool = True,
      transform: Optional[Callable] = None,
      target_transform: Optional[Callable] = None,
      download: bool = False,
  ) -> None:
      super().__init__(
          join(root, self.folder),
          download=download,
          transform=transform,
          target_transform=target_transform,
          background=train,
      )
  
      self.targets = [x[1] for x in self._flat_character_images]
  
imports: from os.path import join
  from typing import Optional, Callable
  from torchvision.datasets import Omniglot
label_desc: Use image node_id 1 to create a new Omniglot object from inherited base classes: OmniglotTorch with example: obj = Omniglot(root, train, transform, target_transform, download)