code: def __init__(
      self,
      *,
      interpolation: Union[
          InterpolationMode, int
      ] = InterpolationMode.NEAREST,
      fill: Union[_FillType, Dict[Union[Type, str], _FillType]] = None,
  ) -> None:
      super().__init__()
      self.interpolation = _check_interpolation(interpolation)
      self.fill = fill
      self._fill = _setup_fill_arg(fill)
  
imports: import math
  from typing import Any, Callable, Dict, List, Optional, Tuple, Type, Union
  import PIL.Image
  import torch
  from torch.utils._pytree import tree_flatten, tree_unflatten, TreeSpec
  from torchvision import transforms, tv_tensors
  from torchvision.transforms import _functional_tensor
  from torchvision.transforms.v2 import AutoAugmentPolicy, functional, InterpolationMode, Transform
  from torchvision.transforms.v2.functional._geometry import _check_interpolation
  from torchvision.transforms.v2.functional._meta import get_size
  from torchvision.transforms.v2.functional._utils import _FillType, _FillTypeJIT
  from ._utils import _get_fill, _setup_fill_arg, check_type, is_pure_tensor
label_desc: Use image node_id 1 to create a new _AutoAugmentBase object from inherited base classes: Transform with example: obj = _AutoAugmentBase()