code: def extra_repr(self) -> str:
      extra = []
      for name, value in self.__dict__.items():
          if name.startswith("_") or name == "training":
              continue
  
          if not isinstance(
              value, (bool, int, float, str, tuple, list, enum.Enum)
          ):
              continue
  
          extra.append(f"{name}={value}")
  
      return ", ".join(extra)
  
imports: from __future__ import annotations
  import enum
  from typing import Any, Callable, Dict, List, Optional, Tuple, Type, Union
  import PIL.Image
  import torch
  from torch import nn
  from torch.utils._pytree import tree_flatten, tree_unflatten
  from torchvision import tv_tensors
  from torchvision.transforms.v2._utils import check_type, has_any, is_pure_tensor
  from torchvision.utils import _log_api_usage_once
  from .functional._utils import _get_kernel
label_desc: Use image node_id 8 for calling the Transform obj's underlying member method code with example usage: obj.extra_repr() and returns: str