code: def describe(self) -> str:
      return (
          "Accepts ``PIL.Image``, batched ``(B, C, H, W)`` and single ``(C, H, W)`` image ``torch.Tensor`` objects. "
          f"The images are resized to ``resize_size={self.resize_size}`` using ``interpolation={self.interpolation}``. "
          f"Finally the values are first rescaled to ``[0.0, 1.0]`` and then normalized using ``mean={self.mean}`` and "
          f"``std={self.std}``."
      )
  
file_path: vision/torchvision/prototype/transforms/_presets.py
imports: from typing import List, Optional, Tuple, Union
  import PIL.Image
  import torch
  from torch import Tensor
  from torchvision.transforms.v2 import functional, InterpolationMode
  from torchvision.transforms.v2.functional._geometry import _check_interpolation
label_desc: Use image node_id 4 for calling the StereoMatching obj's underlying member method code with example usage: obj.describe() and returns: str, self, str, self, str, self, str, self, str