class_docstr: Adds random shade to the input image
  
  >>> import torch
  >>> from doctr.transforms import RandomShadow
  >>> transfo = RandomShadow((0., 1.))
  >>> out = transfo(torch.rand((3, 64, 64)))
  
  Args:
  ----
      opacity_range : minimum and maximum opacity of the shade
class_docstr_tok: ["Adds","random","shade","to","the","input","image",">",">",">","import","torch",">",">",">","from","doctr.transforms","import","RandomShadow",">",">",">","transfo","=","RandomShadow","(","(","0.",",","1",".",")",")",">",">",">","out","=","transfo","(","torch.rand","(","(","3",",","64",",","64",")",")",")","Args",":","--","--","opacity_range",":","minimum","and","maximum","opacity","of","the","shade"]
code: def extra_repr(self) -> str:
      return f"opacity_range={self.opacity_range}"
  
imports: import math
  from typing import Any, Dict, Optional, Tuple, Union
  import numpy
  import torch
  from PIL.Image import Image
  from torch.nn.functional import pad
  from torchvision.transforms import functional
  from torchvision.transforms import transforms
  from ..functional.pytorch import random_shadow
label_desc: Use image node_id 3 for calling the RandomShadow obj's underlying member method code with example usage: obj.extra_repr() and returns: str, self