class_docstr: Crop and/or pad image with random placement within the crop or pad margin.
      
class_docstr_tok: ["Crop","and\/or","pad","image","with","random","placement","within","the","crop","or","pad","margin","."]
code: def __init__(
      self,
      size: Union[int, List[int]],
      fill: Union[int, Tuple[int, int, int]] = 0,
      padding_mode: str = "constant",
  ):
      super().__init__()
      self.size = _setup_size(size)
      self.fill = fill
      self.padding_mode = padding_mode
  
imports: import math
  import numbers
  import random
  import warnings
  from typing import List, Sequence, Tuple, Union
  import torch
  import torchvision.transforms.functional
  from PIL import Image
  import numpy
label_desc: Use image node_id 1 to create a new RandomCropOrPad object from inherited base classes: torch.nn with example: obj = RandomCropOrPad(size, fill, padding_mode)