code: def __init__(
      self, crop_size, min_scale=-0.2, max_scale=0.5, stretch_prob=0.8
  ):
      super().__init__()
      self.crop_size = crop_size
      self.min_scale = min_scale
      self.max_scale = max_scale
      self.stretch_prob = stretch_prob
      self.resize_prob = 0.8
      self.max_stretch = 0.2
  
imports: import torch
  import torchvision.transforms
  import torchvision.transforms.functional
label_desc: Use image node_id 1 to create a new RandomResizeAndCrop object from inherited base classes: torch.nn with example: obj = RandomResizeAndCrop(crop_size, min_scale, max_scale, stretch_prob)