class_docstr: Implementation of random rotation.
  
  Randomly rotates an input image by a fixed angle. By default, we rotate
  the image by 90 degrees with a probability of 50%.
  
  This augmentation can be very useful for rotation invariant images such as
  in medical imaging or satellite imaginary.
  
  Attributes:
      prob:
          Probability with which image is rotated.
      angle:
          Angle by which the image is rotated. We recommend multiples of 90
          to prevent rasterization artifacts. If you pick numbers like
          90, 180, 270 the tensor will be rotated without introducing
          any artifacts.
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code: def __init__(self, prob: float = 0.5, angle: int = 90):
      self.prob = prob
      self.angle = angle
  
file_path: lightly/lightly/transforms/rotation.py
imports: from typing import Tuple, Union
  import numpy
  import torchvision.transforms
  from PIL.Image import Image
  from torch import Tensor
  from torchvision.transforms import functional
label_desc: Use image node_id 1 to create a new RandomRotate object  with example: obj = RandomRotate(prob, angle)