class_docstr: scale+rotation
class_docstr_tok: ["scale+rotation"]
code: def __init__(
      self,
      scale: Tuple[float, float] = None,  # e.g. (0.65, 1.35)
      rotation: Tuple[int, int] = None,  # e.g. (-45, 45)
      fixed_size: Tuple[int, int] = (256, 192),
  ):
      self.scale = scale
      self.rotation = rotation
      self.fixed_size = fixed_size
  
imports: import math
  import random
  from typing import Tuple
  import cv2
  import numpy
  import torch
  from torchvision.transforms import functional
  import matplotlib.pyplot
label_desc: Use image node_id 1 to create a new AffineTransform object from inherited base classes: object with example: obj = AffineTransform(scale, rotation, fixed_size)