code: def __init__(self, mean=0, var=20):
      self.mean = mean
      if isinstance(var, numbers.Number):
          self.var = max(int(sample_asym(var)), 1)
      elif isinstance(var, (tuple, list)) and len(var) == 2:
          self.var = int(sample_uniform(var[0], var[1]))
      else:
          raise Exception("degree must be number or list with length 2")
  
imports: import math
  import numbers
  import random
  import cv2
  import numpy
  from paddle.vision.transforms import Compose, ColorJitter
label_desc: Use image node_id 1 to create a new CVGaussianNoise object from inherited base classes: object with example: obj = CVGaussianNoise(mean, var)