code: def disk(radius, alias_blur=0.1, dtype=np.float32):
    
    if radius <= 8:
      length = np.arange(-8, 8 + 1)
      ksize = (3, 3)
    else:
      length = np.arange(-radius, radius + 1)
      ksize = (5, 5)
    x_axis, y_axis = np.meshgrid(length, length)
    aliased_disk = np.array((x_axis**2 + y_axis**2) <= radius**2, dtype=dtype)
    aliased_disk /= np.sum(aliased_disk)
    # supersample disk to antialias
    return tfds.core.lazy_imports.cv2.GaussianBlur(
        aliased_disk, ksize=ksize, sigmaX=alias_blur)
docs: Generating a Gaussian blurring kernel with disk shape.
  
    Generating a Gaussian blurring kernel with disk shape using cv2 API.
  
    Args:
      radius: integer, radius of blurring kernel.
      alias_blur: float, standard deviation of Gaussian blurring.
      dtype: data type of kernel
  
    Returns:
      cv2 object of the Gaussian blurring kernel.