code: def disk(radius, alias_blur=0.1, dtype=np.float32):
      """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.
      """
      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
      )
  
imports: import io
  import subprocess
  import tempfile
  import numpy
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
  import tensorflow_datasets.public_api
label_desc: Use image node_id 3 for calling a global function with example usage: disk(radius, alias_blur, dtype) and returns: tfds