code: def gaussian_blur(x, severity=1):
      """Apply gaussian blur to images.
  
      Args:
        x: numpy array, uncorrupted image, assumed to have uint8 pixel in [0,255].
        severity: integer, severity of corruption.
  
      Returns:
        numpy array, image with uint8 pixels in [0,255]. Applied gaussian blur.
      """
      c = [1, 2, 3, 4, 6][severity - 1]
  
      x = tfds.core.lazy_imports.skimage.filters.gaussian(
          np.array(x) / 255.0, sigma=c, channel_axis=-1
      )
      x = np.clip(x, 0, 1) * 255
  
      return around_and_astype(x)
  
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 21 for calling a global function with example usage: gaussian_blur(x, severity) and returns: around_and_astype