code: def zoom_blur(x, severity=1):
      """Zoom blurring to images.
  
      Applying zoom blurring to images by zooming the central part of the 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 zoom blur.
      """
      c = [
          np.arange(1, 1.11, 0.01),
          np.arange(1, 1.16, 0.01),
          np.arange(1, 1.21, 0.02),
          np.arange(1, 1.26, 0.02),
          np.arange(1, 1.31, 0.03),
      ][severity - 1]
      x = (np.array(x) / 255.0).astype(np.float32)
      out = np.zeros_like(x)
      for zoom_factor in c:
          out += clipped_zoom(x, zoom_factor)
      x = (x + out) / (len(c) + 1)
      x_clip = np.clip(x, 0, 1) * 255
      return around_and_astype(x_clip)
  
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 11 for calling a global function with example usage: zoom_blur(x, severity) and returns: around_and_astype