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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def frosted_glass_blur(x, severity=1):
 """Frosted glass blurring to images. Apply frosted glass blurring to images by shuffling pixels locally. 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 frosted glass blur. """

  # sigma, max_delta, iterations
  c = [(0.7, 1, 2), (0.9, 2, 1), (1, 2, 3), (1.1, 3, 2), (1.5, 4,
                                                          2)][severity - 1]
  x = np.uint8(
      tfds.core.lazy_imports.skimage.filters.gaussian(
          np.array(x) / 255., sigma=c[0], multichannel=True) * 255)

  # locally shuffle pixels
  for _ in range(c[2]):
    for h in range(x.shape[0] - c[1], c[1], -1):
      for w in range(x.shape[1] - c[1], c[1], -1):
        dx, dy = np.random.randint(-c[1], c[1], size=(2,))
        h_prime, w_prime = h + dy, w + dx
        # swap
        x[h, w], x[h_prime, w_prime] = x[h_prime, w_prime], x[h, w]
  x_clip = np.clip(
      tfds.core.lazy_imports.skimage.filters.gaussian(
          x / 255., sigma=c[0], multichannel=True), 0, 1)
  x_clip *= 255
  return around_and_astype(x_clip)