code: def _generate_examples_validation(self, archive, labels):
      
      # Get the current random seeds.
      numpy_st0 = np.random.get_state()
      # Set new random seeds.
      np.random.seed(135)
      logging.warning('Overwriting cv2 RNG seed.')
      tfds.core.lazy_imports.cv2.setRNGSeed(357)
  
      for example in super(Imagenet2012Corrupted,
                           self)._generate_examples_validation(archive, labels):
        with tf.Graph().as_default():
          tf_img = tf.image.decode_jpeg(example['image'].read(), channels=3)
          image_np = tfds.as_numpy(tf_img)
        example['image'] = self._get_corrupted_example(image_np)
        yield example
      # Reset the seeds back to their original values.
      np.random.set_state(numpy_st0)
docs: Generate corrupted imagenet validation data.
  
      Apply corruptions to the raw images according to self.corruption_type.
  
      Args:
        archive: an iterator for the raw dataset.
        labels: a dictionary that maps the file names to imagenet labels.
  
      Yields:
        dictionary with the file name, an image file objective, and label of each
        imagenet validation data.