old_contents: import unittest
  
  import tensorflow as tf
  import tensorflow_addons as tfa
  
  
  class TestTensorflowAddons(unittest.TestCase):
      def test_tfa_image(self):
          img_raw = tf.io.read_file('/input/tests/data/dot.png')
          img = tf.io.decode_image(img_raw)
          img = tf.image.convert_image_dtype(img, tf.float32)
          mean = tfa.image.mean_filter2d(img, filter_shape=1)
  
          self.assertEqual(1, len(mean))
new_contents: import unittest
  
  import numpy as np
  import tensorflow as tf
  import tensorflow_addons as tfa
  
  
  class TestTensorflowAddons(unittest.TestCase):
      def test_tfa_image(self):
          img_raw = tf.io.read_file('/input/tests/data/dot.png')
          img = tf.io.decode_image(img_raw)
          img = tf.image.convert_image_dtype(img, tf.float32)
          mean = tfa.image.mean_filter2d(img, filter_shape=1)
  
          self.assertEqual(1, len(mean))
      
      # This test exercises TFA Custom Op. See: b/145555176
      def test_gelu(self):
          x = tf.constant([[0.5, 1.2, -0.3]])
          layer = tfa.layers.GELU()
          result = layer(x)
  
          self.assertEqual((1, 3), result.shape)
subject: Add a test exercising TFA custom op.