message: Fixed error in the example of image_gradients documentation
  image_gradients returns (dy, dx) rather than (dx, dy)
diff: @@ -4455,7 +4455,7 @@ def image_gradients(image):
  image = tf.reshape(tf.range(IMAGE_HEIGHT * IMAGE_WIDTH * CHANNELS,
  delta=1, dtype=tf.float32),
  shape=(BATCH_SIZE, IMAGE_HEIGHT, IMAGE_WIDTH, CHANNELS))
  - dx, dy = tf.image.image_gradients(image)
  + dy, dx = tf.image.image_gradients(image)
  print(image[0, :,:,0])
  tf.Tensor(
  [[ 0. 1. 2. 3. 4.]
  @@ -4463,14 +4463,14 @@ def image_gradients(image):
  [10. 11. 12. 13. 14.]
  [15. 16. 17. 18. 19.]
  [20. 21. 22. 23. 24.]], shape=(5, 5), dtype=float32)
  - print(dx[0, :,:,0])
  + print(dy[0, :,:,0])
  tf.Tensor(
  [[5. 5. 5. 5. 5.]
  [5. 5. 5. 5. 5.]
  [5. 5. 5. 5. 5.]
  [5. 5. 5. 5. 5.]
  [0. 0. 0. 0. 0.]], shape=(5, 5), dtype=float32)
  - print(dy[0, :,:,0])
  + print(dx[0, :,:,0])
  tf.Tensor(
  [[1. 1. 1. 1. 0.]
  [1. 1. 1. 1. 0.]
  