message: [core API doc fixit] tf.image.sobel_edges; add examples.
diff: @@ -4515,6 +4515,33 @@ def image_gradients(image):
  def sobel_edges(image):
  """Returns a tensor holding Sobel edge maps.
  + Example usage:
  +
  + For general usage, `image` would be loaded from a file as below:
  +
  + ```python
  + image_bytes = tf.io.read_file(path_to_image_file)
  + image = tf.image.decode_image(image_bytes)
  + image = tf.cast(image, tf.float32)
  + image = tf.expand_dims(image, 0)
  + ```
  + But for demo purposes, we are using randomly generated values for `image`:
  +
  + >>> image = tf.random.uniform(
  + ... maxval=255, shape=[1, 28, 28, 3], dtype=tf.float32)
  + >>> sobel = tf.image.sobel_edges(image)
  + >>> sobel_y = np.asarray(sobel[0, :, :, :, 0]) # sobel in y-direction
  + >>> sobel_x = np.asarray(sobel[0, :, :, :, 1]) # sobel in x-direction
  +
  + For displaying the sobel results, PIL's [Image Module](
  + https://pillow.readthedocs.io/en/stable/reference/Image.html) can be used:
  +
  + ```python
  + # Display edge maps for the first channel (at index 0)
  + Image.fromarray(sobel_y[..., 0] / 4 + 0.5).show()
  + Image.fromarray(sobel_x[..., 0] / 4 + 0.5).show()
  + ```
  +
  Arguments:
  image: Image tensor with shape [batch_size, h, w, d] and type float32 or
  float64. The image(s) must be 2x2 or larger.
  