message: Adding examples for tf.image.random_flip_left_right and
  tf.image.random_flip_up_down usage.
diff: @@ -326,6 +326,26 @@ def random_flip_up_down(image, seed=None):
  With a 1 in 2 chance, outputs the contents of `image` flipped along the first
  dimension, which is `height`. Otherwise output the image as-is.
  + When passing a batch of images, each image will be randomly flipped
  + independent of other images.
  +
  + Example usage:
  +
  + Randomly flip a single image.
  + >>> import numpy as np
  +
  + >>> image = np.array([[[1], [2]], [[3], [4]]])
  + >>> tf.image.random_flip_up_down(image, 3).numpy().tolist()
  + [[[3], [4]], [[1], [2]]]
  +
  + Randomly flip multiple images.
  + >>> images = np.array(
  + ... [
  + ... [[[1], [2]], [[3], [4]]],
  + ... [[[5], [6]], [[7], [8]]]
  + ... ])
  + >>> tf.image.random_flip_up_down(images, 4).numpy().tolist()
  + [[[[3], [4]], [[1], [2]]], [[[5], [6]], [[7], [8]]]]
  Args:
  image: 4-D Tensor of shape `[batch, height, width, channels]` or 3-D Tensor
  @@ -347,6 +367,25 @@ def random_flip_left_right(image, seed=None):
  With a 1 in 2 chance, outputs the contents of `image` flipped along the
  second dimension, which is `width`. Otherwise output the image as-is.
  + When passing a batch of images, each image will be randomly flipped
  + independent of other images.
  +
  + Example usage:
  + Randomly flip a single image.
  + >>> import numpy as np
  +
  + >>> image = np.array([[[1], [2]], [[3], [4]]])
  + >>> tf.image.random_flip_left_right(image, 5).numpy().tolist()
  + [[[2], [1]], [[4], [3]]]
  +
  + Randomly flip multiple images.
  + >>> images = np.array(
  + ... [
  + ... [[[1], [2]], [[3], [4]]],
  + ... [[[5], [6]], [[7], [8]]]
  + ... ])
  + >>> tf.image.random_flip_left_right(images, 6).numpy().tolist()
  + [[[[2], [1]], [[4], [3]]], [[[5], [6]], [[7], [8]]]]
  Args:
  image: 4-D Tensor of shape `[batch, height, width, channels]` or 3-D Tensor
  