message: Usable example added in extract_glimpses
  Added a visual example of extract_glimpses
diff: @@ -3681,17 +3681,24 @@ def extract_glimpse(
  Usage Example:
  ```python
  - BATCH_SIZE = 2
  - IMAGE_HEIGHT = 256
  - IMAGE_WIDTH = 256
  - CHANNELS = 3
  - GLIMPSE_SIZE = (24, 24)
  - image = tf.random.normal(shape=(BATCH_SIZE, IMAGE_HEIGHT,
  + BATCH_SIZE = 1
  + IMAGE_HEIGHT = 5
  + IMAGE_WIDTH = 5
  + CHANNELS = 1
  + GLIMPSE_SIZE = (3, 3)
  + image = tf.random.uniform(shape=(BATCH_SIZE, IMAGE_HEIGHT,
  IMAGE_WIDTH, CHANNELS) )
  - offsets = tf.random.uniform(shape=(BATCH_SIZE, 2))
  output = tf.image.extract_glimpse(image, size=GLIMPSE_SIZE,
  - offsets=offsets)
  - print(output.shape)
  + offsets=[[1, 1]], centered=False, normalized=False)
  + print(image)
  + <tf.Tensor: id=172, shape=(3, 3), dtype=float32, numpy=
  + array([[0.98461604, 0.14595735, 0.3296578 ],
  + [0.247967 , 0.17635965, 0.3487332 ],
  + [0.33684814, 0.971017 , 0.41953743]], dtype=float32)>
  + print(output)
  + tf.Tensor(
  + [[0.98461604 0.14595735]
  + [0.247967 0.17635965]], shape=(2, 2), dtype=float32)
  ```
  """
  return gen_image_ops.extract_glimpse(
  @@ -3762,19 +3769,25 @@ def extract_glimpse_v2(
  Usage Example:
  ```python
  - BATCH_SIZE = 2
  - IMAGE_HEIGHT = 256
  - IMAGE_WIDTH = 256
  - CHANNELS = 3
  - GLIMPSE_SIZE = (24, 24)
  - image = tf.random.normal(shape=(BATCH_SIZE, IMAGE_HEIGHT,
  + BATCH_SIZE = 1
  + IMAGE_HEIGHT = 5
  + IMAGE_WIDTH = 5
  + CHANNELS = 1
  + GLIMPSE_SIZE = (3, 3)
  + image = tf.random.uniform(shape=(BATCH_SIZE, IMAGE_HEIGHT,
  IMAGE_WIDTH, CHANNELS) )
  - offsets = tf.random.uniform(shape=(BATCH_SIZE, 2))
  output = tf.image.extract_glimpse(image, size=GLIMPSE_SIZE,
  - offsets=offsets)
  - print(output.shape)
  + offsets=[[1, 1]], centered=False, normalized=False)
  + print(image)
  + <tf.Tensor: id=172, shape=(3, 3), dtype=float32, numpy=
  + array([[0.98461604, 0.14595735, 0.3296578 ],
  + [0.247967 , 0.17635965, 0.3487332 ],
  + [0.33684814, 0.971017 , 0.41953743]], dtype=float32)>
  + print(output)
  + tf.Tensor(
  + [[0.98461604 0.14595735]
  + [0.247967 0.17635965]], shape=(2, 2), dtype=float32)
  ```
  -
  """
  return gen_image_ops.extract_glimpse(
  input=input,
  