message: Added example and description about numpy_function() in Dataset.map()
diff: @@ -1619,6 +1619,18 @@ name=None))
  >>> list(d.as_numpy_iterator())
  [b'HELLO', b'WORLD']
  + 3) Use `tf.numpy_function`, which allows you to write arbitrary python
  + code. Note here that `tf.py_function` accepts `tf.Tensor` whereas
  + `tf.numpy_function` accepts numpy arrays. For example:
  +
  + >>> d = tf.data.Dataset.from_tensor_slices(['hello', 'world'])
  + >>> def upper_case_fn(t: np.ndarray):
  + ... return t.decode('utf-8').upper()
  + >>> d = d.map(lambda x: tf.numpy_function(func=upper_case_fn,
  + ... inp=[x], Tout=tf.string))
  + >>> list(d.as_numpy_iterator())
  + [b'HELLO', b'WORLD']
  +
  Performance can often be improved by setting `num_parallel_calls` so that
  `map` will use multiple threads to process elements. If deterministic order
  isn't required, it can also improve performance to set
  