message: Remove a possible ambiguity in the `py_func` documentation.
diff: @@ -267,7 +267,7 @@ def py_func(func, inp, Tout, stateful=True, name=None):
  """Wraps a python function and uses it as a TensorFlow op.
  Given a python function `func`, which takes numpy arrays as its
  - inputs and returns numpy arrays as its outputs, wrap this function as an
  + arguments and returns numpy arrays as its outputs, wrap this function as an
  operation in a TensorFlow graph. The following snippet constructs a simple
  TensorFlow graph that invokes the `np.sinh()` NumPy function as a operation
  in the graph:
  @@ -276,8 +276,8 @@ def py_func(func, inp, Tout, stateful=True, name=None):
  def my_func(x):
  # x will be a numpy array with the contents of the placeholder below
  return np.sinh(x)
  - inp = tf.placeholder(tf.float32)
  - y = tf.py_func(my_func, [inp], tf.float32)
  + input = tf.placeholder(tf.float32)
  + y = tf.py_func(my_func, [input], tf.float32)
  ```
  **N.B.** The `tf.py_func()` operation has the following known limitations:
  @@ -293,10 +293,12 @@ def py_func(func, inp, Tout, stateful=True, name=None):
  server (e.g. using `with tf.device():`).
  Args:
  - func: A Python function, which accepts a list of NumPy `ndarray` objects
  - having element types that match the corresponding `tf.Tensor` objects
  - in `inp`, and returns a list of `ndarray` objects (or a single `ndarray`)
  - having element types that match the corresponding values in `Tout`.
  + func: A Python function, which accepts `ndarray` objects as arguments and
  + returns a list of `ndarray` objects (or a single `ndarray`). This function
  + must accept as many arguments as there are tensors in `inp`, and these
  + argument types will match the corresponding `tf.Tensor` objects
  + in `inp`. The returns `ndarray`s must match the number and types defined
  + `Tout`.
  Important Note: Input and output numpy `ndarray`s of `func` are not
  guaranteed to be copies. In some cases their underlying memory will be
  shared with the corresponding TensorFlow tensors.
  