def as_default(self):
    """Returns a context manager that makes this object the default session.

    Use with the `with` keyword to specify that calls to
    @{tf.Operation.run} or @{tf.Tensor.eval} should be executed in
    this session.

    ```python
    c = tf.constant(..)
    sess = tf.Session()

    with sess.as_default():
      assert tf.get_default_session() is sess
      print(c.eval())
    ```

    To get the current default session, use @{tf.get_default_session}.

    *N.B.* The `as_default` context manager *does not* close the
    session when you exit the context, and you must close the session
    explicitly.

    ```python
    c = tf.constant(...)
    sess = tf.Session()
    with sess.as_default():
      print(c.eval())
    # ...
    with sess.as_default():
      print(c.eval())

    sess.close()
    ```

    Alternatively, you can use `with tf.Session():` to create a
    session that is automatically closed on exiting the context,
    including when an uncaught exception is raised.

    *N.B.* The default session is a property of the current thread. If you
    create a new thread, and wish to use the default session in that
    thread, you must explicitly add a `with sess.as_default():` in that
    thread's function.

    *N.B.* Entering a `with sess.as_default():` block does not affect
    the current default graph. If you are using multiple graphs, and
    `sess.graph` is different from the value of @{tf.get_default_graph},
    you must explicitly enter a `with sess.graph.as_default():` block
    to make `sess.graph` the default graph.

    Returns:
      A context manager using this session as the default session.
    """
    return ops.default_session(self)

  def as_default(self):
    """Returns a context manager that makes this object the default session.

    Use with the `with` keyword to specify that calls to
    [`Operation.run()`](../../api_docs/python/framework.md#Operation.run) or
    [`Tensor.eval()`](../../api_docs/python/framework.md#Tensor.eval) should be
    executed in this session.

    ```python
    c = tf.constant(..)
    sess = tf.Session()

    with sess.as_default():
      assert tf.get_default_session() is sess
      print(c.eval())
    ```

    To get the current default session, use
    [`tf.get_default_session()`](#get_default_session).


    *N.B.* The `as_default` context manager *does not* close the
    session when you exit the context, and you must close the session
    explicitly.

    ```python
    c = tf.constant(...)
    sess = tf.Session()
    with sess.as_default():
      print(c.eval())
    # ...
    with sess.as_default():
      print(c.eval())

    sess.close()
    ```

    Alternatively, you can use `with tf.Session():` to create a
    session that is automatically closed on exiting the context,
    including when an uncaught exception is raised.

    *N.B.* The default graph is a property of the current thread. If you
    create a new thread, and wish to use the default session in that
    thread, you must explicitly add a `with sess.as_default():` in that
    thread's function.

    Returns:
      A context manager using this session as the default session.

    """
    return ops.default_session(self)

 def as_default(self):
   return ops.default_session(self)

  def as_default(self):
    """Returns a context manager that makes this object the default session.

    Use with the `with` keyword to specify that calls to
    [`Operation.run()`](../../api_docs/python/framework.md#Operation.run) or
    [`Tensor.run()`](../../api_docs/python/framework.md#Tensor.run) should be
    executed in this session.

    ```python
    c = tf.constant(..)
    sess = tf.Session()

    with sess.as_default():
      assert tf.get_default_session() is sess
      print c.eval()
    ```

    To get the current default session, use
    [`tf.get_default_session()`](#get_default_session).


    *N.B.* The `as_default` context manager *does not* close the
    session when you exit the context, and you must close the session
    explicitly.

    ```python
    c = tf.constant(...)
    sess = tf.Session()
    with sess.as_default():
      print c.eval()
    # ...
    with sess.as_default():
      print c.eval()

    sess.close()
    ```

    Alternatively, you can use `with tf.Session():` to create a
    session that is automatically closed on exiting the context,
    including when an uncaught exception is raised.

    *N.B.* The default graph is a property of the current thread. If you
    create a new thread, and wish to use the default session in that
    thread, you must explicitly add a `with sess.as_default():` in that
    thread's function.

    Returns:
      A context manager using this session as the default session.

    """
    return ops.default_session(self)

  # Eventually, this registration could be opened up to support custom
  # Tensor expansions. Expects tuples of (Type, fetch_fn, feed_fn),
  # where the signatures are:
  #   fetch_fn : Type -> (list of Tensors,
  #                       lambda: list of fetched np.ndarray -> TypeVal)
  #   feed_fn  : Type, TypeVal -> list of (Tensor, value)
  # Conceptually, fetch_fn describes how to expand fetch into its
  # component Tensors and how to contracting the fetched results back into
  # a single return value. feed_fn describes how to unpack a single fed
  #