Method partial_run_setup

tensorflow/python/client/session.py:1023–1098

Sets up a graph with feeds and fetches for partial run. This is EXPERIMENTAL and subject to change. Note that contrary to `run`, `feeds` only specifies the graph elements. The tensors will be supplied by the subsequent `partial_run` calls. Args: fetches: A single graph eleme

(self, fetches, feeds=None)

    return self._run(handle, fetches, feed_dict, None, None)

  def partial_run_setup(self, fetches, feeds=None):
    """Sets up a graph with feeds and fetches for partial run.

    This is EXPERIMENTAL and subject to change.

    Note that contrary to `run`, `feeds` only specifies the graph elements.
    The tensors will be supplied by the subsequent `partial_run` calls.

    Args:
      fetches: A single graph element, or a list of graph elements.
      feeds: A single graph element, or a list of graph elements.

    Returns:
      A handle for partial run.

    Raises:
      RuntimeError: If this `Session` is in an invalid state (e.g. has been
        closed).
      TypeError: If `fetches` or `feed_dict` keys are of an inappropriate type.
      tf.errors.OpError: Or one of its subclasses if a TensorFlow error happens.
    """

    def _feed_fn(feed):
      for tensor_type, _, _, feed_fn in _REGISTERED_EXPANSIONS:
        if isinstance(feed, tensor_type):
          return feed_fn(feed)
      raise TypeError('Feed argument %r has invalid type %r' %
                      (feed, type(feed)))

    # Check session.
    if self._closed:
      raise RuntimeError('Attempted to use a closed Session.')
    if self.graph.version == 0:
      raise RuntimeError('The Session graph is empty.  Add operations to the '
                         'graph before calling run().')

    if feeds is None:
      feeds = []
    # Create request.
    feed_list = []

    # Validate and process feed_list.
    is_list_feed = isinstance(feeds, (list, tuple))
    if not is_list_feed:
      feeds = [feeds]
    for feed in feeds:
      for subfeed in _feed_fn(feed):
        try:
          subfeed_t = self.graph.as_graph_element(
              subfeed, allow_tensor=True, allow_operation=False)
          # pylint: disable=protected-access
          feed_list.append(subfeed_t._as_tf_output())
          # pylint: enable=protected-access
        except Exception as e:
          e.message = ('Cannot interpret feed_list key as Tensor: ' + e.message)
          e.args = (e.message,)
          raise e