parameters: (self, sess, save_path)
docstring: Restores previously saved variables.
  
      This method runs the ops added by the constructor for restoring variables.
      It requires a session in which the graph was launched.  The variables to
      restore do not have to have been initialized, as restoring is itself a way
      to initialize variables.
  
      The `save_path` argument is typically a value previously returned from a
      `save()` call, or a call to `latest_checkpoint()`.
  
      Args:
        sess: A `Session` to use to restore the parameters.
        save_path: Path where parameters were previously saved.
  
      Raises:
        ValueError: If save_path is None.
docstring_summary: Restores previously saved variables.
docstring_tokens: Restores previously saved variables .
function: def restore(self, sess, save_path):
      """Restores previously saved variables.
  
      This method runs the ops added by the constructor for restoring variables.
      It requires a session in which the graph was launched.  The variables to
      restore do not have to have been initialized, as restoring is itself a way
      to initialize variables.
  
      The `save_path` argument is typically a value previously returned from a
      `save()` call, or a call to `latest_checkpoint()`.
  
      Args:
        sess: A `Session` to use to restore the parameters.
        save_path: Path where parameters were previously saved.
  
      Raises:
        ValueError: If save_path is None.
      """
      if self._is_empty:
        return
      if save_path is None:
        raise ValueError("Can't load save_path when it is None.")
      logging.info("Restoring parameters from %s", save_path)
      sess.run(self.saver_def.restore_op_name,
               {self.saver_def.filename_tensor_name: save_path})
function_tokens: def restore ( self , sess , save_path ) : if self . _is_empty : return if save_path is None : raise ValueError ( "Can't load save_path when it is None." ) logging . info ( "Restoring parameters from %s" , save_path ) sess . run ( self . saver_def . restore_op_name , { self . saver_def . filename_tensor_name : save_path } )