(self, sess, input_feed, state_feed)
Runs one step of inference.

    Args:
      sess: TensorFlow Session object.
      input_feed: A numpy array of shape [batch_size].
      state_feed: A numpy array of shape [batch_size, state_size].

    Returns:
      softmax_output: A numpy array of shape [batch_size, vocab_size].
      new_state: A numpy array of shape [batch_size, state_size].
      metadata: Optional. If not None, a string containing metadata about the
        current inference step (e.g. serialized numpy array containing
        activations from a particular model layer.).
Runs one step of inference.
Runs one step of inference .
def inference_step(self, sess, input_feed, state_feed):
    """Runs one step of inference.

    Args:
      sess: TensorFlow Session object.
      input_feed: A numpy array of shape [batch_size].
      state_feed: A numpy array of shape [batch_size, state_size].

    Returns:
      softmax_output: A numpy array of shape [batch_size, vocab_size].
      new_state: A numpy array of shape [batch_size, state_size].
      metadata: Optional. If not None, a string containing metadata about the
        current inference step (e.g. serialized numpy array containing
        activations from a particular model layer.).
    """
    tf.logging.fatal("Please implement inference_step in subclass")
def inference_step ( self , sess , input_feed , state_feed ) : tf . logging . fatal ( "Please implement inference_step in subclass" )