(self)
return softmax, state, lengths
Runs one batch of training data through the model.

    Uses a queue runner to pull one batch of data from the training files
    and run it through the model.

    Returns:
      A batch of softmax probabilities and model state vectors.
Runs one batch of training data through the model.
Runs one batch of training data through the model .
def run_training_batch(self):
    """Runs one batch of training data through the model.

    Uses a queue runner to pull one batch of data from the training files
    and run it through the model.

    Returns:
      A batch of softmax probabilities and model state vectors.
    """
    if self.training_file_list is None:
      tf.logging.warn('No training file path was provided, cannot run training'
                      'batch')
      return

    coord = tf.train.Coordinator()
    tf.train.start_queue_runners(sess=self.session, coord=coord)

    softmax, state, lengths = self.session.run([self.train_softmax,
                                                self.train_state,
                                                self.train_lengths])

    coord.request_stop()

    return softmax, state, lengths
def run_training_batch ( self ) : if self . training_file_list is None : tf . logging . warn ( 'No training file path was provided, cannot run training' 'batch' ) return coord = tf . train . Coordinator ( ) tf . train . start_queue_runners ( sess = self . session , coord = coord ) softmax , state , lengths = self . session . run ( [ self . train_softmax , self . train_state , self . train_lengths ] ) coord . request_stop ( ) return softmax , state , lengths