code: def cost(self, logits, target):
      
      logits = tf.reshape(logits, [self._num_steps * self._batch_size, -1])
      target = tf.reshape(target, [self._num_steps * self._batch_size, -1])
      xent = tf.nn.softmax_cross_entropy_with_logits(logits=logits, labels=target)
      loss = tf.reduce_sum(xent)
  
      return loss / self._batch_size
docs: Returns cost.
  
      Args:
        logits: model output.
        target: target.
  
      Returns:
        Cross-entropy loss for a sequence of logits. The loss will be averaged
        across time steps if time_average_cost was enabled at construction time.