import tensorflow as tf


    Get the cross-entropy for each example in the vector self._xent.

    Args:
      in_size: size of the hidden state vectors
      mats: list of hidden state vectors
    """
    pred_mat = tf.get_variable('pred_mat',
                               [in_size, self._out_vocab_size])
    pred_bias = tf.get_variable('pred_bias', [self._out_vocab_size])

    # Make a prediction on every word.
    def GetWordPred(o_):
      logits = tf.nn.xw_plus_b(o_, pred_mat, pred_bias)
