import tensorflow as tf

    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 for each tweet.
    def GetWordPred(o_):
      logits = tf.nn.xw_plus_b(o_, pred_mat, pred_bias)
      return tf.nn.softmax(logits)

    preds = GetWordPred(wvsum)
    z = tf.tile(tf.reshape(tf.reduce_sum(preds,1),[-1,1]), [1, out_vocab_size])
    self.preds, self.z = preds, z
    self.probs = tf.div(preds, z) #normalize
