import tensorflow as tf

    random_tensor = (1.0 - self._dropout_keep_prob +
                     tf.random_uniform(tf.shape(confidence_scores)))
    binary_tensor = -50.0 * tf.floor(random_tensor)

    csshape = confidence_scores.get_shape()
    self.cs = tf.nn.softmax(tf.constant(1.0, shape=csshape))

    # The final prediction is the average of the predictions for each word
    # weighted by the individual confidence/utility scores.

