import tensorflow as tf


        self.updates = tf.group(denoise_updates, ranker_updates)

    def DenoisingNet(self, list_size, forward_only=False, scope=None):
        with tf.variable_scope(scope or "denoising_model"):
            # If we are in testing, do not compute propensity
            if forward_only:
                return tf.ones_like(self.output)#, tf.ones_like(self.output)
