import tensorflow as tf

        flattened_filters = policy_utils.flatten(conv2)
        self.z = tf.layers.dense(inputs=flattened_filters,
                                 units=256,
                                 activation=tf.nn.elu)

    def build_manager(self):
        with tf.variable_scope('manager'):
            # Calculate manager internal state
            self.s = tf.layers.dense(inputs=self.z,
                                     units=self.g_dim,
                                     activation=tf.nn.elu)

            # Calculate manager output g
            x = tf.expand_dims(self.s, [0])
            self.manager_lstm = SingleStepLSTM(x,
                                               self.g_dim,
