import tensorflow as tf

                    self.names_ops = names_ops + ['norm_grads_q', 'norm_grads_policy', 'avg_norm_grads_f', 'avg_norm_k',
                                                  'avg_norm_g', 'avg_norm_k_dot_g', 'avg_norm_adj']

                self.train_model = train_model
                self.step_model = step_model
                self.step = step_model.step
                self.proba_step = step_model.proba_step
                self.initial_state = step_model.initial_state

                tf.global_variables_initializer().run(session=self.sess)

                self.summary = tf.summary.merge_all()

    def _train_step(self, obs, actions, rewards, dones, mus, states, masks, steps, writer=None):
        """
        applies a training step to the model

        :param obs: ([float]) The input observations
