How to use the algorithms.common.abstract.agent.AbstractAgent.save_params function in algorithms

def save_params(self, n_episode: int):
        """Save model and optimizer parameters."""
        params = {
            "actor": self.actor.state_dict(),
            "qf_1": self.qf_1.state_dict(),
            "qf_2": self.qf_2.state_dict(),
            "vf": self.vf.state_dict(),
            "vf_target": self.vf_target.state_dict(),
            "actor_optim": self.actor_optimizer.state_dict(),
            "qf_1_optim": self.qf_1_optimizer.state_dict(),
            "qf_2_optim": self.qf_2_optimizer.state_dict(),
            "vf_optim": self.vf_optimizer.state_dict(),
        }

        AbstractAgent.save_params(self, params, n_episode)

def save_params(self, n_episode: int):
        """Save model and optimizer parameters."""
        params = {
            "actor": self.actor.state_dict(),
            "actor_target": self.actor_target.state_dict(),
            "actor_optim": self.actor_optimizer.state_dict(),
            "critic_1": self.critic_1.state_dict(),
            "critic_2": self.critic_2.state_dict(),
            "critic_target1": self.critic_target1.state_dict(),
            "critic_target2": self.critic_target2.state_dict(),
            "critic_optim1": self.critic_optimizer1.state_dict(),
            "critic_optim2": self.critic_optimizer2.state_dict(),
        }

        AbstractAgent.save_params(self, params, n_episode)

def save_params(self, n_episode: int):
        """Save model and optimizer parameters."""
        params = {
            "actor": self.actor.state_dict(),
            "actor_target": self.actor_target.state_dict(),
            "actor_optim": self.actor_optimizer.state_dict(),
            "critic_1": self.critic_1.state_dict(),
            "critic_2": self.critic_2.state_dict(),
            "critic_target1": self.critic_target1.state_dict(),
            "critic_target2": self.critic_target2.state_dict(),
            "critic_optim1": self.critic_optimizer1.state_dict(),
            "critic_optim2": self.critic_optimizer2.state_dict(),
        }

        AbstractAgent.save_params(self, params, n_episode)

def save_params(self, n_episode: int):
        """Save model and optimizer parameters."""
        params = {
            "actor_state_dict": self.actor.state_dict(),
            "critic_state_dict": self.critic.state_dict(),
            "actor_optim_state_dict": self.actor_optimizer.state_dict(),
            "critic_optim_state_dict": self.critic_optimizer.state_dict(),
        }

        AbstractAgent.save_params(self, params, n_episode)

def save_params(self, n_episode: int):
        """Save model and optimizer parameters."""
        params = {
            "actor_state_dict": self.actor.state_dict(),
            "critic_state_dict": self.critic.state_dict(),
            "actor_optim_state_dict": self.actor_optimizer.state_dict(),
            "critic_optim_state_dict": self.critic_optimizer.state_dict(),
        }

        AbstractAgent.save_params(self, params, n_episode)

def save_params(self, n_episode: int):
        """Save model and optimizer parameters."""
        params = {
            "actor_state_dict": self.actor.state_dict(),
            "baseline_state_dict": self.baseline.state_dict(),
            "actor_optim_state_dict": self.actor_optimizer.state_dict(),
            "baseline_optim_state_dict": self.baseline_optimizer.state_dict(),
        }

        AbstractAgent.save_params(self, params, n_episode)