def _save_config(self, saved_hyperparams: dict[str, Any]) -> None:
        """
        Save unprocessed hyperparameters, this can be use later
        to reproduce an experiment.

        :param saved_hyperparams:
        """
        # Save hyperparams
        with open(os.path.join(self.params_path, "config.yml"), "w") as f:
            yaml.dump(saved_hyperparams, f)

        # save command line arguments
        with open(os.path.join(self.params_path, "args.yml"), "w") as f:
            ordered_args = OrderedDict([(key, vars(self.args)[key]) for key in sorted(vars(self.args).keys())])
            yaml.dump(ordered_args, f)

        # Save command used to train
        command = "python3 " + " ".join(sys.argv)
        # Python 3.10+
        if hasattr(sys, "orig_argv"):
            command = " ".join(sys.orig_argv)
        (Path(self.params_path) / "command.txt").write_text(command)

        print(f"Log path: {self.save_path}")

        Save unprocessed hyperparameters, this can be use later
        to reproduce an experiment.

        :param saved_hyperparams:
        
rl_zoo3/exp_manager.py