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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def save(self, checkpoint_dir=None):
 """Saves the current model state to a checkpoint. Subclasses should override ``_save()`` instead to save state. This method dumps additional metadata alongside the saved path. Args: checkpoint_dir (str):
 Optional dir to place the checkpoint. Returns: Checkpoint path that may be passed to restore(). """


        checkpoint_dir = os.path.join(checkpoint_dir or self.logdir,
                                      "checkpoint_{}".format(self._iteration))
        if not os.path.exists(checkpoint_dir):
            os.makedirs(checkpoint_dir)
        checkpoint = self._save(checkpoint_dir)
        saved_as_dict = False
        if isinstance(checkpoint, string_types):
            if (not checkpoint.startswith(checkpoint_dir)
                    or checkpoint == checkpoint_dir):
                raise ValueError(
                    "The returned checkpoint path must be within the "
                    "given checkpoint dir {}: {}".format(
                        checkpoint_dir, checkpoint))
            if not os.path.exists(checkpoint):
                raise ValueError(
                    "The returned checkpoint path does not exist: {}".format(
                        checkpoint))
            checkpoint_path = checkpoint
        elif isinstance(checkpoint, dict):
            saved_as_dict = True
            checkpoint_path = os.path.join(checkpoint_dir, "checkpoint")
            with open(checkpoint_path, "wb") as f:
                pickle.dump(checkpoint, f)
        else:
            raise ValueError(
                "`_save` must return a dict or string type: {}".format(
                    str(type(checkpoint))))
        with open(checkpoint_path + ".tune_metadata", "wb") as f:
            pickle.dump({
                "experiment_id": self._experiment_id,
                "iteration": self._iteration,
                "timesteps_total": self._timesteps_total,
                "time_total": self._time_total,
                "episodes_total": self._episodes_total,
                "saved_as_dict": saved_as_dict
            }, f)
        return checkpoint_path