def resume_start(self, checkpoint_path: Optional[_PATH] = None) -> None:
        """Attempts to pre-load the checkpoint file to memory, with the source path determined in this priority:

        1. from HPC weights if `checkpoint_path` is ``None`` and on SLURM or passed keyword `"hpc"`.
        2. from fault-tolerant auto-saved checkpoint if found
        3. from `checkpoint_path` file if provided
        4. don't restore

        """
        self._ckpt_path = checkpoint_path
        if not checkpoint_path:
            log.debug("`checkpoint_path` not specified. Skipping checkpoint loading.")
            return

        rank_zero_info(f"Restoring states from the checkpoint path at {checkpoint_path}")
        with pl_legacy_patch():
            loaded_checkpoint = self.trainer.strategy.load_checkpoint(checkpoint_path)
        self._loaded_checkpoint = _pl_migrate_checkpoint(loaded_checkpoint, checkpoint_path)
Attempts to pre-load the checkpoint file to memory, with the source path determined in this priority:

        1. from HPC weights if `checkpoint_path` is ``None`` and on SLURM or passed keyword `"hpc"`.
        2. from fault-tolerant auto-saved checkpoint if found
        3. from `checkpoint_path` file if provided
        4. don't restore

        
src/lightning/pytorch/trainer/connectors/checkpoint_connector.py