code: def _hpc_resume_path(self) -> Optional[str]:
      dir_path_hpc = self.trainer.default_root_dir
      dir_path_hpc = str(dir_path_hpc)
      fs, path = url_to_fs(dir_path_hpc)
      if not _is_dir(fs, path):
          return None
      max_version = self.__max_ckpt_version_in_folder(
          dir_path_hpc, "hpc_ckpt_"
      )
      if max_version is not None:
          if isinstance(fs, LocalFileSystem):
              return os.path.join(
                  dir_path_hpc, f"hpc_ckpt_{max_version}.ckpt"
              )
          return dir_path_hpc + fs.sep + f"hpc_ckpt_{max_version}.ckpt"
      return None
  
imports: import logging
  import os
  import re
  from typing import Any, Dict, Optional
  import torch
  from fsspec.core import url_to_fs
  from fsspec.implementations.local import LocalFileSystem
  from torch import Tensor
  import lightning.pytorch
  from lightning.fabric.plugins.environments.slurm import SLURMEnvironment
  from lightning.fabric.utilities.cloud_io import _is_dir, get_filesystem
  from lightning.fabric.utilities.types import _PATH
  from lightning.pytorch.callbacks import ModelCheckpoint
  from lightning.pytorch.plugins.precision import MixedPrecision
  from lightning.pytorch.trainer import call
  from lightning.pytorch.trainer.states import TrainerFn
  from lightning.pytorch.utilities.exceptions import MisconfigurationException
  from lightning.pytorch.utilities.imports import _OMEGACONF_AVAILABLE
  from lightning.pytorch.utilities.migration import pl_legacy_patch
  from lightning.pytorch.utilities.migration.utils import _pl_migrate_checkpoint
  from lightning.pytorch.utilities.rank_zero import rank_zero_info, rank_zero_warn
label_desc: Use image node_id 2 for calling the _CheckpointConnector obj's underlying member method code with example usage: obj._hpc_resume_path() and returns: None, None, unknown, os