code: def _try_loop_run(
      trainer: "pl.Trainer", params: Dict[str, Any]
  ) -> None:
      loop = trainer._active_loop
      assert loop is not None
      loop.load_state_dict(deepcopy(params["loop_state_dict"]))
      loop.restarting = False
      loop.run()
  
file_path: pytorch-lightning/src/lightning/pytorch/tuner/batch_size_scaling.py
imports: import logging
  import os
  import uuid
  from copy import deepcopy
  from typing import Any, Dict, Optional, Tuple
  import lightning.pytorch
  from lightning.pytorch.utilities.memory import garbage_collection_cuda, is_oom_error
  from lightning.pytorch.utilities.parsing import lightning_getattr, lightning_setattr
  from lightning.pytorch.utilities.rank_zero import rank_zero_info, rank_zero_warn
label_desc: Use image node_id 9 for calling a global function with example usage: _try_loop_run(trainer, params) without return types