code: def _reset_dataloaders(trainer: "pl.Trainer") -> None:
      loop = trainer._active_loop
      assert loop is not None
      loop._combined_loader = None  # force a reload
      loop.setup_data()
      if isinstance(loop, pl.loops._FitLoop):
          loop.epoch_loop.val_loop._combined_loader = None
          loop.epoch_loop.val_loop.setup_data()
  
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 8 for calling a global function with example usage: _reset_dataloaders(trainer) without return types