code: def on_load_checkpoint(self, checkpoint: Dict[str, Any]) -> None:
      if "active_dataset" in checkpoint:
          self.active_dataset.load_state_dict(
              checkpoint["active_dataset"]
          )
      else:
          log.warning("'active_dataset' not in checkpoint!")
  
imports: import sys
  import types
  import warnings
  from collections.abc import Sequence
  from typing import Dict, Any, Optional
  import numpy
  import structlog
  import torch
  from pytorch_lightning import Trainer, Callback, LightningDataModule, LightningModule
  from pytorch_lightning.accelerators import CUDAAccelerator
  from torch.utils.data import DataLoader
  from tqdm import tqdm
  from baal.active import ActiveLearningDataset
  from baal.active.heuristics import heuristics
  from baal.modelwrapper import mc_inference
  from baal.utils.cuda_utils import to_cuda
  from baal.utils.iterutils import map_on_tensor
label_desc: Use image node_id 3 for calling the BaaLDataModule obj's underlying member method code with example usage: obj.on_load_checkpoint(checkpoint) without return types