class_docstr: Pytorch Lightning class which adds methods to perform
  active learning.
docstr: DataLoader for the pool. Must be defined if you do not use a DataModule
docstr_tok: ["DataLoader","for","the","pool",".","Must","be","defined","if","you","do","not","use","a","DataModule"]
code: def pool_dataloader(self) -> DataLoader:
      """DataLoader for the pool. Must be defined if you do not use a DataModule"""
      raise NotImplementedError
  
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 1 for calling the ActiveLightningModule obj's underlying member method code with example usage: obj.pool_dataloader() without return types