code: def maybe_shuffle_instances(
      loader: DataLoader, shuffle: bool
  ) -> Iterable[Instance]:
      if shuffle:
          return util.shuffle_iterable(loader.iter_instances())
      else:
          return loader.iter_instances()
  
imports: from typing import Any, Dict, Iterable, Iterator, Union, Optional
  import itertools
  import math
  import torch
  from allennlp.common import util
  from allennlp.data.batch import Batch
  from allennlp.data.data_loaders.data_loader import DataLoader, TensorDict
  from allennlp.data.data_loaders.multiprocess_data_loader import MultiProcessDataLoader
  from allennlp.data.data_loaders.multitask_scheduler import MultiTaskScheduler
  from allennlp.data.data_loaders.multitask_epoch_sampler import MultiTaskEpochSampler
  from allennlp.data.dataset_readers.multitask import MultiTaskDatasetReader
  from allennlp.data.instance import Instance
  from allennlp.data.vocabulary import Vocabulary
  import allennlp.nn.util
label_desc: Use image node_id 1 for calling a global function with example usage: maybe_shuffle_instances(loader, shuffle) and returns: util, loader