code: def test_profiler_closing(multiple_iterables):
      """Tests if the profiler terminates upon raising a StopIteration on an iterable dataset."""
  
      class TestDataset(IterableDataset):
          def __init__(self):
              self.list = list(range(1))
  
          def __iter__(self):
              return iter(self.list)
  
      fetcher = _PrefetchDataFetcher()
      if multiple_iterables:
          loader = CombinedLoader(
              [DataLoader(TestDataset()), DataLoader(TestDataset())]
          )
      else:
          loader = CombinedLoader(TestDataset())
      fetcher.setup(loader)
      profiler = SimpleProfiler()
      fetcher._start_profiler = lambda: profiler.start("test")
      fetcher._stop_profiler = lambda: profiler.stop("test")
      iter(fetcher)  # on epoch 0 start
      next(fetcher)  # raises StopIteration exception
      assert not bool(profiler.current_actions)
  
imports: from collections import Counter
  from typing import Any, Iterator
  import pytest
  import torch
  from lightning.pytorch import LightningDataModule, Trainer
  from lightning.pytorch.demos.boring_classes import BoringModel, RandomDataset
  from lightning.pytorch.loops.fetchers import _DataLoaderIterDataFetcher, _PrefetchDataFetcher
  from lightning.pytorch.profilers import SimpleProfiler
  from lightning.pytorch.utilities.combined_loader import CombinedLoader
  from lightning.pytorch.utilities.exceptions import MisconfigurationException
  from lightning.pytorch.utilities.types import STEP_OUTPUT
  from torch import Tensor
  from torch.utils.data import DataLoader, Dataset, IterableDataset
  from tests_pytorch.helpers.runif import RunIf
label_desc: Use image node_id 2 for calling a global function with example usage: test_profiler_closing(multiple_iterables) and returns: iter