code: def shared_step(self, dataloader_iter, stage):
      self.record[stage]["entered"] += 1
      for i in range(self.fetches_per_step):
          try:
              batch, _, __ = next(dataloader_iter)
          except StopIteration:
              self.record[stage]["raised"] += 1
              return None
          self.record[stage]["fetched"] += 1
      return self.layer(batch).sum()
  
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 the DataLoaderIterMonitorModel obj's underlying member method code with example usage: obj.shared_step(dataloader_iter, stage) and returns: self, None