code: def validation_step(self, batch, batch_idx):
      assert len(self.trainer.val_dataloaders) == 10
      return super().validation_step(batch, batch_idx)
  
imports: from re import escape
  from typing import Sized
  from unittest import mock
  from unittest.mock import Mock
  import lightning.fabric
  import pytest
  from lightning.fabric.utilities.distributed import DistributedSamplerWrapper
  from lightning.fabric.utilities.warnings import PossibleUserWarning
  from lightning.pytorch import Trainer
  from lightning.pytorch.demos.boring_classes import BoringDataModule, BoringModel, RandomDataset
  from lightning.pytorch.trainer.connectors.data_connector import _check_dataloader_iterable, _DataHookSelector, _DataLoaderSource, _worker_check, warning_cache
  from lightning.pytorch.trainer.states import RunningStage, TrainerFn
  from lightning.pytorch.utilities.combined_loader import CombinedLoader
  from lightning.pytorch.utilities.data import _update_dataloader
  from lightning.pytorch.utilities.exceptions import MisconfigurationException
  from lightning_utilities.test.warning import no_warning_call
  from torch import Tensor
  from torch.utils.data import BatchSampler, DataLoader, DistributedSampler, Sampler, SequentialSampler
  from tests_pytorch.helpers.runif import RunIf
label_desc: Use image node_id 2 for calling the LoaderTestModel obj's underlying member method code with example usage: obj.validation_step(batch, batch_idx) and returns: super