code: def test_transfer_hooks_with_unpacking(tmpdir):
      """This test asserts the `transfer_batch` hooks are called only once per batch."""
  
      class RandomDictDataset(RandomDataset):
          def __getitem__(self, index):
              return {
                  "x": self.data[index],
                  "y_true": torch.ones((2,)),
                  "other": torch.ones((1,)),
              }
  
      class BoringDataModule(LightningDataModule):
          count_called_on_before_batch_transfer = 0
          count_called_transfer_batch_to_device = 0
          count_called_on_after_batch_transfer = 0
  
          def train_dataloader(self):
              return DataLoader(RandomDictDataset(32, 2))
  
          def val_dataloader(self):
              return DataLoader(RandomDictDataset(32, 2))
  
          def on_before_batch_transfer(
              self, batch, dataloader_idx: int
          ):
              self.count_called_on_before_batch_transfer += 1
              return batch["x"], batch["y_true"]
  
          def transfer_batch_to_device(self, *args, **kwargs):
              self.count_called_transfer_batch_to_device += 1
              return super().transfer_batch_to_device(*args, **kwargs)
  
          def on_after_batch_transfer(self, batch, dataloader_idx: int):
              self.count_called_on_after_batch_transfer += 1
              return super().on_after_batch_transfer(
                  batch, dataloader_idx
              )
  
      class TestModel(BoringModel):
          def training_step(self, batch, batch_idx):
              x, _ = batch
              return super().training_step(x, batch_idx)
  
          def validation_step(self, batch, batch_idx):
              x, _ = batch
              return super().validation_step(x, batch_idx)
  
      trainer = Trainer(
          default_root_dir=tmpdir, max_epochs=1, num_sanity_val_steps=0
      )
      dm = BoringDataModule()
      trainer.fit(TestModel(), datamodule=dm)
      assert dm.count_called_on_before_batch_transfer == 4
      assert dm.count_called_transfer_batch_to_device == 4
      assert dm.count_called_on_after_batch_transfer == 4
  
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 10 for calling a global function with example usage: test_transfer_hooks_with_unpacking(tmpdir) and returns: dict, DataLoader, DataLoader, batch,  batch, super, super, super, super