code: def test_device_placement(tmpdir, accelerator, device):
      model = BoringModel()
      trainer = Trainer(
          default_root_dir=tmpdir,
          fast_dev_run=True,
          accelerator=accelerator,
          devices=1,
      )
      trainer.fit(model)
  
      def assert_device(device: torch.device) -> None:
          assert model.device == device
          for p in model.parameters():
              assert p.device == device
  
      assert_device(torch.device("cpu"))
      model.to(torch.device(device))
      assert_device(torch.device(device))
      trainer.test(model)
      assert_device(torch.device("cpu"))
      trainer.predict(model, dataloaders=model.train_dataloader())
      assert_device(torch.device("cpu"))
  
imports: import sys
  import weakref
  from unittest.mock import Mock
  import pytest
  import torch
  from lightning.fabric import Fabric
  from lightning.fabric.utilities.imports import _TORCH_GREATER_EQUAL_1_13, _TORCH_GREATER_EQUAL_2_0
  from lightning.pytorch import LightningModule, Trainer
  from lightning.pytorch.core.module import _TrainerFabricShim
  from lightning.pytorch.demos.boring_classes import BoringModel
  from lightning.pytorch.loggers import TensorBoardLogger
  from lightning.pytorch.utilities.exceptions import MisconfigurationException
  from torch import nn
  from torch.optim import SGD, Adam
  from tests_pytorch.helpers.runif import RunIf
label_desc: Use image node_id 11 for calling a global function with example usage: test_device_placement(tmpdir, accelerator, device) without return types