code: def test_metrics_and_outputs_device(tmpdir, accelerator):
      class TestModel(BoringModel):
          outputs = []
  
          def on_before_backward(self, loss: Tensor) -> None:
              # the loss should be on the correct device before backward
              assert loss.device.type == accelerator
  
          def validation_step(self, *args):
              x = torch.tensor(
                  2.0, requires_grad=True, device=self.device
              )
              y = x * 2
              assert x.requires_grad is True
              assert y.grad_fn is None  # disabled by validation
              self.log("foo", y)
              self.outputs.append(y)
              return y
  
          def on_validation_epoch_end(self):
              # the step outputs were not moved after returning them
              assert all(o.device == self.device for o in self.outputs)
              # and the logged metrics aren't
              assert (
                  self.trainer.callback_metrics["foo"].device.type
                  == accelerator
              )
  
      model = TestModel()
      trainer = Trainer(
          default_root_dir=tmpdir,
          fast_dev_run=True,
          accelerator=accelerator,
          devices=1,
      )
      trainer.fit(model)
      trainer.validate(model, verbose=False)
  
imports: import collections
  import itertools
  import os
  from contextlib import redirect_stdout
  from io import StringIO
  from unittest import mock
  from unittest.mock import ANY, call
  import numpy
  import pytest
  import torch
  from lightning.fabric.utilities.imports import _PYTHON_GREATER_EQUAL_3_8_0
  from lightning.pytorch import Trainer, callbacks
  from lightning.pytorch.callbacks.progress.rich_progress import _RICH_AVAILABLE
  from lightning.pytorch.demos.boring_classes import BoringModel, RandomDataset
  from lightning.pytorch.loggers import TensorBoardLogger
  from lightning.pytorch.loops import _EvaluationLoop
  from lightning.pytorch.trainer.states import RunningStage
  from lightning.pytorch.utilities.exceptions import MisconfigurationException
  from torch import Tensor
  from tests_pytorch.helpers.runif import RunIf
label_desc: Use image node_id 12 for calling a global function with example usage: test_metrics_and_outputs_device(tmpdir, accelerator) and returns: y