code: def test_lr_scheduler_with_extra_keys_warns(tmpdir):
      """Test warning when lr_scheduler dict has extra keys."""
      model = BoringModel()
      optimizer = optim.Adam(model.parameters())
      model.configure_optimizers = lambda: {
          "optimizer": optimizer,
          "lr_scheduler": {
              "scheduler": optim.lr_scheduler.StepLR(optimizer, 1),
              "foo": 1,
              "bar": 2,
          },
      }
      trainer = Trainer(default_root_dir=tmpdir, fast_dev_run=True)
      with pytest.warns(
          RuntimeWarning,
          match=r"Found unsupported keys in the lr scheduler dict: \{.+\}",
      ):
          trainer.fit(model)
  
imports: from unittest import mock
  from unittest.mock import call
  import pytest
  import torch
  from lightning.pytorch import Trainer
  from lightning.pytorch.callbacks import ModelCheckpoint
  from lightning.pytorch.core.optimizer import _configure_optimizers, _configure_schedulers_automatic_opt, _init_optimizers_and_lr_schedulers
  from lightning.pytorch.demos.boring_classes import BoringDataModule, BoringModel
  from lightning.pytorch.utilities.exceptions import MisconfigurationException
  from lightning.pytorch.utilities.types import LRSchedulerConfig
  from torch import optim
  from tests_pytorch.helpers.runif import RunIf
label_desc: Use image node_id 17 for calling a global function with example usage: test_lr_scheduler_with_extra_keys_warns(tmpdir) without return types