code: def test_onecyclelr_with_epoch_interval_warns():
      """Test warning when a OneCycleLR is used and interval is epoch."""
      model = BoringModel()
      optimizer = optim.Adam(model.parameters())
      lr_scheduler = {
          "scheduler": optim.lr_scheduler.OneCycleLR(
              optimizer, max_lr=0.01, total_steps=3
          )
      }
      with pytest.warns(
          RuntimeWarning,
          match="Are you sure you didn't mean 'interval': 'step'?",
      ):
          _configure_schedulers_automatic_opt([lr_scheduler], None)
  
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 5 for calling a global function with example usage: test_onecyclelr_with_epoch_interval_warns() without return types