code: def test_model_reset_correctly(tmpdir):
      """Check that model weights are correctly reset after _lr_find()"""
      model = BoringModel()
      model.lr = 0.1
  
      # logger file to get meta
      trainer = Trainer(default_root_dir=tmpdir, max_epochs=1)
      tuner = Tuner(trainer)
      before_state_dict = deepcopy(model.state_dict())
  
      tuner.lr_find(model, num_training=5)
  
      after_state_dict = model.state_dict()
  
      for key in before_state_dict:
          assert torch.all(
              torch.eq(before_state_dict[key], after_state_dict[key])
          ), "Model was not reset correctly after learning rate finder"
  
      assert not any(
          f for f in os.listdir(tmpdir) if f.startswith(".lr_find")
      )
  
imports: import logging
  import math
  import os
  from copy import deepcopy
  from typing import Any
  from unittest import mock
  import pytest
  import torch
  from lightning.pytorch import Trainer, seed_everything
  from lightning.pytorch.callbacks.lr_finder import LearningRateFinder
  from lightning.pytorch.demos.boring_classes import BoringModel
  from lightning.pytorch.tuner.lr_finder import _LRFinder
  from lightning.pytorch.tuner.tuning import Tuner
  from lightning.pytorch.utilities.exceptions import MisconfigurationException
  from lightning.pytorch.utilities.types import STEP_OUTPUT
  from lightning_utilities.test.warning import no_warning_call
  from tests_pytorch.helpers.datamodules import ClassifDataModule
  from tests_pytorch.helpers.runif import RunIf
  from tests_pytorch.helpers.simple_models import ClassificationModel
  from tests_pytorch.helpers.utils import getattr_recursive
label_desc: Use image node_id 2 for calling a global function with example usage: test_model_reset_correctly(tmpdir) without return types