code: def test_multiple_lr_find_calls_gives_same_results(tmpdir):
      """Tests that lr_finder gives same results if called multiple times."""
      seed_everything(1)
      model = BoringModel()
      model.lr = 0.1
  
      trainer = Trainer(
          default_root_dir=tmpdir,
          max_epochs=2,
          limit_train_batches=10,
          limit_val_batches=2,
          enable_progress_bar=False,
          enable_model_summary=False,
          enable_checkpointing=False,
      )
      tuner = Tuner(trainer)
      all_res = [tuner.lr_find(model).results for _ in range(3)]
  
      assert all(
          all_res[0][k] == curr_lr_finder[k]
          and len(curr_lr_finder[k]) > 10
          for curr_lr_finder in all_res[1:]
          for k in all_res[0]
      )
  
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 14 for calling a global function with example usage: test_multiple_lr_find_calls_gives_same_results(tmpdir) without return types