code: def test_lr_candidates_between_min_and_max(tmpdir):
      """Test that learning rate candidates are between min_lr and max_lr."""
      seed_everything(1)
  
      class TestModel(BoringModel):
          def __init__(self, learning_rate=0.1):
              super().__init__()
              self.save_hyperparameters()
  
      model = TestModel()
      trainer = Trainer(default_root_dir=tmpdir)
  
      lr_min = 1e-8
      lr_max = 1.0
      tuner = Tuner(trainer)
      lr_finder = tuner.lr_find(
          model, max_lr=lr_min, min_lr=lr_max, num_training=3
      )
      lr_candidates = lr_finder.results["lr"]
      assert all(lr_min <= lr <= lr_max for lr in lr_candidates)
  
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 12 for calling a global function with example usage: test_lr_candidates_between_min_and_max(tmpdir) without return types