code: def test_accumulation_and_early_stopping(tmpdir):
      """Test that early stopping of learning rate finder works, and that accumulation also works for this feature."""
      seed_everything(1)
  
      class TestModel(BoringModel):
          def __init__(self):
              super().__init__()
              self.lr = 1e-3
  
      model = TestModel()
      trainer = Trainer(
          default_root_dir=tmpdir, accumulate_grad_batches=2
      )
      tuner = Tuner(trainer)
      lr_finder = tuner.lr_find(model, early_stop_threshold=None)
  
      assert lr_finder.suggestion() != 1e-3
      assert (
          len(lr_finder.results["lr"])
          == len(lr_finder.results["loss"])
          == 100
      )
      assert lr_finder._total_batch_idx == 199
  
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 8 for calling a global function with example usage: test_accumulation_and_early_stopping(tmpdir) without return types