code: def test_lbfgs_cpu_model(tmpdir):
      """Test each of the trainer options.
  
      Testing LBFGS optimizer
  
      """
      seed_everything(42)
  
      class ModelSpecifiedOptimizer(BoringModel):
          def __init__(self, optimizer_name, learning_rate):
              super().__init__()
              self.optimizer_name = optimizer_name
              self.learning_rate = learning_rate
              self.save_hyperparameters()
  
      trainer_options = {
          "default_root_dir": tmpdir,
          "max_epochs": 1,
          "enable_progress_bar": False,
          "limit_train_batches": 0.2,
          "limit_val_batches": 0.2,
      }
  
      model = ModelSpecifiedOptimizer(
          optimizer_name="LBFGS", learning_rate=0.004
      )
      tpipes.run_model_test_without_loggers(
          trainer_options, model, min_acc=0.01
      )
  
file_path: pytorch-lightning/tests/tests_pytorch/models/test_cpu.py
imports: import os
  from unittest import mock
  import torch
  from lightning.pytorch import Trainer, seed_everything
  from lightning.pytorch.callbacks import Callback, EarlyStopping, ModelCheckpoint
  from lightning.pytorch.demos.boring_classes import BoringModel
  import tests_pytorch.helpers.pipelines
  import tests_pytorch.helpers.utils
  from tests_pytorch.helpers.datamodules import ClassifDataModule
  from tests_pytorch.helpers.runif import RunIf
  from tests_pytorch.helpers.simple_models import ClassificationModel
label_desc: Use image node_id 4 for calling a global function with example usage: test_lbfgs_cpu_model(tmpdir) without return types