code: def test_strict_model_load_more_params(
      monkeypatch, tmpdir, tmpdir_server, url_ckpt
  ):
      """Tests use case where trainer saves the model, and user loads it from tags independently."""
      # set $TORCH_HOME, which determines torch hub's cache path, to tmpdir
      monkeypatch.setenv("TORCH_HOME", tmpdir)
  
      model = BoringModel()
      # Extra layer
      model.c_d3 = torch.nn.Linear(32, 32)
  
      # logger file to get meta
      logger = tutils.get_default_logger(tmpdir)
  
      # fit model
      trainer = Trainer(
          default_root_dir=tmpdir,
          max_epochs=1,
          limit_train_batches=2,
          limit_val_batches=2,
          logger=logger,
          callbacks=[ModelCheckpoint(dirpath=tmpdir)],
      )
      trainer.fit(model)
  
      # traning complete
      assert (
          trainer.state.finished
      ), f"Training failed with {trainer.state}"
  
      # save model
      new_weights_path = os.path.join(tmpdir, "save_test.ckpt")
      trainer.save_checkpoint(new_weights_path)
  
      # load new model
      hparams_path = os.path.join(
          tutils.get_data_path(logger, path_dir=tmpdir), "hparams.yaml"
      )
      hparams_url = f"http://{tmpdir_server[0]}:{tmpdir_server[1]}/{os.path.basename(new_weights_path)}"
      ckpt_path = hparams_url if url_ckpt else new_weights_path
  
      BoringModel.load_from_checkpoint(
          checkpoint_path=ckpt_path,
          hparams_file=hparams_path,
          strict=False,
      )
  
      with pytest.raises(
          RuntimeError,
          match=r'Unexpected key\(s\) in state_dict: "c_d3.weight", "c_d3.bias"',
      ):
          BoringModel.load_from_checkpoint(
              checkpoint_path=ckpt_path,
              hparams_file=hparams_path,
              strict=True,
          )
  
imports: import glob
  import logging
  import os
  import pickle
  from copy import deepcopy
  from typing import Generic, Mapping, TypeVar
  import cloudpickle
  import pytest
  import torch
  from lightning.fabric import seed_everything
  from lightning.pytorch import Callback, Trainer
  from lightning.pytorch.callbacks import ModelCheckpoint
  from lightning.pytorch.demos.boring_classes import BoringModel
  from lightning.pytorch.trainer.states import TrainerFn
  from lightning_utilities.test.warning import no_warning_call
  from torch import Tensor
  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
  from tests_pytorch.loops.test_loops import CustomException
label_desc: Use image node_id 12 for calling a global function with example usage: test_strict_model_load_more_params(monkeypatch, tmpdir, tmpdir_server, url_ckpt) without return types