code: def test_warning_invalid_trainstep_output(tmpdir, case):
      output, match = case
  
      class InvalidTrainStepModel(BoringModel):
          def training_step(self, batch, batch_idx):
              return output
  
      model = InvalidTrainStepModel()
      trainer = Trainer(default_root_dir=tmpdir, fast_dev_run=1)
  
      with pytest.raises(MisconfigurationException, match=match):
          trainer.fit(model)
  
file_path: pytorch-lightning/tests/tests_pytorch/loops/optimization/test_optimizer_loop.py
imports: from typing import Dict, Generic, Iterator, Mapping, TypeVar
  import pytest
  import torch
  from lightning.pytorch import Trainer
  from lightning.pytorch.demos.boring_classes import BoringModel
  from lightning.pytorch.loops.optimization.automatic import ClosureResult
  from lightning.pytorch.utilities.exceptions import MisconfigurationException
label_desc: Use image node_id 3 for calling a global function with example usage: test_warning_invalid_trainstep_output(tmpdir, case) and returns: output