code: def model_and_trainer_cases():
      class TestHparamsNamespace(LightningModule):
          learning_rate = 1
  
          def __contains__(self, item):
              return item == "learning_rate"
  
      TestHparamsDict = {"learning_rate": 2}
  
      class TestModel1(LightningModule):  # test for namespace
          learning_rate = 0
  
      model1 = TestModel1()
  
      class TestModel2(LightningModule):  # test for hparams namespace
          hparams = TestHparamsNamespace()
  
      model2 = TestModel2()
  
      class TestModel3(LightningModule):  # test for hparams dict
          hparams = TestHparamsDict
  
      model3 = TestModel3()
  
      class TestModel4(LightningModule):  # fail case
          batch_size = 1
  
      model4 = TestModel4()
      trainer1 = Trainer()
      model4.trainer = trainer1
      datamodule = LightningDataModule()
      datamodule.batch_size = 8
      trainer1.datamodule = datamodule
  
      model5 = LightningModule()
      model5.trainer = trainer1
  
      class TestModel6(
          LightningModule
      ):  # test for datamodule w/ hparams w/o attribute (should use datamodule)
          hparams = TestHparamsDict
  
      model6 = TestModel6()
      model6.trainer = trainer1
  
      TestHparamsDict2 = {"batch_size": 2}
  
      class TestModel7(
          LightningModule
      ):  # test for datamodule w/ hparams w/ attribute (should use datamodule)
          hparams = TestHparamsDict2
  
      model7 = TestModel7()
      model7.trainer = trainer1
  
      class TestDataModule8(
          LightningDataModule
      ):  # test for hparams dict
          hparams = TestHparamsDict2
  
      model8 = TestModel1()
      trainer2 = Trainer()
      model8.trainer = trainer2
      datamodule = TestDataModule8()
      trainer2.datamodule = datamodule
  
      return (
          model1,
          model2,
          model3,
          model4,
          model5,
          model6,
          model7,
          model8,
      ), (trainer1, trainer2)
  
file_path: pytorch-lightning/tests/tests_pytorch/utilities/test_parsing.py
imports: import inspect
  import threading
  import pytest
  from lightning.pytorch import LightningDataModule, LightningModule, Trainer
  from lightning.pytorch.utilities.parsing import _get_init_args, clean_namespace, collect_init_args, is_picklable, lightning_getattr, lightning_hasattr, lightning_setattr, parse_class_init_keys
  from torch.jit import ScriptModule
label_desc: Use image node_id 1 for calling a global function with example usage: model_and_trainer_cases() and returns: model1,  model2,  model3,  model4,  model5,  model6,  model7,  model8,  trainer1,  trainer2, unknown