code: def test_pytorch_autolog_persists_manually_created_run():
      with mlflow.start_run() as manual_run:
          mlflow.pytorch.autolog()
          model = IrisClassification()
          dm = IrisDataModule()
          dm.setup(stage="fit")
          trainer = pl.Trainer(max_epochs=NUM_EPOCHS)
          trainer.fit(model, dm)
          trainer.test(datamodule=dm)
          assert mlflow.active_run() is not None
          assert (
              mlflow.active_run().info.run_id == manual_run.info.run_id
          )
  
imports: import pytest
  import pytorch_lightning
  import torch
  from iris import IrisClassification, IrisClassificationMultiOptimizer, IrisClassificationWithoutValidation
  from iris_data_module import IrisDataModule, IrisDataModuleWithoutValidation
  from packaging.version import Version
  from pytorch_lightning.callbacks import ModelCheckpoint
  from pytorch_lightning.callbacks.early_stopping import EarlyStopping
  import mlflow
  import mlflow.pytorch
  from mlflow import MlflowClient
  from mlflow.exceptions import MlflowException
  from mlflow.pytorch._lightning_autolog import _get_optimizer_name
  from mlflow.utils.file_utils import TempDir
label_desc: Use image node_id 13 for calling a global function with example usage: test_pytorch_autolog_persists_manually_created_run() without return types