code: def test_extra_tags_pytorch_autolog():
      mlflow.pytorch.autolog(extra_tags={"test_tag": "pytorch_autolog"})
      model = IrisClassification()
      dm = IrisDataModule()
      dm.setup(stage="fit")
      trainer = pl.Trainer(max_epochs=NUM_EPOCHS)
      trainer.fit(model, dm)
  
      run = mlflow.last_active_run()
      assert run.data.tags["test_tag"] == "pytorch_autolog"
      assert (
          run.data.tags[mlflow.utils.mlflow_tags.MLFLOW_AUTOLOGGING]
          == "pytorch"
      )
  
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 7 for calling a global function with example usage: test_extra_tags_pytorch_autolog() without return types