code: def test_extra_tags_mlflow_autolog():
      from sklearn.ensemble import RandomForestRegressor
  
      from mlflow.exceptions import MlflowException
      from mlflow.utils.mlflow_tags import MLFLOW_AUTOLOGGING
  
      mlflow.autolog(
          extra_tags={"test_tag": "autolog", MLFLOW_AUTOLOGGING: "123"}
      )
      rf = RandomForestRegressor(
          n_estimators=1, max_depth=1, max_features=1
      )
      rf.fit([[1, 2]], [[3]])
      autolog_run = mlflow.last_active_run()
      assert autolog_run.data.tags["test_tag"] == "autolog"
      assert autolog_run.data.tags[MLFLOW_AUTOLOGGING] == "sklearn"
  
      with pytest.raises(
          MlflowException, match="Invalid `extra_tags` type"
      ):
          mlflow.autolog(extra_tags="test_tag")
  
imports: import sys
  from collections import namedtuple
  from io import StringIO
  from unittest import mock
  import fastai
  import lightgbm
  import pyspark
  import pyspark.ml
  import pytest
  import pytorch_lightning
  import setfit
  import sklearn
  import statsmodels
  import tensorflow
  import transformers
  import xgboost
  import mlflow
  from mlflow.utils.autologging_utils import AutologgingEventLogger, autologging_is_disabled, get_autologging_config
  from tests.autologging.fixtures import reset_stderr, test_mode_off, test_mode_on
label_desc: Use image node_id 14 for calling a global function with example usage: test_extra_tags_mlflow_autolog() without return types