code: def test_universal_autolog_calls_specific_autologs_correctly(
      library, mlflow_module
  ):
      integrations_with_additional_config = [xgboost, lightgbm, sklearn]
      args_to_test = {
          "log_models": False,
          "log_datasets": False,
          "disable": True,
          "exclusive": True,
          "disable_for_unsupported_versions": True,
          "silent": True,
      }
      if library in integrations_with_additional_config:
          args_to_test.update(
              {"log_input_examples": True, "log_model_signatures": True}
          )
  
      mlflow.autolog(**args_to_test)
  
      mlflow.utils.import_hooks.notify_module_loaded(library)
  
      for arg_key, arg_value in args_to_test.items():
          assert (
              get_autologging_config(
                  mlflow_module.autolog.integration_name, arg_key, None
              )
              == arg_value
          )
  
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 6 for calling a global function with example usage: test_universal_autolog_calls_specific_autologs_correctly(library, mlflow_module) without return types