code: def test_spark_autologging_with_sklearn_autologging(
      spark_session, data_format, file_path
  ):
      assert mlflow.active_run() is None
      mlflow.spark.autolog()
      mlflow.sklearn.autolog()
      df = (
          spark_session.read.format(data_format)
          .option("header", "true")
          .option("inferSchema", "true")
          .load(file_path)
          .select("number1", "number2")
      )
      pandas_df = df.toPandas()
      run = _fit_sklearn_model(pandas_df)
      _assert_spark_data_logged(run, file_path, data_format)
      assert mlflow.active_run() is None
  
file_path: mlflow/tests/spark/autologging/datasource/test_spark_datasource_autologging_crossframework.py
imports: import time
  import numpy
  import pytest
  from sklearn.linear_model import LinearRegression
  import mlflow
  import mlflow.spark
  from tests.spark.autologging.utils import _assert_spark_data_logged
label_desc: Use image node_id 6 for calling a global function with example usage: test_spark_autologging_with_sklearn_autologging(spark_session, data_format, file_path) without return types