code: def _fit_sklearn_model(pandas_df):
      active_run = mlflow.active_run()
      if active_run:
          return _fit_sklearn_model_with_active_run(pandas_df)
      else:
          return _fit_sklearn_model_no_active_run(pandas_df)
  
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 5 for calling a global function with example usage: _fit_sklearn_model(pandas_df) and returns: _fit_sklearn_model_with_active_run, _fit_sklearn_model_no_active_run