code: def _fit_sklearn_model_no_active_run(pandas_df):
      orig_runs = mlflow.search_runs()
      orig_run_ids = set(orig_runs["run_id"])
      _fit_sklearn(pandas_df)
      new_runs = mlflow.search_runs()
      new_run_ids = set(new_runs["run_id"])
      assert len(new_run_ids) == len(orig_run_ids) + 1
      run_id = (new_run_ids - orig_run_ids).pop()
      return mlflow.get_run(run_id)
  
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 4 for calling a global function with example usage: _fit_sklearn_model_no_active_run(pandas_df) and returns: mlflow