code: def test_autologging_does_not_start_run(
      spark_session, format_to_file_path
  ):
      try:
          mlflow.spark.autolog()
          data_format = list(format_to_file_path.keys())[0]
          file_path = format_to_file_path[data_format]
          df = (
              spark_session.read.format(data_format)
              .option("header", "true")
              .option("inferSchema", "true")
              .load(file_path)
          )
          df.collect()
          time.sleep(1)
          active_run = mlflow.active_run()
          assert active_run is None
          assert len(mlflow.search_runs()) == 0
      finally:
          mlflow.end_run()
  
file_path: mlflow/tests/spark/autologging/datasource/test_spark_datasource_autologging.py
imports: import time
  from unittest import mock
  from pyspark.sql import Row
  from pyspark.sql.types import IntegerType, StructField, StructType
  import mlflow
  import mlflow.spark
  from mlflow._spark_autologging import _SPARK_TABLE_INFO_TAG_NAME
  from mlflow.utils.validation import MAX_TAG_VAL_LENGTH
  from tests.spark.autologging.utils import _assert_spark_data_logged
  from tests.tracking.integration_test_utils import _init_server
label_desc: Use image node_id 7 for calling a global function with example usage: test_autologging_does_not_start_run(spark_session, format_to_file_path) without return types