code: def test_autologging_disabled_logging_datasource_with_different_formats(
      spark_session, format_to_file_path
  ):
      mlflow.spark.autolog(disable=True)
      for data_format, file_path in format_to_file_path.items():
          df = (
              spark_session.read.format(data_format)
              .option("header", "true")
              .option("inferSchema", "true")
              .load(file_path)
          )
  
          with mlflow.start_run():
              run_id = mlflow.active_run().info.run_id
              df.collect()
              time.sleep(1)
          run = mlflow.get_run(run_id)
          _assert_spark_data_not_logged(run=run)
  
imports: import time
  import mlflow
  import mlflow.spark
  from tests.spark.autologging.utils import _assert_spark_data_logged, _assert_spark_data_not_logged
label_desc: Use image node_id 1 for calling a global function with example usage: test_autologging_disabled_logging_datasource_with_different_formats(spark_session, format_to_file_path) without return types