code: def test_spark_udf_spark_connect_unsupported_env_manager(
      spark, tmp_path, env_manager
  ):
      with pytest.raises(
          mlflow.MlflowException,
          match=f"Environment manager {env_manager!r} is not supported",
      ):
          mlflow.pyfunc.spark_udf(
              spark, str(tmp_path), env_manager=env_manager
          )
  
file_path: mlflow/tests/pyfunc/test_spark_connect.py
imports: import numpy
  import pandas
  import pyspark
  import pytest
  from pyspark.sql import SparkSession
  from sklearn.datasets import load_iris
  from sklearn.linear_model import LogisticRegression
  import mlflow
label_desc: Use image node_id 3 for calling a global function with example usage: test_spark_udf_spark_connect_unsupported_env_manager(spark, tmp_path, env_manager) without return types