code: def run(data_path, model_uri):
      with pyspark.sql.SparkSession.builder.config(
          key="spark.python.worker.reuse", value=True
      ).config(key="spark.ui.enabled", value=False).master(
          "local-cluster[2, 1, 1024]"
      ).getOrCreate() as spark:
          # ignore spark log output
          spark.sparkContext.setLogLevel("OFF")
          print(score_model(spark, data_path, model_uri))
  
file_path: mlflow/examples/flower_classifier/score_images_spark.py
imports: import base64
  import os
  import click
  import pandas
  import pyspark
  from pyspark.sql.types import ArrayType, Row, StringType, StructField, StructType
  import mlflow
  import mlflow.pyfunc
  from mlflow.utils import cli_args
label_desc: Use image node_id 4 for calling a global function with example usage: run(data_path, model_uri) without return types