code: def test_processing_step_with_processor_and_step_args(
      pipeline_session, processing_input, image_uri
  ):
      processor = Processor(
          image_uri=image_uri,
          role=ROLE,
          instance_count=1,
          instance_type=INSTANCE_TYPE,
          sagemaker_session=pipeline_session,
      )
  
      step_args = processor.run(inputs=processing_input)
      try:
          ProcessingStep(
              name="MyProcessingStep",
              step_args=step_args,
              processor=processor,
          )
          assert False
      except Exception as e:
          assert isinstance(e, ValueError)
  
      try:
          ProcessingStep(
              name="MyProcessingStep",
          )
          assert False
      except Exception as e:
          assert isinstance(e, ValueError)
  
imports: from __future__ import absolute_import
  import json
  import os
  from mock import patch
  import pytest
  import warnings
  from copy import deepcopy
  from sagemaker.estimator import Estimator
  from sagemaker.parameter import IntegerParameter
  from sagemaker.transformer import Transformer
  from sagemaker.tuner import HyperparameterTuner
  from sagemaker.processing import Processor, ScriptProcessor, FrameworkProcessor, ProcessingOutput, ProcessingInput
  from sagemaker.sklearn.processing import SKLearnProcessor
  from sagemaker.pytorch.processing import PyTorchProcessor
  from sagemaker.tensorflow.processing import TensorFlowProcessor
  from sagemaker.huggingface.processing import HuggingFaceProcessor
  from sagemaker.xgboost.processing import XGBoostProcessor
  from sagemaker.mxnet.processing import MXNetProcessor
  from sagemaker.wrangler.processing import DataWranglerProcessor
  from sagemaker.spark.processing import SparkJarProcessor, PySparkProcessor
  from sagemaker.workflow.steps import CacheConfig, ProcessingStep
  from sagemaker.workflow.pipeline import Pipeline, PipelineGraph
  from sagemaker.workflow.pipeline_definition_config import PipelineDefinitionConfig
  from sagemaker.workflow.pipeline_context import _PipelineConfig
  from sagemaker.workflow.properties import PropertyFile
  from sagemaker.workflow.parameters import ParameterString
  from sagemaker.workflow.functions import Join
  from sagemaker.workflow.utilities import hash_files_or_dirs
  from sagemaker.workflow import is_pipeline_variable
  from sagemaker.network import NetworkConfig
  from sagemaker.pytorch.estimator import PyTorch
  from sagemaker import utils, Model
  from sagemaker.clarify import SageMakerClarifyProcessor, BiasConfig, DataConfig, ModelConfig, ModelPredictedLabelConfig, SHAPConfig
  from tests.unit.sagemaker.workflow.helpers import CustomStep, ordered, get_step_args_helper
  from tests.unit import DATA_DIR
  from tests.unit.sagemaker.workflow.conftest import ROLE, BUCKET, IMAGE_URI, INSTANCE_TYPE
label_desc: Use image node_id 4 for calling a global function with example usage: test_processing_step_with_processor_and_step_args(pipeline_session, processing_input, image_uri) without return types