code: def test_decorator_step_checksum_mismatch(
      sagemaker_session,
      dummy_container_without_error,
      pipeline_name,
      role,
  ):
      step_name = "original_func_step"
  
      @step(
          name=step_name,
          role=role,
          image_uri=dummy_container_without_error,
          instance_type=INSTANCE_TYPE,
          keep_alive_period_in_seconds=60,
      )
      def original_func(x):
          return x * x
  
      def updated_func(x):
          return x + 25
  
      pickled_updated_func = CloudpickleSerializer.serialize(
          updated_func
      )
  
      step_a = original_func(10)
  
      pipeline = Pipeline(
          name=pipeline_name,
          steps=[step_a],
          sagemaker_session=sagemaker_session,
      )
  
      try:
          pipeline.create(role)
  
          pipeline_definition = json.loads(
              pipeline.describe()["PipelineDefinition"]
          )
          s3_base_uri = pipeline_definition["Steps"][0]["Arguments"][
              "OutputDataConfig"
          ]["S3OutputPath"]
          step_container_args = pipeline_definition["Steps"][0][
              "Arguments"
          ]["AlgorithmSpecification"]["ContainerArguments"]
          build_time = step_container_args[
              step_container_args.index("--func_step_s3_dir") + 1
          ]
  
          # some other user updates the pickled function code
          S3Uploader.upload_bytes(
              pickled_updated_func,
              s3_path_join(
                  s3_base_uri,
                  step_name,
                  build_time,
                  "function",
                  "payload.pkl",
              ),
              kms_key=None,
              sagemaker_session=sagemaker_session,
          )
          execution = pipeline.start()
          wait_pipeline_execution(
              execution=execution, delay=20, max_attempts=20
          )
          execution_steps = execution.list_steps()
  
          assert execution_steps[0]["StepStatus"] == "Failed"
          assert (
              "Integrity check for the serialized function or data failed"
              in execution_steps[0]["FailureReason"]
          )
      finally:
          try:
              pipeline.delete()
          except Exception:
              pass
  
imports: from __future__ import absolute_import
  import json
  import numpy
  import pytest
  import os
  import random
  from sagemaker import get_execution_role, utils
  from sagemaker.config import load_sagemaker_config
  from sagemaker.processing import ProcessingInput
  from sagemaker.remote_function.errors import RemoteFunctionError
  from sagemaker.sklearn import SKLearnProcessor
  from sagemaker.remote_function.core.serialization import CloudpickleSerializer
  from sagemaker.s3 import S3Uploader
  from sagemaker.s3_utils import s3_path_join
  from sagemaker.workflow.conditions import ConditionLessThan
  from sagemaker.workflow.fail_step import FailStep
  from sagemaker.workflow.function_step import step
  from sagemaker.workflow.condition_step import ConditionStep
  from sagemaker.workflow.conditions import ConditionEquals
  from sagemaker.workflow.pipeline import Pipeline
  from sagemaker.workflow.parameters import ParameterString, ParameterInteger, ParameterFloat, ParameterBoolean
  from sagemaker.workflow.step_outputs import get_step
  from sagemaker.workflow.steps import ProcessingStep
  from tests.integ.sagemaker.workflow.helpers import create_and_execute_pipeline, wait_pipeline_execution
  from tests.integ import DATA_DIR
label_desc: Use image node_id 16 for calling a global function with example usage: test_decorator_step_checksum_mismatch(sagemaker_session, dummy_container_without_error, pipeline_name, role) and returns: unknown, unknown