code: def clarify_processor_with_job_name_prefix(sagemaker_session):
      return SageMakerClarifyProcessor(
          role="AmazonSageMaker-ExecutionRole",
          instance_count=1,
          instance_type="ml.c5.xlarge",
          sagemaker_session=sagemaker_session,
          job_name_prefix=JOB_NAME_PREFIX,
      )
  
imports: from __future__ import absolute_import, print_function
  import copy
  import pytest
  from mock import MagicMock, Mock, patch
  from sagemaker import Processor, image_uris
  from sagemaker.clarify import BiasConfig, DataConfig, ModelConfig, ModelPredictedLabelConfig, PDPConfig, SageMakerClarifyProcessor, SHAPConfig, TextConfig, ImageConfig, _AnalysisConfigGenerator, DatasetType, ProcessingOutputHandler, SegmentationConfig
label_desc: Use image node_id 29 for calling a global function with example usage: clarify_processor_with_job_name_prefix(sagemaker_session) and returns: SageMakerClarifyProcessor