code: def test_shap(
      name_from_base,
      clarify_processor,
      clarify_processor_with_job_name_prefix,
      data_config,
      model_config,
      shap_config,
  ):
      expected_predictor_config = {
          "model_name": "xgboost-model",
          "instance_type": "ml.c5.xlarge",
          "initial_instance_count": 1,
      }
      _run_test_explain(
          name_from_base,
          clarify_processor,
          clarify_processor_with_job_name_prefix,
          data_config,
          model_config,
          shap_config,
          None,
          None,
          expected_predictor_config,
      )
  
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 42 for calling a global function with example usage: test_shap(name_from_base, clarify_processor, clarify_processor_with_job_name_prefix, data_config, model_config, shap_config) without return types