code: def shap_config():
      return SHAPConfig(
          baseline=[
              [
                  0.26124998927116394,
                  0.2824999988079071,
                  0.06875000149011612,
              ],
          ],
          num_samples=100,
          agg_method="mean_sq",
      )
  
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 34 for calling a global function with example usage: shap_config() and returns: SHAPConfig