code: def shap_config():
      return SHAPConfig(
          baseline=SHAP_BASELINE,
          num_samples=SHAP_NUM_SAMPLES,
          agg_method=SHAP_AGG_METHOD,
          use_logit=SHAP_USE_LOGIT,
      )
  
imports: from __future__ import print_function, absolute_import
  import copy
  import json
  import time
  from mock import patch, Mock, MagicMock
  import pytest
  from sagemaker.clarify import BiasConfig, DataConfig, ModelConfig, SHAPConfig, ModelPredictedLabelConfig
  from sagemaker.model_monitor import BiasAnalysisConfig, Constraints, CronExpressionGenerator, EndpointInput, BatchTransformInput, ExplainabilityAnalysisConfig, ModelBiasMonitor, ModelExplainabilityMonitor, MonitoringExecution, NetworkConfig
  from sagemaker.model_monitor.clarify_model_monitoring import ClarifyModelMonitor, ClarifyBaseliningJob, ClarifyMonitoringExecution
  from sagemaker.model_monitor.dataset_format import MonitoringDatasetFormat
label_desc: Use image node_id 10 for calling a global function with example usage: shap_config() and returns: SHAPConfig