code: def test_model_explainability_check_step(
      sagemaker_session,
      check_job_config,
      model_package_group_name,
      data_config,
      model_config,
      shap_config,
  ):
      model_explainability_check_config = (
          ModelExplainabilityCheckConfig(
              data_config=data_config,
              model_config=model_config,
              explainability_config=shap_config,
          )
      )
      model_explainability_check_step = ClarifyCheckStep(
          name="ModelExplainabilityCheckStep",
          clarify_check_config=model_explainability_check_config,
          check_job_config=check_job_config,
          skip_check=False,
          fail_on_violation=False,
          register_new_baseline=False,
          model_package_group_name=model_package_group_name,
          supplied_baseline_constraints="supplied_baseline_constraints",
      )
      pipeline = Pipeline(
          name="MyPipeline",
          parameters=[model_package_group_name],
          steps=[model_explainability_check_step],
          sagemaker_session=sagemaker_session,
      )
  
      assert (
          json.loads(pipeline.definition())["Steps"][0]
          == _expected_model_explainability_dsl
      )
      assert re.match(
          f"s3://{_DEFAULT_BUCKET}/{_MODEL_MONITOR_S3_PATH}"
          + f"/{_EXPLAINABILITY_MONITORING_CFG_BASE_NAME}-configuration"
          + f"/{_EXPLAINABILITY_MONITORING_CFG_BASE_NAME}-config-.*/.*/analysis_config.json",
          model_explainability_check_config.monitoring_analysis_config_uri,
      )
  
imports: from __future__ import absolute_import
  import json
  import re
  import pytest
  from sagemaker.clarify import DataConfig, BiasConfig, ModelConfig, ModelPredictedLabelConfig, SHAPConfig
  from sagemaker.workflow.clarify_check_step import DataBiasCheckConfig, ClarifyCheckStep, ModelBiasCheckConfig, ModelExplainabilityCheckConfig, ClarifyCheckConfig, _EXPLAINABILITY_MONITORING_CFG_BASE_NAME, _BIAS_MONITORING_CFG_BASE_NAME
  from sagemaker.model_monitor.model_monitoring import _MODEL_MONITOR_S3_PATH
  from sagemaker.workflow.parameters import ParameterString
  from sagemaker.workflow.pipeline import Pipeline
  from sagemaker.workflow.pipeline import PipelineDefinitionConfig
  from sagemaker.workflow.steps import CacheConfig
  from sagemaker.workflow.check_job_config import CheckJobConfig
label_desc: Use image node_id 10 for calling a global function with example usage: test_model_explainability_check_step(sagemaker_session, check_job_config, model_package_group_name, data_config, model_config, shap_config) without return types