code: def test_model_quality_check_step(
      sagemaker_session,
      check_job_config,
      model_package_group_name,
      supplied_baseline_statistics_uri,
      supplied_baseline_constraints_uri,
  ):
      model_quality_check_config = ModelQualityCheckConfig(
          baseline_dataset="baseline_dataset_s3_url",
          dataset_format=DatasetFormat.csv(header=True),
          problem_type="BinaryClassification",
          probability_attribute=0,  # the integer should be converted to str by SDK
          ground_truth_attribute=None,
          probability_threshold_attribute=0.5,  # the float should be converted to str by SDK
          post_analytics_processor_script="s3://my_bucket/data_quality/postprocessor.py",
          output_s3_uri="",
      )
      model_quality_check_step = QualityCheckStep(
          name="ModelQualityCheckStep",
          register_new_baseline=False,
          skip_check=False,
          fail_on_violation=True,
          quality_check_config=model_quality_check_config,
          check_job_config=check_job_config,
          model_package_group_name=model_package_group_name,
          supplied_baseline_statistics=supplied_baseline_statistics_uri,
          supplied_baseline_constraints=supplied_baseline_constraints_uri,
      )
      pipeline = Pipeline(
          name="MyPipeline",
          parameters=[
              supplied_baseline_statistics_uri,
              supplied_baseline_constraints_uri,
              model_package_group_name,
          ],
          steps=[model_quality_check_step],
          sagemaker_session=sagemaker_session,
      )
  
      step_definition = _get_step_definition_for_test(pipeline)
  
      assert step_definition == _expected_model_quality_dsl
  
file_path: sagemaker-python-sdk/tests/unit/sagemaker/workflow/test_quality_check_step.py
imports: from __future__ import absolute_import
  import json
  import pytest
  from sagemaker.model_monitor import DatasetFormat
  from sagemaker.workflow.parameters import ParameterString
  from sagemaker.workflow.pipeline import Pipeline
  from sagemaker.workflow.pipeline import PipelineDefinitionConfig
  from sagemaker.workflow.quality_check_step import QualityCheckStep, DataQualityCheckConfig, ModelQualityCheckConfig, QualityCheckConfig
  from sagemaker.workflow.steps import CacheConfig
  from sagemaker.workflow.check_job_config import CheckJobConfig
label_desc: Use image node_id 6 for calling a global function with example usage: test_model_quality_check_step(sagemaker_session, check_job_config, model_package_group_name, supplied_baseline_statistics_uri, supplied_baseline_constraints_uri) without return types