code: def test_rai_insights_binary(self, manager_type):
      (
          X_train,
          y_train,
          X_test,
          y_test,
          classes,
      ) = create_binary_classification_dataset()
  
      models = create_models_classification(X_train, y_train)
      X_train[LABELS] = y_train
      X_test[LABELS] = y_test
      manager_args = {ManagerParams.TREATMENT_FEATURES: ["col0"]}
  
      for model in models:
          run_rai_insights(
              model,
              X_train,
              X_test,
              LABELS,
              None,
              manager_type,
              manager_args,
              classes=classes,
          )
  
imports: import os
  import pickle
  from pathlib import Path
  from tempfile import TemporaryDirectory
  import numpy
  import pandas
  import pytest
  from tests.causal_manager_validator import validate_causal
  from tests.common_utils import create_iris_data
  from tests.counterfactual_manager_validator import validate_counterfactual
  from tests.error_analysis_validator import setup_error_analysis, validate_error_analysis
  from tests.explainer_manager_validator import setup_explainer, validate_explainer
  from rai_test_utils.datasets.tabular import create_binary_classification_dataset, create_cancer_data, create_housing_data
  from rai_test_utils.models.model_utils import create_models_classification, create_models_regression
  from rai_test_utils.models.sklearn import create_complex_classification_pipeline
  from rai_test_utils.utilities import is_valid_uuid
  from raiutils.models import ModelTask
  from responsibleai import RAIInsights
  from responsibleai._internal.constants import ManagerNames, SerializationAttributes
  from responsibleai._tools.shared.state_directory_management import DirectoryManager
  from responsibleai.feature_metadata import FeatureMetadata
label_desc: Use image node_id 3 for calling the TestRAIInsights obj's underlying member method code with example usage: obj.test_rai_insights_binary(manager_type) without return types