code: def test_rai_insights_binary_mixed_types(
      self, manager_type, add_boolean, adult_data
  ):
      (
          data_train,
          data_test,
          y_train,
          y_test,
          categorical_features,
          continuous_features,
          target_name,
          classes,
          feature_columns,
          feature_range_keys,
      ) = adult_data
  
      if add_boolean:
          data_train = data_train.copy()
          data_test = data_test.copy()
          data_train["is_adult"] = data_train["age"] >= 18
          data_test["is_adult"] = data_test["age"] >= 18
          categorical_features = categorical_features + ["is_adult"]
  
      X_train = data_train.drop([target_name], axis=1)
      dropped_feature = "education"
      X_train_after_drop = X_train.drop([dropped_feature], axis=1)
      categorical_features_after_drop = categorical_features.copy()
      categorical_features_after_drop.remove(dropped_feature)
  
      model = create_complex_classification_pipeline(
          X_train_after_drop,
          y_train,
          continuous_features,
          categorical_features_after_drop,
      )
      manager_args = {
          ManagerParams.TREATMENT_FEATURES: ["age", "hours_per_week"],
          ManagerParams.DESIRED_CLASS: "opposite",
          ManagerParams.FEATURE_IMPORTANCE: False,
      }
  
      feature_metadata = FeatureMetadata(
          dropped_features=[dropped_feature]
      )
      run_rai_insights(
          model,
          data_train,
          data_test,
          target_name,
          categorical_features,
          manager_type,
          manager_args,
          classes=classes,
          feature_metadata=feature_metadata,
      )
  
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 4 for calling the TestRAIInsights obj's underlying member method code with example usage: obj.test_rai_insights_binary_mixed_types(manager_type, add_boolean, adult_data) without return types