code: def test_rai_insights_save_load_add_dropped_features(
      self, manager_type, adult_data
  ):
      (
          data_train,
          data_test,
          y_train,
          y_test,
          categorical_features,
          continuous_features,
          target_name,
          classes,
          feature_columns,
          feature_range_keys,
      ) = adult_data
  
      dropped_features = ADULT_DROPPED_FEATURES
      categorical_features_after_drop = (
          ADULT_CATEGORICAL_FEATURES_AFTER_DROP
      )
  
      X_train = data_train.drop(
          [target_name] + dropped_features, axis=1
      )
  
      model = create_complex_classification_pipeline(
          X_train,
          y_train,
          continuous_features,
          categorical_features_after_drop,
      )
  
      # Cut down size for counterfactuals, in the interests of speed
      if manager_type == ManagerNames.COUNTERFACTUAL:
          data_test = data_test[0:1]
  
      feature_metadata = FeatureMetadata(
          dropped_features=dropped_features
      )
  
      save_load_add_rai_insights(
          manager_type=manager_type,
          data_train=data_train,
          data_test=data_test,
          target_name=target_name,
          categorical_features=categorical_features,
          feature_columns=feature_columns,
          feature_range_keys=feature_range_keys,
          feature_metadata=feature_metadata,
          model=model,
      )
  
imports: import os
  from pathlib import Path
  from tempfile import TemporaryDirectory
  import numpy
  import pandas
  import pytest
  from tests.common_utils import ADULT_CATEGORICAL_FEATURES_AFTER_DROP, ADULT_DROPPED_FEATURES, create_iris_data
  from rai_test_utils.datasets.tabular import create_binary_classification_dataset
  from rai_test_utils.models.lightgbm import create_lightgbm_classifier
  from rai_test_utils.models.sklearn import create_complex_classification_pipeline
  from raiutils.models import ModelTask
  from responsibleai import RAIInsights
  from responsibleai._internal.constants import ManagerNames, SerializationAttributes
  from responsibleai.feature_metadata import FeatureMetadata
label_desc: Use image node_id 6 for calling the TestRAIInsightsSaveAndLoadScenarios obj's underlying member method code with example usage: obj.test_rai_insights_save_load_add_dropped_features(manager_type, adult_data) without return types