code: def create_adult_income_dataset(create_small_dataset=True):
      # workaround for SSL expiration error from UCI website
      default_http_context = ssl._create_default_https_context
      ssl._create_default_https_context = ssl._create_unverified_context
      fetcher = FetchDiceAdultCensusIncomeDataset()
      action_name = "Adult dataset download"
      err_msg = "Failed to download adult dataset"
      max_retries = 4
      retry_delay = 60
      dataset = retry_function(
          fetcher.fetch,
          action_name,
          err_msg,
          max_retries=max_retries,
          retry_delay=retry_delay,
      )
      continuous_features = ["age", "hours_per_week"]
      target_name = "income"
      target = dataset[target_name]
      classes = list(np.unique(target))
      feature_columns = dataset.drop(
          columns=[target_name]
      ).columns.tolist()
      feature_range_keys = [
          "column_name",
          "range_type",
          "unique_values",
      ]
      categorical_features = list(
          set(dataset.columns)
          - set(continuous_features)
          - set([target_name])
      )
      # Split data into train and test
      if create_small_dataset:
          data_train, data_test, y_train, y_test = train_test_split(
              dataset,
              target,
              train_size=500,
              test_size=50,
              random_state=7,
              stratify=target,
          )
      else:
          data_train, data_test, y_train, y_test = train_test_split(
              dataset,
              target,
              test_size=5000,
              random_state=7,
              stratify=target,
          )
      ssl._create_default_https_context = default_http_context
      return (
          data_train,
          data_test,
          y_train,
          y_test,
          categorical_features,
          continuous_features,
          target_name,
          classes,
          feature_columns,
          feature_range_keys,
      )
  
imports: import json
  import random
  import ssl
  import numpy
  import pandas
  import pytest
  from dice_ml.utils import helpers
  from sklearn.model_selection import train_test_split
  from rai_test_utils.datasets.tabular import create_iris_data
  from raiutils.common.retries import retry_function
label_desc: Use image node_id 3 for calling a global function with example usage: create_adult_income_dataset(create_small_dataset) and returns: data_train,  data_test,  y_train,  y_test,  categorical_features,  continuous_features,  target_name,  classes,  feature_columns,  feature_range_keys