code: def generate_data(self, testtype, n, code_string):
      # numeric; integer, string categorical, list categorical, dictionary,
      # array, nd array (1 dim), nd array (4 dim).
  
      if testtype == "regression":
          sf = tc.util.generate_random_regression_sframe(
              n, code_string, random_seed=1
          )
          test_sf = tc.util.generate_random_regression_sframe(
              n, code_string, random_seed=2
          )
  
      elif testtype == "classification":
          sf = tc.util.generate_random_classification_sframe(
              n, code_string, 2, random_seed=1
          )
          test_sf = tc.util.generate_random_classification_sframe(
              n, code_string, 2, random_seed=2
          )
  
      elif testtype == "multiclass":
          sf = tc.util.generate_random_classification_sframe(
              n, code_string, 10, random_seed=1
          )
          test_sf = tc.util.generate_random_classification_sframe(
              n, code_string, 10, random_seed=2
          )
  
      else:
          assert False
  
      return sf, test_sf
  
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import absolute_import
  import unittest
  import tempfile
  import turicreate
  import math
  import uuid
  import random
  import copy
  from turicreate.toolkits import evaluation
  from turicreate.toolkits._main import ToolkitError
  from turicreate.toolkits._internal_utils import _mac_ver
  import shutil
  import numpy
  import sys
  import platform
  import array
  import os
  import pytest
label_desc: Use image node_id 1 for calling the CoreMLExportTest obj's underlying member method code with example usage: obj.generate_data(testtype, n, code_string) and returns: sf,  test_sf