code: def test_included_model_types():
      expected_config = dict(
          excluded_model_types=[
              "XT",
              "KNN",
              "GBM",
              "CAT",
              "XGB",
              "NN_TORCH",
              "LR",
              "FASTAI",
              "TRANSF",
              "AG_TEXT_NN",
              "AG_IMAGE_NN",
              "AG_AUTOMM",
              "FT_TRANSFORMER",
              "TABPFN",
              "FASTTEXT",
              "IM_RULEFIT",
              "IM_GREEDYTREE",
              "IM_FIGS",
              "IM_HSTREE",
              "IM_BOOSTEDRULES",
              "VW",
              "DUMMY",
          ]
      )
      actual_config = ConfigBuilder().included_model_types("RF").build()
      assert actual_config == expected_config
  
      actual_config = (
          ConfigBuilder().included_model_types(["RF"]).build()
      )
      assert actual_config == expected_config
  
      actual_config = (
          ConfigBuilder().included_model_types(["RF", "RF"]).build()
      )
      assert actual_config == expected_config
  
      expected_config = dict(
          excluded_model_types=[
              "XT",
              "KNN",
              "GBM",
              "CAT",
              "XGB",
              "NN_TORCH",
              "FASTAI",
              "TRANSF",
              "AG_TEXT_NN",
              "AG_IMAGE_NN",
              "AG_AUTOMM",
              "FT_TRANSFORMER",
              "TABPFN",
              "FASTTEXT",
              "IM_RULEFIT",
              "IM_GREEDYTREE",
              "IM_FIGS",
              "IM_HSTREE",
              "IM_BOOSTEDRULES",
              "VW",
              "DUMMY",
          ]
      )
      actual_config = (
          ConfigBuilder().included_model_types(["RF", "LR"]).build()
      )
      assert actual_config == expected_config
  
      class CustomKNN(KNNModel):
          pass
  
      expected_config = dict(
          excluded_model_types=[
              "XT",
              "KNN",
              "GBM",
              "CAT",
              "XGB",
              "NN_TORCH",
              "LR",
              "FASTAI",
              "TRANSF",
              "AG_TEXT_NN",
              "AG_IMAGE_NN",
              "AG_AUTOMM",
              "FT_TRANSFORMER",
              "TABPFN",
              "FASTTEXT",
              "IM_RULEFIT",
              "IM_GREEDYTREE",
              "IM_FIGS",
              "IM_HSTREE",
              "IM_BOOSTEDRULES",
              "VW",
              "DUMMY",
          ]
      )
      actual_config = (
          ConfigBuilder()
          .included_model_types([CustomKNN, "RF"])
          .build()
      )
      assert actual_config == expected_config
  
imports: import numpy
  import pytest
  from sklearn.feature_extraction.text import CountVectorizer
  from autogluon.features import TextNgramFeatureGenerator
  from autogluon.tabular.configs.config_helper import ConfigBuilder, FeatureGeneratorBuilder
  from autogluon.tabular.models import KNNModel
label_desc: Use image node_id 5 for calling a global function with example usage: test_included_model_types() without return types