code: def test_excluded_model_types():
      expected_config = dict(excluded_model_types=["RF"])
      actual_config = ConfigBuilder().excluded_model_types("RF").build()
      assert actual_config == expected_config
  
      actual_config = (
          ConfigBuilder().excluded_model_types(["RF"]).build()
      )
      assert actual_config == expected_config
  
      expected_config = dict(excluded_model_types=["LR", "RF"])
      actual_config = (
          ConfigBuilder().excluded_model_types(["RF", "LR"]).build()
      )
      assert actual_config == expected_config
  
      expected_config = dict(excluded_model_types=["RF"])
      actual_config = (
          ConfigBuilder().excluded_model_types(["RF", "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 3 for calling a global function with example usage: test_excluded_model_types() without return types