code: def test_feature_generator_2():
      config = (
          ConfigBuilder()
          .feature_generator()
          .enable_numeric_features(False)
          .enable_categorical_features(False)
          .enable_datetime_features(False)
          .enable_text_special_features(False)
          .enable_text_ngram_features(False)
          .enable_raw_text_features(False)
          .enable_vision_features(False)
          .build()
          .build()
      )
  
      assert (
          config["feature_generator"].enable_numeric_features is False
      )
      assert (
          config["feature_generator"].enable_categorical_features
          is False
      )
      assert (
          config["feature_generator"].enable_datetime_features is False
      )
      assert (
          config["feature_generator"].enable_text_special_features
          is False
      )
      assert (
          config["feature_generator"].enable_text_ngram_features
          is False
      )
      assert (
          config["feature_generator"].enable_raw_text_features is False
      )
      assert config["feature_generator"].enable_vision_features is False
  
      text_gen = None
      generators_classes = []
      for gl in config["feature_generator"].generators:
          for g in gl:
              if isinstance(g, TextNgramFeatureGenerator):
                  text_gen = g
              generators_classes.append(g.__class__.__name__)
      assert text_gen is None
      assert sorted(list(set(generators_classes))) == [
          "AsTypeFeatureGenerator",
          "DropDuplicatesFeatureGenerator",
          "DropUniqueFeatureGenerator",
          "FillNaFeatureGenerator",
      ]
  
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 29 for calling a global function with example usage: test_feature_generator_2() without return types