code: def test_feature_generator_builder_standalone():
      vectorizer = CountVectorizer(
          min_df=7, ngram_range=(2, 3), max_features=11, dtype=np.uint8
      )
  
      generator = (
          FeatureGeneratorBuilder()
          .enable_numeric_features()
          .enable_categorical_features()
          .enable_datetime_features()
          .enable_text_special_features()
          .enable_text_ngram_features()
          .enable_raw_text_features()
          .enable_vision_features()
          .vectorizer(vectorizer)
          .text_ngram_params({"vectorizer_strategy": "both"})
          .build()
      )
      assert generator.enable_numeric_features is True
      assert generator.enable_categorical_features is True
      assert generator.enable_datetime_features is True
      assert generator.enable_text_special_features is True
      assert generator.enable_text_ngram_features is True
      assert generator.enable_raw_text_features is True
      assert generator.enable_vision_features is True
  
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 30 for calling a global function with example usage: test_feature_generator_builder_standalone() without return types