code: def test_presets():
      expected_config = dict(presets=["best_quality"])
      actual_config = ConfigBuilder().presets("best_quality").build()
      assert actual_config == expected_config
  
      actual_config = ConfigBuilder().presets(["best_quality"]).build()
      assert actual_config == expected_config
  
      expected_config = dict(
          presets=["best_quality", "optimize_for_deployment"]
      )
      actual_config = (
          ConfigBuilder()
          .presets(["best_quality", "optimize_for_deployment"])
          .build()
      )
      assert actual_config == expected_config
  
      expected_config = dict(presets={"a": 42})
      actual_config = ConfigBuilder().presets({"a": 42}).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 1 for calling a global function with example usage: test_presets() without return types