code: def test_hyperparameters_dict():
      expected_config = dict(hyperparameters={"RF": {}})
      actual_config = (
          ConfigBuilder().hyperparameters({"RF": {}}).build()
      )
      assert actual_config == expected_config
  
      class CustomKNN(KNNModel):
          pass
  
      expected_config = dict(
          hyperparameters={CustomKNN: [{}, {"prop": 42}]}
      )
      actual_config = (
          ConfigBuilder()
          .hyperparameters({CustomKNN: [{}, {"prop": 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 10 for calling a global function with example usage: test_hyperparameters_dict() without return types