code: def test_predict_marginalized_no_features():
      """The RF should fall back to the regular predict() method."""
  
      rs = np.random.RandomState(1)
      X = rs.rand(20, 10)
      Y = rs.rand(10, 1)
      model = RandomForest(configspace=_get_cs(10))
      model.train(X[:10], Y[:10])
      model.predict(X[10:])
  
file_path: SMAC3/tests/test_model/test_rf.py
imports: import numpy
  import pytest
  from ConfigSpace import CategoricalHyperparameter, ConfigurationSpace, EqualsCondition, OrdinalHyperparameter, UniformFloatHyperparameter, UniformIntegerHyperparameter
  from smac.model.random_forest.random_forest import RandomForest
  from smac.utils.configspace import convert_configurations_to_array
label_desc: Use image node_id 6 for calling a global function with example usage: test_predict_marginalized_no_features() without return types