code: def _test_preprocessing_dtype(self):
      # Dense
      # np.float32
      X_train, Y_train, X_test, Y_test = get_dataset("iris")
      self.assertEqual(X_train.dtype, np.float32)
  
      configuration_space = Nystroem.get_hyperparameter_search_space()
      default = configuration_space.get_default_configuration()
      preprocessor = Nystroem(
          random_state=1,
          **{
              hp.hyperparameter.name: hp.value
              for hp in default.values.values()
          },
      )
      preprocessor.fit(X_train)
      Xt = preprocessor.transform(X_train)
      self.assertEqual(Xt.dtype, np.float32)
  
      # np.float64
      X_train, Y_train, X_test, Y_test = get_dataset("iris")
      X_train = X_train.astype(np.float64)
      configuration_space = Nystroem.get_hyperparameter_search_space()
      default = configuration_space.get_default_configuration()
      preprocessor = Nystroem(
          random_state=1,
          **{
              hp.hyperparameter.name: hp.value
              for hp in default.values.values()
          },
      )
      preprocessor.fit(X_train, Y_train)
      Xt = preprocessor.transform(X_train)
      self.assertEqual(Xt.dtype, np.float64)
  
      # Sparse
      # np.float32
      X_train, Y_train, X_test, Y_test = get_dataset(
          "iris", make_sparse=True
      )
      self.assertEqual(X_train.dtype, np.float32)
      configuration_space = Nystroem.get_hyperparameter_search_space()
      default = configuration_space.get_default_configuration()
      preprocessor = Nystroem(
          random_state=1,
          **{
              hp.hyperparameter.name: hp.value
              for hp in default.values.values()
          },
      )
      preprocessor.fit(X_train)
      Xt = preprocessor.transform(X_train)
      self.assertEqual(Xt.dtype, np.float32)
  
      # np.float64
      X_train, Y_train, X_test, Y_test = get_dataset(
          "iris", make_sparse=True
      )
      X_train = X_train.astype(np.float64)
      configuration_space = Nystroem.get_hyperparameter_search_space()
      default = configuration_space.get_default_configuration()
      preprocessor = Nystroem(
          random_state=1,
          **{
              hp.hyperparameter.name: hp.value
              for hp in default.values.values()
          },
      )
      preprocessor.fit(X_train)
      Xt = preprocessor.transform(X_train)
      self.assertEqual(Xt.dtype, np.float64)
  
file_path: auto-sklearn/test/test_pipeline/components/feature_preprocessing/test_nystroem_sampler.py
imports: import numpy
  import sklearn.preprocessing
  from autosklearn.pipeline.components.feature_preprocessing.nystroem_sampler import Nystroem
  from autosklearn.pipeline.util import _test_preprocessing, get_dataset
  import unittest
label_desc: Use image node_id 2 for calling the NystroemComponentTest obj's underlying member method code with example usage: obj._test_preprocessing_dtype() without return types