docstr: Given a configuration in config, this procedure makes sure that
  the given implementation, which should be a autosklearn component, honors
  is created with the desired hyperparameters stated in config_dict
docstr_tok: ["Given","a","configuration","in","config",",","this","procedure","makes","sure","that","the","given","implementation",",","which","should","be","a","autosklearn","component",",","honors","is","created","with","the","desired","hyperparameters","stated","in","config_dict"]
code: def _test_set_hyperparameter_component(
      self, expected_key, implementation, config_dict
  ):
      """
      Given a configuration in config, this procedure makes sure that
      the given implementation, which should be a autosklearn component, honors
      is created with the desired hyperparameters stated in config_dict
      """
      keys_checked = []
      attributes = vars(implementation)
      expected_attributes = {}
      for key, value in config_dict.items():
          if expected_key in key:
              keys_checked.append(key)
              key = key.replace(expected_key + ":", "")
              if ":" in key:
                  raise ValueError(
                      "This utility should only be called with a "
                      "matching string that produces leaf configurations, "
                      "that is no further colons are expected, yet key={}"
                      "".format(key)
                  )
              expected_attributes[key] = value
      # Cannot check the whole dictionary, just names, as some
      # classes map the text hyperparameter directly to a function!
      for expected_attribute in expected_attributes.keys():
          self.assertIn(expected_attribute, attributes.keys())
      return keys_checked
  
imports: import copy
  import itertools
  import resource
  import tempfile
  import numpy
  import sklearn.datasets
  import sklearn.decomposition
  import sklearn.ensemble
  import sklearn.svm
  from ConfigSpace.configuration_space import ConfigurationSpace
  from ConfigSpace.hyperparameters import CategoricalHyperparameter
  from joblib import Memory
  from sklearn.base import clone
  from sklearn.utils.validation import check_is_fitted
  import autosklearn.pipeline.components.feature_preprocessing
  import autosklearn.pipeline.components.regression
  from autosklearn.pipeline.components.base import AutoSklearnChoice, AutoSklearnComponent, AutoSklearnPreprocessingAlgorithm, AutoSklearnRegressionAlgorithm
  from autosklearn.pipeline.constants import DENSE, PREDICTIONS, SIGNED_DATA, SPARSE, UNSIGNED_DATA
  from autosklearn.pipeline.regression import SimpleRegressionPipeline
  from autosklearn.pipeline.util import get_dataset
  import unittest
  import unittest.mock
  from test.test_pipeline.ignored_warnings import ignore_warnings, regressor_warnings
label_desc: Use image node_id 26 for calling the SimpleRegressionPipelineTest obj's underlying member method code with example usage: obj._test_set_hyperparameter_component(expected_key, implementation, config_dict) and returns: keys_checked