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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def _create_warm_start_tuner(self, additional_parents, warm_start_type, estimator=None):
 """Creates a new ``HyperparameterTuner`` with ``WarmStartConfig``, where type will be equal to ``warm_start_type`` and``parents`` would be equal to union of ``additional_parents`` and self. Args: additional_parents (set{str}):
 Additional parents along with self, to be used for warm starting. warm_start_type (sagemaker.tuner.WarmStartTypes):
 Type of warm start job. Returns: sagemaker.tuner.HyperparameterTuner: Instance with the request fields copied from self along with the warm start configuration """

        all_parents = {self.latest_tuning_job.name}
        if additional_parents:
            all_parents = all_parents.union(additional_parents)

        return HyperparameterTuner(estimator=estimator if estimator else self.estimator,
                                   objective_metric_name=self.objective_metric_name,
                                   hyperparameter_ranges=self._hyperparameter_ranges,
                                   objective_type=self.objective_type,
                                   max_jobs=self.max_jobs,
                                   max_parallel_jobs=self.max_parallel_jobs,
                                   warm_start_config=WarmStartConfig(warm_start_type=warm_start_type,
                                                                     parents=all_parents))