@classmethod
def _map_tuning_config(cls, strategy, max_jobs, max_parallel_jobs,
    early_stopping_type='Off', objective_type=None, objective_metric_name=
    None, parameter_ranges=None):
    """
        Construct tuning job configuration dictionary.

        Args:
            strategy (str): Strategy to be used for hyperparameter estimations.
            max_jobs (int): Maximum total number of training jobs to start for the hyperparameter
                tuning job.
            max_parallel_jobs (int): Maximum number of parallel training jobs to start.
            early_stopping_type (str): Specifies whether early stopping is enabled for the job.
                Can be either 'Auto' or 'Off'. If set to 'Off', early stopping will not be
                attempted. If set to 'Auto', early stopping of some training jobs may happen,
                but is not guaranteed to.
            objective_type (str): The type of the objective metric for evaluating training jobs.
                This value can be either 'Minimize' or 'Maximize'.
            objective_metric_name (str): Name of the metric for evaluating training jobs.
            parameter_ranges (dict): Dictionary of parameter ranges. These parameter ranges can
                be one of three types: Continuous, Integer, or Categorical.

        Returns:
            A dictionary of tuning job configuration. For format details, please refer to
            HyperParameterTuningJobConfig as described in
            https://botocore.readthedocs.io/en/latest/reference/services/sagemaker.html#SageMaker.Client.create_hyper_parameter_tuning_job
        """
    tuning_config = {'Strategy': strategy, 'ResourceLimits': {
        'MaxNumberOfTrainingJobs': max_jobs, 'MaxParallelTrainingJobs':
        max_parallel_jobs}, 'TrainingJobEarlyStoppingType': early_stopping_type
        }
    tuning_objective = cls._map_tuning_objective(objective_type,
        objective_metric_name)
    if tuning_objective is not None:
        tuning_config['HyperParameterTuningJobObjective'] = tuning_objective
    if parameter_ranges is not None:
        tuning_config['ParameterRanges'] = parameter_ranges
    return tuning_config
