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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 hyperparameter_ranges(self):
 """Return the hyperparameter ranges in a dictionary to be used as part of a request for creating a hyperparameter tuning job. """

        hyperparameter_ranges = dict()
        for range_type in ParameterRange.__all_types__:
            parameter_ranges = []
            for parameter_name, parameter in self._hyperparameter_ranges.items():
                if parameter is not None and parameter.__name__ == range_type:
                    # Categorical parameters needed to be serialized as JSON for our framework containers
                    if isinstance(parameter, CategoricalParameter) and isinstance(self.estimator, Framework):
                        tuning_range = parameter.as_json_range(parameter_name)
                    else:
                        tuning_range = parameter.as_tuning_range(parameter_name)
                    parameter_ranges.append(tuning_range)
            hyperparameter_ranges[range_type + 'ParameterRanges'] = parameter_ranges
        return hyperparameter_ranges