code: def reduce_configs(self):
          
          experiment_ids = self.get_reduced_configs()
          experiments = self.experiment_group.experiments.filter(id__in=experiment_ids)
          self.create_iteration()
          iteration_config = self.experiment_group.iteration_config
          hptuning_config = self.experiment_group.hptuning_config
          n_resources = self.experiment_group.search_manager.get_resources_for_iteration(
              iteration=iteration_config.iteration)
          resource_value = self.experiment_group.search_manager.get_n_resources(
              n_resources=n_resources, bracket_iteration=iteration_config.bracket_iteration
          )
          resource_name = hptuning_config.hyperband.resource.name
          resource_value = hptuning_config.hyperband.resource.cast_value(resource_value)
  
          # Check if we need to resume or restart the experiments
          for experiment in experiments:
              declarations = experiment.declarations
              declarations[resource_name] = resource_value
              declarations_spec = {'declarations': declarations}
              specification = experiment.specification.patch(declarations_spec)
              status_message = 'Hyperband iteration: {}, bracket iteration: {}'.format(
                  iteration_config.iteration,
                  iteration_config.bracket_iteration)
  
              if hptuning_config.hyperband.resume:
                  experiment.resume(
                      declarations=declarations,
                      config=specification.parsed_data,
                      message=status_message)
              else:
                  experiment.restart(
                      experiment_group=self.experiment_group,
                      declarations=declarations,
                      config=specification.parsed_data)
docs: Reduce the experiments to restart.