code: def save_checkpoint(self):
      runner_state = self.runner.get_runner_state()
      metarunner_state = self.get_state()
      print("Saving State")
      self.checkpoint_saver.save(
          runner_state=runner_state, metarunner_state=metarunner_state
      )
  
imports: from dataclasses import dataclass
  from typing import Dict
  import torch.nn
  import jiant.proj.main.runner
  import jiant.proj.main.components.task_sampler
  from jiant.shared.runner import save_model_with_metadata, compare_steps_max_steps
  from jiant.utils.python.datastructures import ExtendedDataClassMixin
  from jiant.utils.python.functional import always_false
  from jiant.utils.torch_utils import copy_state_dict, CPU_DEVICE, get_model_for_saving
  from jiant.utils.zlog import BaseZLogger, PRINT_LOGGER
  from jiant.shared.metarunner import AbstractMetarunner
label_desc: Use image node_id 9 for calling the JiantMetarunner obj's underlying member method code with example usage: obj.save_checkpoint() without return types