code: def get_runner_state(self):
      # TODO: Add fp16  (issue #1186)
      state = {
          "model": torch_utils.get_model_for_saving(
              self.jiant_model
          ).state_dict(),
          "optimizer": self.optimizer_scheduler.optimizer.state_dict(),
      }
      return state
  
imports: from typing import Dict
  from dataclasses import dataclass
  import torch
  import jiant.tasks.evaluate
  import jiant.utils.torch_utils
  from jiant.proj.main.components.container_setup import JiantTaskContainer
  from jiant.proj.main.modeling.primary import JiantModel, wrap_jiant_forward
  from jiant.shared.constants import PHASE
  from jiant.shared.runner import complex_backpropagate, get_train_dataloader_from_cache, get_eval_dataloader_from_cache
  from jiant.utils.display import maybe_tqdm
  from jiant.utils.python.datastructures import InfiniteYield, ExtendedDataClassMixin
label_desc: Use image node_id 14 for calling the JiantRunner obj's underlying member method code with example usage: obj.get_runner_state() and returns: state