code: def load_state(self, runner_state):
      torch_utils.get_model_for_saving(
          self.jiant_model
      ).load_state_dict(runner_state["model"])
      self.optimizer_scheduler.optimizer.load_state_dict(
          runner_state["optimizer"]
      )
  
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 15 for calling the JiantRunner obj's underlying member method code with example usage: obj.load_state(runner_state) without return types