code: def get_val_labels_dict(self, task_name_list, use_subset=False):
      val_labels_dict = {}
      for task_name in task_name_list:
          task_specific_config = (
              self.jiant_task_container.task_specific_configs[task_name]
          )
          val_labels_cache = self.jiant_task_container.task_cache_dict[
              task_name
          ]["val_labels"]
          val_labels = val_labels_cache.get_all()
          if use_subset:
              val_labels = val_labels[
                  : task_specific_config.eval_subset_num
              ]
          val_labels_dict[task_name] = val_labels
      return val_labels_dict
  
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 11 for calling the JiantRunner obj's underlying member method code with example usage: obj.get_val_labels_dict(task_name_list, use_subset) and returns: val_labels_dict