code: def create_tasks_from_benchmarks(benchmark_dict):
      """Creates a dictionary of tasks from a dict
      :param benchmark_dict: { dataset: [lang_pair, ...], }
      :return: {task_name: task}
          e.g. {wmt14-fr-en: Task, wmt16-de-en: Task}
      """
  
      def version_of(dataset, language_pair):
          if language_pair[-2:] in ["zh", "ja"]:
              return 1  # changed to use jieba/nagisa
          return 0
  
      return {
          f"{dataset}-{language_pair}": create_translation_task(
              dataset, language_pair, version_of(dataset, language_pair)
          )
          for dataset, language_pairs in benchmark_dict.items()
          for language_pair in language_pairs
      }
  
imports: import pycountry
  from pprint import pprint
  from sacrebleu import sacrebleu
  from lm_eval import metrics
  from lm_eval.base import Task, rf
  from typing import List
label_desc: Use image node_id 1 for calling a global function with example usage: create_tasks_from_benchmarks(benchmark_dict) and returns: unknown, int, int