code: def _check_job_results(
      job_results: List[List[Dict[str, Any]]]
  ) -> None:
      """
      See if we have a complete results dictionary for every job.
  
      Parameters
      ----------
      job_results : List[List[Dict[str, Any]]]
          A list of job result dictionaries.
      """
      logger = get_skll_logger("experiment")
      logger.info("Checking job results")
      for result_dicts in job_results:
          if not result_dicts or "task" not in result_dicts[0]:
              logger.error(
                  "There was an error running the experiment:\n"
                  f"{result_dicts}"
              )
  
imports: import json
  import math
  import re
  from collections import defaultdict
  from typing import Any, Dict, List, Union
  import numpy
  from sklearn.base import BaseEstimator
  from sklearn.pipeline import Pipeline
  from tabulate import tabulate
  from skll.types import EvaluateTaskResults, LabelType
  from skll.utils.logging import get_skll_logger
label_desc: Use image node_id 1 for calling a global function with example usage: _check_job_results(job_results) without return types