code: def run_evaluation(args):
      test, ref, evaluator, metric_kwargs = args
      evaluator.set_test(test)
      evaluator.set_reference(ref)
      if evaluator.labels is None:
          evaluator.construct_labels()
      current_scores = evaluator.evaluate(**metric_kwargs)
      if type(test) == str:
          current_scores["test"] = test
      if type(ref) == str:
          current_scores["reference"] = ref
      return current_scores
  
imports: import collections
  import inspect
  import json
  import hashlib
  from datetime import datetime
  from multiprocessing.pool import Pool
  import numpy
  import pandas
  import SimpleITK
  from collections import OrderedDict
  from .metrics import ConfusionMatrix, ALL_METRICS
label_desc: Use image node_id 1 for calling a global function with example usage: run_evaluation(args) and returns: current_scores