code: def run_metrics_for_one_output(
      metric_config, y_true=None, y_pred=None
  ):
      metrics_list_config = metric_config["cals"]
      score = dict()
      for one_metric in metrics_list_config:
          metric_name = one_metric["name"]
          calculator = registers.metric[metric_name](metric_config)
          arguments = one_metric["arguments"]
          metric_score = calculator(
              y_true=y_true, y_pred=y_pred, arguments=arguments
          )
          score[metric_name] = metric_score
      return score
  
imports: import os
  import abc
  from absl import logging
  import numpy
  from sklearn import metrics
  from seqeval.metrics import classification_report
  from delta.utils.register import registers
  from delta.utils.postprocess.postprocess_utils import ids_to_sentences
  from rouge import FilesRouge
  from sacrebleu import corpus_bleu
  from delta.utils.metrics import metric_utils
label_desc: Use image node_id 1 for calling a global function with example usage: run_metrics_for_one_output(metric_config, y_true, y_pred) and returns: score