code: def _print_mean_std_score(
      metrics: List[Tuple[str, Callable]],
      scores: Dict[str, List[float]],
  ):
      scores_mean_std = []  # type: List[str]
      for name, _ in metrics:
          if len(scores[name]) > 1:
              score_mean = np.mean(scores[name]).item()
              score_std = np.std(scores[name], ddof=1).item()
              scores_mean_std.append(
                  "%.3f\t%.3f" % (score_mean, score_std)
              )
          else:
              score = scores[name][0]
              scores_mean_std.append("%.3f\t(-)" % score)
      print("\t".join(scores_mean_std))
  
imports: import argparse
  import logging
  import sys
  from collections import defaultdict
  from functools import partial
  from typing import Callable, Iterable, Dict, List, Tuple, Optional
  import numpy
  import sacrebleu
  from sockeye_contrib import rouge
  from .None import arguments
  from .None import constants
  from .None import data_io
  from .None import utils
  from .log import setup_main_logger, log_sockeye_version
label_desc: Use image node_id 9 for calling a global function with example usage: _print_mean_std_score(metrics, scores) without return types