code: def stderr_for_metric(metric, bootstrap_iters):
      bootstrappable = [
          median,
          matthews_corrcoef,
          f1_score,
          perplexity,
          bleu,
          chrf,
          ter,
      ]
  
      if metric in bootstrappable:
          return lambda x: bootstrap_stderr(
              metric, x, iters=bootstrap_iters
          )
  
      stderr = {mean: mean_stderr, acc_all: acc_all_stderr}
  
      return stderr.get(metric, None)
  
imports: import math
  from collections.abc import Iterable
  import numpy
  import sacrebleu
  import sklearn.metrics
  import random
  from collections import defaultdict
label_desc: Use image node_id 23 for calling a global function with example usage: stderr_for_metric(metric, bootstrap_iters) and returns: stderr, function