code: def mean_multiclass_f1(num_classes, **metric_fn_kwargs):
      """Computes the unweighted average of the F1 per class."""
      return sklearn_metrics_wrapper(
          "fbeta_score",
          metric_dict_str="mean_%dclass_f1" % num_classes,
          metric_post_process_fn=lambda x: 100 * x,
          beta=1,
          labels=range(num_classes),
          average="macro",
          **metric_fn_kwargs,
      )
  
imports: import collections
  import itertools
  import re
  import string
  from typing import Any, Dict, Mapping, Optional, Sequence, Tuple, Union
  from absl import logging
  import editdistance
  import flax
  import jax.numpy
  import numpy
  import sacrebleu
  import scipy.stats
  import seqio
  import sklearn.metrics
  from t5.evaluation import qa_utils
  import tensorflow.compat.v2
  from rouge_score import rouge_scorer
  from rouge_score import scoring
label_desc: Use image node_id 12 for calling a global function with example usage: mean_multiclass_f1(num_classes) and returns: sklearn_metrics_wrapper