code: def matthews_corrcoef(preds, labels):
      # make it consistent with other metrics taking (preds, labels) as input
      mcc = _matthews_corrcoef(labels, preds)
      return mcc
  
imports: import math
  from dataclasses import dataclass, field
  from itertools import chain
  import numpy
  import torch
  import torch.nn.functional
  from sklearn.metrics import f1_score
  from sklearn.metrics import matthews_corrcoef
  from scipy.stats import pearsonr, spearmanr
  from fairseq.logging import metrics
  from fairseq.criterions import FairseqCriterion, register_criterion
  from fairseq.dataclass import FairseqDataclass
  from fairseq.logging.meters import safe_round
label_desc: Use image node_id 4 for calling a global function with example usage: matthews_corrcoef(preds, labels) and returns: mcc