code: def get_bleu(in_sent, target_sent):
      bleu = sacrebleu.corpus_bleu([in_sent], [[target_sent]])
      out = " ".join(
          map(
              str,
              [bleu.score, bleu.sys_len, bleu.ref_len]
              + bleu.counts
              + bleu.totals,
          )
      )
      return out
  
file_path: fairseq/examples/discriminative_reranking_nmt/scripts/prep_data.py
imports: import argparse
  from multiprocessing import Pool
  from pathlib import Path
  import sacrebleu
  import sentencepiece
label_desc: Use image node_id 2 for calling a global function with example usage: get_bleu(in_sent, target_sent) and returns: out