compute-bleu.py

#!/usr/bin/env python
# -*- coding: utf-8 -*-

"""
    corpus analyzed: files must be untokenized/unsubworded
    example command: $ python compute-bleu.py test_file_name.txt mt_file_name.txt
"""


import sys
import sacrebleu

target_test = sys.argv[1]  # Test file argument
target_pred = sys.argv[2]  # MTed file argument

# Open the test dataset human translation file and detokenize the references
refs = []
with open(target_test) as test:
    for line in test: 
        line = line.strip()
        refs.append(line)

print("Reference 1st sentence:", refs[0])

refs = [refs]  # Yes, it is a list of list(s) as required by sacreBLEU

# Open the translation file by the NMT model and detokenize the predictions
preds = []
with open(target_pred) as pred:  
    for line in pred: 
        line = line.strip()
        preds.append(line)

print("MTed 1st sentence:", preds[0])

# Calculate and print the BLEU score
bleu = sacrebleu.corpus_bleu(preds, refs)
print("BLEU: ", bleu.score)