import nltk
from nltk.translate.bleu_score import SmoothingFunction
smoothing = SmoothingFunction()

hypothesis = open('in').read().strip()
reference =  open('ref').read().strip()
score = nltk.translate.bleu_score.sentence_bleu([reference.split()], hypothesis.split(), smoothing_function=smoothing.method2)
print("%f"%(score*100))