def cur_cost(current_hyp, source, phrase_probs, lang_model: LanguageModel):
translated_phrases = [x for _,_,x in current_hyp]
translated_tokens = []
for phrase in translated_phrases:
translated_tokens.extend(phrase.split(" "))
lang_model_probs = lang_model.get_prob_sentance(translated_tokens,padded_left=True,padded_right=False)
translation_prob = 1
distortion_prob = 1
last_end_f = -1
for cur_phrase in current_hyp:
start_f,end_f,e = cur_phrase
foreign_phrase = " ".join(source[start_f:end_f+1])
translation_prob *= phrase_probs[foreign_phrase][e]
if last_end_f != -1:
distortion_prob *= d(start_f,last_end_f)
last_end_f = end_f
# print(translation_prob)
# print(distortion_prob)
# print(lang_model_probs)
return lang_model_probs*distortion_prob*translation_prob
