示例#1
0
 def _greedy_decode(self):
     """Performs greedy decoding from the start node. Used to obtain
     the initial hypothesis.
     """
     hypo = PartialHypothesis()
     hypos = []
     posteriors = []
     score_breakdowns = []
     scores = []
     bag = dict(self.full_bag)
     while bag:
         posterior,score_breakdown = self.apply_predictors()
         hypo.predictor_states = copy.deepcopy(self.get_predictor_states())
         hypos.append(hypo)
         posteriors.append(posterior)
         score_breakdowns.append(score_breakdown)
         best_word = utils.argmax({w: posterior[w] for w in bag})
         bag[best_word] -= 1
         if bag[best_word] < 1:
             del bag[best_word]
         self.consume(best_word)
         hypo = hypo.expand(best_word,
                            None,
                            posterior[best_word],
                            score_breakdown[best_word])
         scores.append(posterior[best_word])
     posterior,score_breakdown = self.apply_predictors()
     hypo.predictor_states = self.get_predictor_states()
     hypos.append(hypo)
     posteriors.append(posterior)
     score_breakdowns.append(score_breakdown)
     hypo = hypo.expand(utils.EOS_ID,
                        None,
                        posterior[utils.EOS_ID],
                        score_breakdown[utils.EOS_ID])
     logging.debug("Greedy hypo (%f): %s" % (
                       hypo.score,
                       ' '.join([str(w) for w in hypo.trgt_sentence])))
     scores.append(posterior[utils.EOS_ID])
     self.best_score = hypo.score
     self.add_full_hypo(hypo.generate_full_hypothesis())
     self._process_new_hypos(FlipCandidate(hypo.trgt_sentence,
                                            scores,
                                            self._create_dummy_bigrams(),
                                            hypo.score),
                              len(hypo.trgt_sentence),
                              hypos,
                              posteriors,
                              score_breakdowns)
示例#2
0
 def _greedy_decode(self):
     """Performs greedy decoding from the start node. Used to obtain
     initial bigram statistics.
     """
     hypo = PartialHypothesis()
     hypos = []
     posteriors = []
     score_breakdowns = []
     bag = dict(self.full_bag)
     while bag:
         posterior,score_breakdown = self.apply_predictors()
         hypo.predictor_states = copy.deepcopy(self.get_predictor_states())
         bag_posterior = {w: posterior[w] for w in self.full_bag_with_eos}
         bag_breakdown = {w: score_breakdown[w] 
                                     for w in self.full_bag_with_eos}
         posteriors.append(bag_posterior)
         score_breakdowns.append(bag_breakdown)
         hypos.append(hypo)
         best_word = utils.argmax({w: bag_posterior[w] for w in bag})
         bag[best_word] -= 1
         if bag[best_word] < 1:
             del bag[best_word]
         self.consume(best_word)
         hypo = hypo.expand(best_word,
                            None,
                            bag_posterior[best_word],
                            score_breakdown[best_word])
     posterior,score_breakdown = self.apply_predictors()
     hypo.predictor_states = copy.deepcopy(self.get_predictor_states())
     bag_posterior = {w: posterior[w] for w in self.full_bag_with_eos}
     bag_breakdown = {w: score_breakdown[w] for w in self.full_bag_with_eos}
     posteriors.append(bag_posterior)
     score_breakdowns.append(bag_breakdown)
     hypos.append(hypo)
     
     hypo = hypo.cheap_expand(utils.EOS_ID,
                              bag_posterior[utils.EOS_ID],
                              score_breakdown[utils.EOS_ID])
     logging.debug("Greedy hypo (%f): %s" % (
                       hypo.score,
                       ' '.join([str(w) for w in hypo.trgt_sentence])))
     self._process_new_hypos(hypos, posteriors, score_breakdowns, hypo)
示例#3
0
 def _greedy_decode(self):
     """Performs greedy decoding from the start node. Used to obtain
     initial bigram statistics.
     """
     hypo = PartialHypothesis()
     hypos = []
     posteriors = []
     score_breakdowns = []
     bag = dict(self.full_bag)
     while bag:
         posterior,score_breakdown = self.apply_predictors()
         hypo.predictor_states = copy.deepcopy(self.get_predictor_states())
         bag_posterior = {w: posterior[w] for w in self.full_bag_with_eos}
         bag_breakdown = {w: score_breakdown[w] 
                                     for w in self.full_bag_with_eos}
         posteriors.append(bag_posterior)
         score_breakdowns.append(bag_breakdown)
         hypos.append(hypo)
         best_word = utils.argmax({w: bag_posterior[w] for w in bag})
         bag[best_word] -= 1
         if bag[best_word] < 1:
             del bag[best_word]
         self.consume(best_word)
         hypo = hypo.expand(best_word,
                            None,
                            bag_posterior[best_word],
                            score_breakdown[best_word])
     posterior,score_breakdown = self.apply_predictors()
     hypo.predictor_states = copy.deepcopy(self.get_predictor_states())
     bag_posterior = {w: posterior[w] for w in self.full_bag_with_eos}
     bag_breakdown = {w: score_breakdown[w] for w in self.full_bag_with_eos}
     posteriors.append(bag_posterior)
     score_breakdowns.append(bag_breakdown)
     hypos.append(hypo)
     
     hypo = hypo.cheap_expand(utils.EOS_ID,
                              bag_posterior[utils.EOS_ID],
                              score_breakdown[utils.EOS_ID])
     logging.debug("Greedy hypo (%f): %s" % (
                       hypo.score,
                       ' '.join([str(w) for w in hypo.trgt_sentence])))
     self._process_new_hypos(hypos, posteriors, score_breakdowns, hypo)