ec01f586b20cc3e9e15146e71d9248301ba277ae,tgen/rank.py,PerceptronRanker,_get_rival_candidates,#PerceptronRanker#,250

Before Change

        // candidates generated using the random planner (use the current DA)
        if "random" in self.rival_gen_strategy:
            random_doc = self.random_candgen.generate_tree(da)
            for _ in xrange(self.rival_number - 1):
                self.random_candgen.generate_tree(da, random_doc)
            rival_ttrees.extend(ttrees_from_doc(random_doc, self.language, self.selector))
            rival_feats.extend([self.vectorizer.transform(self.feats.get_features(ttree, {"da": da}))
                                for ttree in rival_ttrees])

After Change

            random_doc = None
            while random_doc is None or (len(random_doc.bundles) < self.rival_number):
                random_doc = self.random_candgen.generate_tree(da, random_doc)
                if (random_doc.bundles[-1].get_zone(self.language, self.selector).ttree
                    == train_ttrees[gold_ttree_no]):  // don"t generate trees identical to the gold one
                    del random_doc.bundles[-1]
            random_ttrees = ttrees_from_doc(random_doc, self.language, self.selector)
            rival_ttrees.extend(random_ttrees)
            rival_feats.extend([self.vectorizer.transform(self.feats.get_features(ttree, {"da": da}))
                                for ttree in random_ttrees])

Instances