d6c184579dee8328635016607049ab17f12c68e4,tgen/rank.py,PerceptronRanker,_get_rival_candidates,#PerceptronRanker#Any#Any#Any#,284

Before Change

            gen_doc = None
            while gen_doc is None or (len(gen_doc.bundles) < self.rival_number):
                gen_doc = self.sampling_planner.generate_tree(da, gen_doc)
                if (gen_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 gen_doc.bundles[-1]
            random_ttrees = ttrees_from_doc(gen_doc, self.language, self.selector)
            rival_ttrees.extend(random_ttrees)
            rival_feats.extend([self._extract_feats(ttree, da) for ttree in random_ttrees])

After Change

            random_trees = []
            while len(random_trees) < self.rival_number:
                tree = self.sampling_planner.generate_tree(da)
                if (tree != train_trees[gold_tree_idx]):  // don"t generate trees identical to the gold one
                    random_trees.append(tree)
            rival_trees.extend(random_trees)
            rival_feats.extend([self._extract_feats(ttree, da) for ttree in random_trees])

        // candidates generated using the A*search planner, which uses this ranker with current

Instances