          for tok_i, clas in enumerate(gold_classes):
              golds[tok_i] = self._moves[clas]
              assert golds[tok_i].clas == clas, '%d vs %d' % (golds[tok_i].clas, clas)
          cdef Move* guess
          while s.i < tokens.length:
              fill_context(self._context, s.i, tokens)
              self.extractor.extract(self._feats, self._values, self._context, NULL)
              self.model.score(self._scores, self._feats, self._values)
              
              set_accept_if_valid(self._moves, self.n_classes, s)
 
</s> remove         for i, clas in enumerate(gold_classes):
            golds[i] = self.moves[clas - 1]
            assert golds[i].id == clas
 </s> add         for tok_i, clas in enumerate(gold_classes):
            golds[tok_i] = self._moves[clas]
            assert golds[tok_i].clas == clas, '%d vs %d' % (golds[tok_i].clas, clas) </s> remove     cpdef int train(self, Tokens tokens, gold_classes):
 </s> add     cpdef int train(self, Tokens tokens, gold_classes) except -1: </s> remove     cdef weight_t score = scores[first_accept]
 </s> add     cdef weight_t score = scores[first_accept-1] </s> remove     cpdef int train(self, Tokens tokens, golds)
 </s> add     cpdef int train(self, Tokens tokens, golds) except -1
        n_correct = 0
        cdef int f = 0
          for tok_i, clas in enumerate(gold_classes):
              golds[tok_i] = self._moves[clas]
              assert golds[tok_i].clas == clas, '%d vs %d' % (golds[tok_i].clas, clas)
          cdef Move* guess
        n_correct = 0
        cdef int f = 0
          while s.i < tokens.length:
              fill_context(self._context, s.i, tokens)
              self.extractor.extract(self._feats, self._values, self._context, NULL)
              self.model.score(self._scores, self._feats, self._values)
              
              set_accept_if_valid(self._moves, self.n_classes, s)
keep keep keep add keep keep keep keep keep keep
 * Fixed greedy NER parsing. With static oracle, replicates accuracy from tagger. 
spacy/ner/greedy_parser.pyx