  
      def train(self, Doc tokens, object gold_tag_strs):
          cdef int i
          cdef int loss
          cdef const weight_t* scores
          golds = [self.tag_names.index(g) if g is not None else -1 for g in gold_tag_strs]
          correct = 0
 
</s> remove         golds = [self.tag_names.index(g) if g is not None else -1
                 for g in gold_tag_strs]
 </s> add         golds = [self.tag_names.index(g) if g is not None else -1 for g in gold_tag_strs] </s> remove             self.vocab.morphology.assign_tag(&tokens.data[i], tag_strs[i])
 </s> add             self.vocab.morphology.assign_tag(self.vocab.strings, &tokens.data[i], tag_strs[i]) </s> remove                 self.vocab.morphology.assign_tag(&tokens.data[i], guess)
 </s> add                 self.vocab.morphology.assign_tag(self.vocab.strings, &tokens.data[i], guess) </s> remove 
            self.vocab.morphology.assign_tag(&tokens.data[i], guess)
 </s> add             self.vocab.morphology.assign_tag(self.vocab.strings, &tokens.data[i], guess) </s> remove     cdef readonly int n_tags

 </s> add 
        assert len(tokens) == len(gold_tag_strs)
  
      def train(self, Doc tokens, object gold_tag_strs):
        assert len(tokens) == len(gold_tag_strs)
          cdef int i
          cdef int loss
          cdef const weight_t* scores
          golds = [self.tag_names.index(g) if g is not None else -1 for g in gold_tag_strs]
          correct = 0
keep add keep keep keep keep keep
 * Tagger training now working. Still need to test load/save of model. Morphology still broken. 
spacy/tagger.pyx