          self.model.set_dim("nO", n_actions)
          self.model.initialize()
          if pipeline is not None:
              self.init_multitask_objectives(get_examples, pipeline, sgd=sgd, **self.cfg)
          util.link_vectors_to_models(self.vocab)
          self.loss_func = SequenceCategoricalCrossentropy(
              names=self.get_tag_names(), normalize=True, missing_value=None
          )
          return sgd
  
 
</s> remove         link_vectors_to_models(self.vocab)
 </s> add  </s> remove         util.link_vectors_to_models(self.vocab)
 </s> add  </s> remove         util.link_vectors_to_models(self.vocab)
 </s> add  </s> remove         if self.vectors.name is not None:
            link_vectors_to_models(self)
 </s> add  </s> remove             if self.vectors.name is not None:
                link_vectors_to_models(self)
 </s> add 
          self.model.set_dim("nO", n_actions)
          self.model.initialize()
          if pipeline is not None:
              self.init_multitask_objectives(get_examples, pipeline, sgd=sgd, **self.cfg)

          self.loss_func = SequenceCategoricalCrossentropy(
              names=self.get_tag_names(), normalize=True, missing_value=None
          )
          return sgd
  
keep keep keep keep replace keep keep keep keep keep
 Clean up link_vectors_to_models unused stuff 
spacy/pipeline/simple_ner.py