          yield from gold_docs
  
      @classmethod
      def iter_gold_docs(cls, nlp, tuples, gold_preproc=True):
          tuples = nonproj.PseudoProjectivity.preprocess_training_data(tuples)
          for raw_text, paragraph_tuples in tuples:
              docs = cls._make_docs(nlp, raw_text, paragraph_tuples,
                                    gold_preproc)
              golds = cls._make_golds(docs, paragraph_tuples)
              for doc, gold in zip(docs, golds):
 
</s> remove             gold.heads, gold.labels = PseudoProjectivity.projectivize(
                                        gold.heads, gold.labels)
 </s> add  </s> remove def read_json_file(loc, docs_filter=None, limit=None):
 </s> add def read_json_file(loc, docs_filter=None, limit=1000): </s> remove     def train_docs(self, nlp, shuffle=0, gold_preproc=True):
 </s> add     def train_docs(self, nlp, shuffle=0, gold_preproc=True,
                   projectivize=False): </s> remove         while todo:
 </s> add         while len(todo) >= 3: </s> remove         gold_docs = self.iter_gold_docs(nlp, self.train_tuples, gold_preproc)
 </s> add         if projectivize:
            train_tuples = nonproj.PseudoProjectivity.preprocess_training_data(
                               self.train_tuples)
        gold_docs = self.iter_gold_docs(nlp, train_tuples, gold_preproc)
          yield from gold_docs
  
      @classmethod
      def iter_gold_docs(cls, nlp, tuples, gold_preproc=True):

          for raw_text, paragraph_tuples in tuples:
              docs = cls._make_docs(nlp, raw_text, paragraph_tuples,
                                    gold_preproc)
              golds = cls._make_golds(docs, paragraph_tuples)
              for doc, gold in zip(docs, golds):
keep keep keep keep replace keep keep keep keep keep
 Fix handling of non-projective deps 
spacy/gold.pyx