          yield from gold_docs
  
      @classmethod
      def iter_gold_docs(cls, nlp, tuples, gold_preproc, max_length=None,
                         noise_level=0.0):
          for raw_text, paragraph_tuples in tuples:
              if gold_preproc:
                  raw_text = None
              else:
                  paragraph_tuples = merge_sents(paragraph_tuples)
 
</s> remove         gold_docs = self.iter_gold_docs(nlp, self.dev_tuples, gold_preproc)
 </s> add         gold_docs = self.iter_gold_docs(nlp, self.dev_tuples,
                                        gold_preproc=gold_preproc) </s> remove             golds = cls._make_golds(docs, paragraph_tuples)
 </s> add             golds = cls._make_golds(docs, paragraph_tuples, make_projective) </s> remove     def train_docs(self, nlp, gold_preproc=False,
                   projectivize=False, max_length=None,
                   noise_level=0.0):
        train_tuples = self.train_tuples
        if projectivize:
            train_tuples = nonproj.preprocess_training_data(
                self.train_tuples, label_freq_cutoff=100)
        random.shuffle(train_tuples)
 </s> add     def train_docs(self, nlp, gold_preproc=False, max_length=None,
                    noise_level=0.0):
        locs = list((self.tmp_dir / 'train').iterdir())
        random.shuffle(locs)
        train_tuples = self.read_tuples(locs, limit=self.limit) </s> remove                                         noise_level=noise_level)
 </s> add                                         noise_level=noise_level,
                                        make_projective=True) </s> remove         i = 0
        for loc in self.dev_locs:
            gold_tuples = read_json_file(loc)
            for item in gold_tuples:
                yield item
                i += len(item[1])
                if self.limit and i >= self.limit:
                    break
 </s> add         locs = (self.tmp_dir / 'dev').iterdir()
        yield from self.read_tuples(locs, limit=self.limit)
   
    @property
    def train_tuples(self):
        locs = (self.tmp_dir / 'train').iterdir()
        yield from self.read_tuples(locs, limit=self.limit)
                       noise_level=0.0, make_projective=False):
          yield from gold_docs
  
      @classmethod
      def iter_gold_docs(cls, nlp, tuples, gold_preproc, max_length=None,
                       noise_level=0.0, make_projective=False):
          for raw_text, paragraph_tuples in tuples:
              if gold_preproc:
                  raw_text = None
              else:
                  paragraph_tuples = merge_sents(paragraph_tuples)
keep keep keep keep replace keep keep keep keep keep
 Revert "Merge branch 'develop' of https://github.com/explosion/spaCy into develop"

This reverts commit c9ba3d3c2dc7067cf8bd55f878cec45a8c6d73d4, reversing
changes made to 92c26a35d425d4e8ca1b805ea776ea10f5ded3df. 
spacy/gold.pyx