          'textcat': lambda nlp, **cfg: TextCategorizer(nlp.vocab, **cfg),
          'sbd': lambda nlp, **cfg: SentenceSegmenter(nlp.vocab, **cfg),
          'sentencizer': lambda nlp, **cfg: SentenceSegmenter(nlp.vocab, **cfg),
          'merge_noun_chunks': lambda nlp, **cfg: merge_noun_chunks,
          'merge_entities': lambda nlp, **cfg: merge_entities
      }
  
      def __init__(self, vocab=True, make_doc=True, meta={}, **kwargs):
          """Initialise a Language object.
  
 
</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             'transitions': lambda b: transitions.extend(ujson.loads(b)),
 </s> add             'moves': lambda b: labels.update(ujson.loads(b)), </s> remove         for trans in transitions:
            self.add_action(trans['move'], trans['label'])
 </s> add         self.initialize_actions(labels) </s> remove         transitions = []
 </s> add         labels = {} </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)
        'merge_entities': lambda nlp, **cfg: merge_entities,
        'merge_subtokens': lambda nlp, **cfg: merge_subtokens,
          'textcat': lambda nlp, **cfg: TextCategorizer(nlp.vocab, **cfg),
          'sbd': lambda nlp, **cfg: SentenceSegmenter(nlp.vocab, **cfg),
          'sentencizer': lambda nlp, **cfg: SentenceSegmenter(nlp.vocab, **cfg),
          'merge_noun_chunks': lambda nlp, **cfg: merge_noun_chunks,
        'merge_entities': lambda nlp, **cfg: merge_entities,
        'merge_subtokens': lambda nlp, **cfg: merge_subtokens,
      }
  
      def __init__(self, vocab=True, make_doc=True, meta={}, **kwargs):
          """Initialise a Language object.
  
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/language.py