          if 'pretrained_dims' not in cfg:
              cfg['pretrained_dims'] = self.vocab.vectors.data.shape[1]
          cfg.setdefault('cnn_maxout_pieces', 3)
          self.cfg = cfg
          if 'actions' in self.cfg:
              for action, labels in self.cfg.get('actions', {}).items():
                  for label in labels:
                      self.moves.add_action(action, label)
          self.model = model
          self._multitasks = []
  
      def __reduce__(self):
          return (Parser, (self.vocab, self.moves, self.model), None, None)
 
</s> remove         cfg.setdefault('cnn_maxout_pieces', 3)
 </s> add  </s> remove                 # Important that the labels be stored as a list! We need the
                # order, or the model goes out of synch
                self.cfg.setdefault('extra_labels', []).append(label)
 </s> add  </s> remove         labels_by_action = OrderedDict()
        cdef Transition t
        for trans in self.c[:self.n_moves]:
            label_str = self.strings[trans.label]
            labels_by_action.setdefault(trans.move, []).append(label_str)
        return (self.__class__,
                (self.strings, labels_by_action),
                None, None)
 </s> add         return (self.__class__, (self.strings, self.labels), None, None) </s> remove             filtered_labels = [decompose(label)[0]
                               if freqs.get(label, cutoff) < cutoff
                               else label for label in labels]
 </s> add             filtered_labels = []
            for label in labels:
                if is_decorated(label) and freqs.get(label, 0) < cutoff:
                    filtered_labels.append(decompose(label)[0])
                else:
                    filtered_labels.append(label) </s> remove         for action, label_strs in labels_by_action.items():
            for label_str in label_strs:
                self.add_action(int(action), label_str)
 </s> add         self.labels = {}
        if labels_by_action:
            self.initialize_actions(labels_by_action, min_freq=min_freq)
          if 'pretrained_dims' not in cfg:
              cfg['pretrained_dims'] = self.vocab.vectors.data.shape[1]
          cfg.setdefault('cnn_maxout_pieces', 3)
          self.cfg = cfg




          self.model = model
          self._multitasks = []
  
      def __reduce__(self):
          return (Parser, (self.vocab, self.moves, self.model), None, None)
keep keep keep keep replace replace replace 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/syntax/nn_parser.pyx