          else:
              activation = "relu"
          self.state2vec = precompute_hiddens(len(docs), self.tokvecs, layers[1],
                                              activation=activation, train=train)
          if len(layers) == 3:
              self.vec2scores = layers[-1]
          else:
              self.vec2scores = None
          self.cuda_stream = util.get_cuda_stream(non_blocking=True)
          self.backprops = []
 
</s> remove         elif len(layers) == 2:
 </s> add         elif has_upper: </s> remove         if self.vec2scores is None:
            self._class_mask = numpy.zeros((self.state2vec.nO,), dtype='f')
        else:
            self._class_mask = numpy.zeros((self.vec2scores.get_dim("nO"),), dtype='f')
 </s> add         self._class_mask = numpy.zeros((self.nO,), dtype='f') </s> remove     def __init__(self, docs, layers, unseen_classes=None, train=True):
 </s> add     def __init__(self, docs, layers, *, has_upper, unseen_classes=None, train=True):
        if has_upper:
          else:
              activation = "relu"
          self.state2vec = precompute_hiddens(len(docs), self.tokvecs, layers[1],
                                              activation=activation, train=train)
        if has_upper:
              self.vec2scores = layers[-1]
          else:
              self.vec2scores = None
          self.cuda_stream = util.get_cuda_stream(non_blocking=True)
          self.backprops = []
keep keep keep keep replace keep keep keep keep keep
 Adapt parser and NER for transformers (#5449)

* Draft layer for BILUO actions

* Fixes to biluo layer

* WIP on BILUO layer

* Add tests for BILUO layer

* Format

* Fix transitions

* Update test

* Link in the simple_ner

* Update BILUO tagger

* Update __init__

* Import simple_ner

* Update test

* Import

* Add files

* Add config

* Fix label passing for BILUO and tagger

* Fix label handling for simple_ner component

* Update simple NER test

* Update config

* Hack train script

* Update BILUO layer

* Fix SimpleNER component

* Update train_from_config

* Add biluo_to_iob helper

* Add IOB layer

* Add IOBTagger model

* Update biluo layer

* Update SimpleNER tagger

* Update BILUO

* Read random seed in train-from-config

* Update use of normal_init

* Fix normalization of gradient in SimpleNER

* Update IOBTagger

* Remove print

* Tweak masking in BILUO

* Add dropout in SimpleNER

* Update thinc

* Tidy up simple_ner

* Fix biluo model

* Unhack train-from-config

* Update setup.cfg and requirements

* Add tb_framework.py for parser model

* Try to avoid memory leak in BILUO

* Move ParserModel into spacy.ml, avoid need for subclass.

* Use updated parser model

* Remove incorrect call to model.initializre in PrecomputableAffine

* Update parser model

* Avoid divide by zero in tagger

* Add extra dropout layer in tagger

* Refine minibatch_by_words function to avoid oom

* Fix parser model after refactor

* Try to avoid div-by-zero in SimpleNER

* Fix infinite loop in minibatch_by_words

* Use SequenceCategoricalCrossentropy in Tagger

* Fix parser model when hidden layer

* Remove extra dropout from tagger

* Add extra nan check in tagger

* Fix thinc version

* Update tests and imports

* Fix test

* Update test

* Update tests

* Fix tests

* Fix test

Co-authored-by: Ines Montani <ines@ines.io> 
spacy/syntax/_parser_model.pyx