          """Create a Parser.
  
          vocab (Vocab): The vocabulary object. Must be shared with documents
              to be processed. The value is set to the `.vocab` attribute.
          moves (TransitionSystem): Defines how the parse-state is created,
              updated and evaluated. The value is set to the .moves attribute
              unless True (default), in which case a new instance is created with
              `Parser.Moves()`.
          model (object): Defines how the parse-state is created, updated and
              evaluated. The value is set to the .model attribute. If set to True
              (default), a new instance will be created with `Parser.Model()`
              in parser.begin_training(), parser.from_disk() or parser.from_bytes().
          **cfg: Arbitrary configuration parameters. Set to the `.cfg` attribute
          """
          self.vocab = vocab
          if moves is True:
              self.moves = self.TransitionSystem(self.vocab.strings)
          else:
 
</s> remove     def __init__(self, Vocab vocab, moves=True, model=True, **cfg):
 </s> add     def __init__(self, Vocab vocab, model, **cfg): </s> remove         if moves is True:
            self.moves = self.TransitionSystem(self.vocab.strings)
        else:
            self.moves = moves
        if 'beam_width' not in cfg:
            cfg['beam_width'] = util.env_opt('beam_width', 1)
        if 'beam_density' not in cfg:
            cfg['beam_density'] = util.env_opt('beam_density', 0.0)
        if 'beam_update_prob' not in cfg:
            cfg['beam_update_prob'] = util.env_opt('beam_update_prob', 1.0)
        cfg.setdefault('cnn_maxout_pieces', 3)
        cfg.setdefault("nr_feature_tokens", self.nr_feature)
        self.cfg = cfg
 </s> add         moves = cfg.get("moves", None)
        if moves is None:
            # defined by EntityRecognizer as a BiluoPushDown
            moves = self.TransitionSystem(self.vocab.strings)
        self.moves = moves
        cfg.setdefault('min_action_freq', 30)
        cfg.setdefault('learn_tokens', False)
        cfg.setdefault('beam_width', 1)
        cfg.setdefault('beam_update_prob', 1.0)  # or 0.5 (both defaults were previously used) </s> remove         model (Model): A `Model` instance or `True` to allocate one later.
 </s> add  </s> remove         model (Model): A `Model` instance or `True` to allocate one later.
 </s> add  </s> remove 
        EXAMPLE:
            >>> from spacy.pipeline import TokenVectorEncoder
            >>> tok2vec = TokenVectorEncoder(nlp.vocab)
            >>> tok2vec.model = tok2vec.Model(128, 5000)
 </s> add 
        **cfg: Configuration parameters. Set to the `.cfg` attribute.
             If it doesn't include a value for 'moves',  a new instance is
             created with `self.TransitionSystem()`. This defines how the
             parse-state is created, updated and evaluated.
          """Create a Parser.
  
          vocab (Vocab): The vocabulary object. Must be shared with documents
              to be processed. The value is set to the `.vocab` attribute.
        **cfg: Configuration parameters. Set to the `.cfg` attribute.
             If it doesn't include a value for 'moves',  a new instance is
             created with `self.TransitionSystem()`. This defines how the
             parse-state is created, updated and evaluated.
        **cfg: Configuration parameters. Set to the `.cfg` attribute.
             If it doesn't include a value for 'moves',  a new instance is
             created with `self.TransitionSystem()`. This defines how the
             parse-state is created, updated and evaluated.
        **cfg: Configuration parameters. Set to the `.cfg` attribute.
             If it doesn't include a value for 'moves',  a new instance is
             created with `self.TransitionSystem()`. This defines how the
             parse-state is created, updated and evaluated.
        **cfg: Configuration parameters. Set to the `.cfg` attribute.
             If it doesn't include a value for 'moves',  a new instance is
             created with `self.TransitionSystem()`. This defines how the
             parse-state is created, updated and evaluated.
        **cfg: Configuration parameters. Set to the `.cfg` attribute.
             If it doesn't include a value for 'moves',  a new instance is
             created with `self.TransitionSystem()`. This defines how the
             parse-state is created, updated and evaluated.
        **cfg: Configuration parameters. Set to the `.cfg` attribute.
             If it doesn't include a value for 'moves',  a new instance is
             created with `self.TransitionSystem()`. This defines how the
             parse-state is created, updated and evaluated.
        **cfg: Configuration parameters. Set to the `.cfg` attribute.
             If it doesn't include a value for 'moves',  a new instance is
             created with `self.TransitionSystem()`. This defines how the
             parse-state is created, updated and evaluated.
        **cfg: Configuration parameters. Set to the `.cfg` attribute.
             If it doesn't include a value for 'moves',  a new instance is
             created with `self.TransitionSystem()`. This defines how the
             parse-state is created, updated and evaluated.
        **cfg: Configuration parameters. Set to the `.cfg` attribute.
             If it doesn't include a value for 'moves',  a new instance is
             created with `self.TransitionSystem()`. This defines how the
             parse-state is created, updated and evaluated.
          """
          self.vocab = vocab
          if moves is True:
              self.moves = self.TransitionSystem(self.vocab.strings)
          else:
keep keep keep keep replace replace replace replace replace replace replace replace replace keep keep keep keep keep
 Default settings to configurations (#4995)

* fix grad_clip naming

* cleaning up pretrained_vectors out of cfg

* further refactoring Model init's

* move Model building out of pipes

* further refactor to require a model config when creating a pipe

* small fixes

* making cfg in nn_parser more consistent

* fixing nr_class for parser

* fixing nn_parser's nO

* fix printing of loss

* architectures in own file per type, consistent naming

* convenience methods default_tagger_config and default_tok2vec_config

* let create_pipe access default config if available for that component

* default_parser_config

* move defaults to separate folder

* allow reading nlp from package or dir with argument 'name'

* architecture spacy.VocabVectors.v1 to read static vectors from file

* cleanup

* default configs for nel, textcat, morphologizer, tensorizer

* fix imports

* fixing unit tests

* fixes and clean up

* fixing defaults, nO, fix unit tests

* restore parser IO

* fix IO

* 'fix' serialization test

* add *.cfg to manifest

* fix example configs with additional arguments

* replace Morpohologizer with Tagger

* add IO bit when testing overfitting of tagger (currently failing)

* fix IO - don't initialize when reading from disk

* expand overfitting tests to also check IO goes OK

* remove dropout from HashEmbed to fix Tagger performance

* add defaults for sentrec

* update thinc

* always pass a Model instance to a Pipe

* fix piped_added statement

* remove obsolete W029

* remove obsolete errors

* restore byte checking tests (work again)

* clean up test

* further test cleanup

* convert from config to Model in create_pipe

* bring back error when component is not initialized

* cleanup

* remove calls for nlp2.begin_training

* use thinc.api in imports

* allow setting charembed's nM and nC

* fix for hardcoded nM/nC + unit test

* formatting fixes

* trigger build 
spacy/syntax/nn_parser.pyx