  
  
  @pytest.fixture
  def parser(vocab):
      parser = DependencyParser(vocab)
      return parser
  
  
  def test_init_parser(parser):
      pass
 
</s> remove     parser = DependencyParser(en_vocab)
 </s> add     parser = DependencyParser(en_vocab, default_parser()) </s> remove     parser.model, cfg = parser.Model(parser.moves.n_moves)
    parser.cfg.update(cfg)
 </s> add  </s> remove     parser = DependencyParser(en_vocab)
 </s> add     parser = DependencyParser(en_vocab, default_parser()) </s> remove     tagger1 = Tagger(en_vocab)
    tagger2 = Tagger(en_vocab)
    tagger1.model = tagger1.Model(8)
    tagger2.model = tagger1.model
    return (tagger1, tagger2)
 </s> add     model = default_tagger()
    tagger1 = Tagger(en_vocab, model)
    tagger2 = Tagger(en_vocab, model)
    return tagger1, tagger2 </s> remove     parser = DependencyParser(Vocab())
 </s> add     parser = DependencyParser(Vocab(), default_parser())
    parser = DependencyParser(vocab, default_parser())
  
  
  @pytest.fixture
  def parser(vocab):
    parser = DependencyParser(vocab, default_parser())
      return parser
  
  
  def test_init_parser(parser):
      pass
keep keep keep keep 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/tests/parser/test_add_label.py