          self.parser = parser
          self.entity = entity
          self.matcher = matcher
  
      def __call__(self, text, tag=True, parse=True, entity=True, merge_mwes=False):
          """Apply the pipeline to some text.  The text can span multiple sentences,
          and can contain arbtrary whitespace.  Alignment into the original string
          is preserved.
          
          Args:
 
</s> remove     def __init__(self, get_lex_attr=None, tag_map=None, vectors=None, lemmatizer=None,
                 serializer_freqs=None):
 </s> add     def __init__(self, get_lex_attr=None, tag_map=None, lemmatizer=None, serializer_freqs=None): </s> remove         if vectors is None:
            vectors = cls.default_vectors(data_dir)
 </s> add  </s> remove             self.repvec_length = self.load_rep_vectors(path.join(data_dir, 'vec.bin'))
 </s> add             self.vectors_length = self.load_vectors(path.join(data_dir, 'vec.bin')) </s> remove     def default_vectors(cls, data_dir):
        return None

    @classmethod
    def default_vocab(cls, data_dir=None, get_lex_attr=None, vectors=None):
 </s> add     def default_vocab(cls, data_dir=None, get_lex_attr=None): </s> remove                 get_lex_attr=get_lex_attr,
                vectors=vectors)
 </s> add                 get_lex_attr=get_lex_attr)
    def __call__(self, text, tag=True, parse=True, entity=True):
          self.parser = parser
          self.entity = entity
          self.matcher = matcher
  
    def __call__(self, text, tag=True, parse=True, entity=True):
          """Apply the pipeline to some text.  The text can span multiple sentences,
          and can contain arbtrary whitespace.  Alignment into the original string
          is preserved.
          
          Args:
keep keep keep keep replace keep keep keep keep keep
 * Remove the vectors option to Vocab, preferring to either load vectors from disk, or set them on the Lexeme objects. 
spacy/language.py