def __init__(self, snlp, meta=None, **kwargs):
    'Initialize the Language class.\n\n        Instead of "en" etc. we call the language "stanfordnlp_en" to not\n        cause conflicts with spaCy\'s built-in languages. Using entry points,\n        this also allows serializing and deserializing the language class\n        and "lang": "stanfordnlp_en" in the meta.json will automatically\n        instantiate this class if this package is available.\n\n        snlp (stanfordnlp.Pipeline): The loaded StanfordNLP pipeline.\n        kwargs: Optional config parameters.\n        RETURNS (spacy.language.Language): The nlp object.\n        '
    lang = snlp.config['lang']
    self.lang = ('stanfordnlp_' + lang)
    self.Defaults = get_defaults(lang)
    self.vocab = self.Defaults.create_vocab()
    self.tokenizer = Tokenizer(snlp, self.vocab)
    self.pipeline = []
    self.max_length = kwargs.get('max_length', (10 ** 6))
    self._meta = ({'lang': self.lang, 'stanfordnlp': snlp.config} if (meta is None) else dict(meta))
    self._path = None
    self._optimizer = None
Initialize the Language class.

Instead of "en" etc. we call the language "stanfordnlp_en" to not
cause conflicts with spaCy's built-in languages. Using entry points,
this also allows serializing and deserializing the language class
and "lang": "stanfordnlp_en" in the meta.json will automatically
instantiate this class if this package is available.

snlp (stanfordnlp.Pipeline): The loaded StanfordNLP pipeline.
kwargs: Optional config parameters.
RETURNS (spacy.language.Language): The nlp object.
def __init__(self, snlp, meta=None, **kwargs):
    'Initialize the Language class.\n\n        Instead of "en" etc. we call the language "stanfordnlp_en" to not\n        cause conflicts with spaCy\'s built-in languages. Using entry points,\n        this also allows serializing and deserializing the language class\n        and "lang": "stanfordnlp_en" in the meta.json will automatically\n        instantiate this class if this package is available.\n\n        snlp (stanfordnlp.Pipeline): The loaded StanfordNLP pipeline.\n        kwargs: Optional config parameters.\n        RETURNS (spacy.language.Language): The nlp object.\n        '
    lang = snlp.config['lang']
    self.lang = ('stanfordnlp_' + lang)
    self.Defaults = get_defaults(lang)
    self.vocab = self.Defaults.create_vocab()
    self.tokenizer = Tokenizer(snlp, self.vocab)
    self.pipeline = []
    self.max_length = kwargs.get('max_length', (10 ** 6))
    self._meta = ({'lang': self.lang, 'stanfordnlp': snlp.config} if (meta is None) else dict(meta))
    self._path = None
    self._optimizer = None