def __init__(self,
                 lang='en',
                 lower=True,
                 lemmatize=False,
                 remove_punct=True,
                 remove_digits=True,
                 remove_stop_words=False,
                 exclude_oov=False,
                 exclude_pos_tags=None,
                 exclude_entities=['PERSON']):
        """Encodes text into `(samples, sentences, words)`

        Args:
            lang: The spacy language to use. (Default value: 'en')
            lower: Lower cases the tokens if True. (Default value: True)
            lemmatize: Lemmatizes words when set to True. This also makes the word lower case
                irrespective if the `lower` setting. (Default value: False)
            remove_punct: Removes punct words if True. (Default value: True)
            remove_digits: Removes digit words if True. (Default value: True)
            remove_stop_words: Removes stop words if True. (Default value: False)
            exclude_oov: Exclude words that are out of spacy embedding's vocabulary.
                By default, GloVe 1 million, 300 dim are used. You can override spacy vocabulary with a custom
                embedding to change this. (Default value: False)
            exclude_pos_tags: A list of parts of speech tags to exclude. Can be any of spacy.parts_of_speech.IDS
                (Default value: None)
            exclude_entities: A list of entity types to be excluded.
                Supported entity types can be found here: https://spacy.io/docs/usage/entity-recognition#entity-types
                (Default value: ['PERSON'])
        """
        super(SpacySentenceTokenizer, self).__init__(lang,
                                                     lower,
                                                     lemmatize,
                                                     remove_punct,
                                                     remove_digits,
                                                     remove_stop_words,
                                                     exclude_oov,
                                                     exclude_pos_tags,
                                                     exclude_entities)
def __init__ ( self , lang = 'en' , lower = True , lemmatize = False , remove_punct = True , remove_digits = True , remove_stop_words = False , exclude_oov = False , exclude_pos_tags = None , exclude_entities = [ 'PERSON' ] ) : super ( SpacySentenceTokenizer , self ) . __init__ ( lang , lower , lemmatize , remove_punct , remove_digits , remove_stop_words , exclude_oov , exclude_pos_tags , exclude_entities )
Encodes text into `(samples, sentences, words)`

        Args:
            lang: The spacy language to use. (Default value: 'en')
            lower: Lower cases the tokens if True. (Default value: True)
            lemmatize: Lemmatizes words when set to True. This also makes the word lower case
                irrespective if the `lower` setting. (Default value: False)
            remove_punct: Removes punct words if True. (Default value: True)
            remove_digits: Removes digit words if True. (Default value: True)
            remove_stop_words: Removes stop words if True. (Default value: False)
            exclude_oov: Exclude words that are out of spacy embedding's vocabulary.
                By default, GloVe 1 million, 300 dim are used. You can override spacy vocabulary with a custom
                embedding to change this. (Default value: False)
            exclude_pos_tags: A list of parts of speech tags to exclude. Can be any of spacy.parts_of_speech.IDS
                (Default value: None)
            exclude_entities: A list of entity types to be excluded.
                Supported entity types can be found here: https://spacy.io/docs/usage/entity-recognition#entity-types
                (Default value: ['PERSON'])