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			259 lines
		
	
	
		
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			259 lines
		
	
	
		
			6.8 KiB
		
	
	
	
		
			Plaintext
		
	
	
	
	
	
| //- 💫 DOCS > API > VOCAB
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| 
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| include ../../_includes/_mixins
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| 
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| p
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|     |  A lookup table that allows you to access #[code Lexeme] objects. The
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|     |  #[code Vocab] instance also provides access to the #[code StringStore],
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|     |  and owns underlying C-data that is shared between #[code Doc] objects.
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| 
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| +h(2, "init") Vocab.__init__
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|     +tag method
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| 
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| p Create the vocabulary.
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| 
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| +table(["Name", "Type", "Description"])
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|     +row
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|         +cell #[code lex_attr_getters]
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|         +cell dict
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|         +cell
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|             |  A dictionary mapping attribute IDs to functions to compute them.
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|             |  Defaults to #[code None].
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| 
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|     +row
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|         +cell #[code tag_map]
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|         +cell dict
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|         +cell
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|             |  A dictionary mapping fine-grained tags to coarse-grained
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|             |  parts-of-speech, and optionally morphological attributes.
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| 
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|     +row
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|         +cell #[code lemmatizer]
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|         +cell object
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|         +cell A lemmatizer. Defaults to #[code None].
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| 
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|     +row
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|         +cell #[code strings]
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|         +cell #[code StringStore] or list
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|         +cell
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|             |  A #[+api("stringstore") #[code StringStore]] that maps
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|             |  strings to hash values, and vice versa, or a list of strings.
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| 
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|     +footrow
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|         +cell returns
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|         +cell #[code Vocab]
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|         +cell The newly constructed object.
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| 
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| +h(2, "len") Vocab.__len__
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|     +tag method
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| 
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| p Get the current number of lexemes in the vocabulary.
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| 
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| +aside-code("Example").
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|     doc = nlp(u'This is a sentence.')
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|     assert len(nlp.vocab) > 0
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| 
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| +table(["Name", "Type", "Description"])
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|     +footrow
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|         +cell returns
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|         +cell int
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|         +cell The number of lexems in the vocabulary.
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| 
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| +h(2, "getitem") Vocab.__getitem__
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|     +tag method
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| 
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| p
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|     |  Retrieve a lexeme, given an int ID or a unicode string. If a previously
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|     |  unseen unicode string is given, a new lexeme is created and stored.
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| 
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| +aside-code("Example").
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|     apple = nlp.vocab.strings['apple']
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|     assert nlp.vocab[apple] == nlp.vocab[u'apple']
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| 
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| +table(["Name", "Type", "Description"])
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|     +row
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|         +cell #[code id_or_string]
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|         +cell int / unicode
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|         +cell The hash value of a word, or its unicode string.
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| 
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|     +footrow
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|         +cell returns
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|         +cell #[code Lexeme]
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|         +cell The lexeme indicated by the given ID.
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| 
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| +h(2, "iter") Vocab.__iter__
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|     +tag method
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| 
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| p Iterate over the lexemes in the vocabulary.
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| 
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| +aside-code("Example").
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|     stop_words = (lex for lex in nlp.vocab if lex.is_stop)
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| 
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| +table(["Name", "Type", "Description"])
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|     +footrow
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|         +cell yields
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|         +cell #[code Lexeme]
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|         +cell An entry in the vocabulary.
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| 
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| +h(2, "contains") Vocab.__contains__
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|     +tag method
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| 
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| p
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|     |  Check whether the string has an entry in the vocabulary. To get the ID
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|     |  for a given string, you need to look it up in
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|     |  #[+api("vocab#attributes") #[code vocab.strings]].
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| 
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| +aside-code("Example").
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|     apple = nlp.vocab.strings['apple']
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|     oov = nlp.vocab.strings['dskfodkfos']
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|     assert apple in nlp.vocab
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|     assert oov not in nlp.vocab
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| 
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| +table(["Name", "Type", "Description"])
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|     +row
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|         +cell #[code string]
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|         +cell unicode
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|         +cell The ID string.
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| 
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|     +footrow
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|         +cell returns
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|         +cell bool
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|         +cell Whether the string has an entry in the vocabulary.
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| 
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| +h(2, "add_flag") Vocab.add_flag
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|     +tag method
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| 
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| p
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|     |  Set a new boolean flag to words in the vocabulary. The #[code flag_getter]
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|     |  function will be called over the words currently in the vocab, and then
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|     |  applied to new words as they occur. You'll then be able to access the flag
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|     |  value on each token, using #[code token.check_flag(flag_id)].
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| 
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| +aside-code("Example").
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|     def is_my_product(text):
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|         products = [u'spaCy', u'Thinc', u'displaCy']
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|         return text in products
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| 
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|     MY_PRODUCT = nlp.vocab.add_flag(is_my_product)
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|     doc = nlp(u'I like spaCy')
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|     assert doc[2].check_flag(MY_PRODUCT) == True
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| 
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| +table(["Name", "Type", "Description"])
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|     +row
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|         +cell #[code flag_getter]
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|         +cell dict
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|         +cell A function #[code f(unicode) -> bool], to get the flag value.
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| 
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|     +row
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|         +cell #[code flag_id]
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|         +cell int
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|         +cell
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|             |  An integer between 1 and 63 (inclusive), specifying the bit at
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|             |  which the flag will be stored. If #[code -1], the lowest
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|             |  available bit will be chosen.
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| 
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|     +footrow
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|         +cell returns
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|         +cell int
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|         +cell The integer ID by which the flag value can be checked.
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| 
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| +h(2, "to_disk") Vocab.to_disk
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|     +tag method
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|     +tag-new(2)
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| 
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| p Save the current state to a directory.
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| 
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| +aside-code("Example").
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|     nlp.vocab.to_disk('/path/to/vocab')
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| 
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| +table(["Name", "Type", "Description"])
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|     +row
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|         +cell #[code path]
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|         +cell unicode or #[code Path]
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|         +cell
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|             |  A path to a directory, which will be created if it doesn't exist.
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|             |  Paths may be either strings or #[code Path]-like objects.
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| 
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| +h(2, "from_disk") Vocab.from_disk
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|     +tag method
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|     +tag-new(2)
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| 
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| p Loads state from a directory. Modifies the object in place and returns it.
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| 
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| +aside-code("Example").
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|     from spacy.vocab import Vocab
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|     vocab = Vocab().from_disk('/path/to/vocab')
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| 
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| +table(["Name", "Type", "Description"])
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|     +row
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|         +cell #[code path]
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|         +cell unicode or #[code Path]
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|         +cell
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|             |  A path to a directory. Paths may be either strings or
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|             |  #[code Path]-like objects.
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| 
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|     +footrow
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|         +cell returns
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|         +cell #[code Vocab]
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|         +cell The modified #[code Vocab] object.
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| 
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| +h(2, "to_bytes") Vocab.to_bytes
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|     +tag method
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| 
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| p Serialize the current state to a binary string.
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| 
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| +aside-code("Example").
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|     vocab_bytes = nlp.vocab.to_bytes()
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| 
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| +table(["Name", "Type", "Description"])
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|     +row
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|         +cell #[code **exclude]
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|         +cell -
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|         +cell Named attributes to prevent from being serialized.
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| 
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|     +footrow
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|         +cell returns
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|         +cell bytes
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|         +cell The serialized form of the #[code Vocab] object.
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| 
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| +h(2, "from_bytes") Vocab.from_bytes
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|     +tag method
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| 
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| p Load state from a binary string.
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| 
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| +aside-code("Example").
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|     fron spacy.vocab import Vocab
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|     vocab_bytes = nlp.vocab.to_bytes()
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|     vocab = Vocab()
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|     vocab.from_bytes(vocab_bytes)
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| 
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| +table(["Name", "Type", "Description"])
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|     +row
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|         +cell #[code bytes_data]
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|         +cell bytes
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|         +cell The data to load from.
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| 
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|     +row
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|         +cell #[code **exclude]
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|         +cell -
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|         +cell Named attributes to prevent from being loaded.
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| 
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|     +footrow
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|         +cell returns
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|         +cell #[code Vocab]
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|         +cell The #[code Vocab] object.
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| 
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| +h(2, "attributes") Attributes
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| 
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| +aside-code("Example").
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|     apple_id = nlp.vocab.strings['apple']
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|     assert type(apple_id) == int
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|     PERSON = nlp.vocab.strings['PERSON']
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|     assert type(PERSON) == int
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| 
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| +table(["Name", "Type", "Description"])
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|     +row
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|         +cell #[code strings]
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|         +cell #[code StringStore]
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|         +cell A table managing the string-to-int mapping.
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