def get_tokenizer()

in torchtext/data/utils.py [0:0]


def get_tokenizer(tokenizer, language='en'):
    r"""
    Generate tokenizer function for a string sentence.

    Args:
        tokenizer: the name of tokenizer function. If None, it returns split()
            function, which splits the string sentence by space.
            If basic_english, it returns _basic_english_normalize() function,
            which normalize the string first and split by space. If a callable
            function, it will return the function. If a tokenizer library
            (e.g. spacy, moses, toktok, revtok, subword), it returns the
            corresponding library.
        language: Default en

    Examples:
        >>> import torchtext
        >>> from torchtext.data import get_tokenizer
        >>> tokenizer = get_tokenizer("basic_english")
        >>> tokens = tokenizer("You can now install TorchText using pip!")
        >>> tokens
        >>> ['you', 'can', 'now', 'install', 'torchtext', 'using', 'pip', '!']

    """

    # default tokenizer is string.split(), added as a module function for serialization
    if tokenizer is None:
        return _split_tokenizer

    if tokenizer == "basic_english":
        if language != 'en':
            raise ValueError("Basic normalization is only available for Enlish(en)")
        return _basic_english_normalize

    # simply return if a function is passed
    if callable(tokenizer):
        return tokenizer

    if tokenizer == "spacy":
        try:
            import spacy
            try:
                spacy = spacy.load(language)
            except IOError:
                # Model shortcuts no longer work in spaCy 3.0+, try using fullnames
                # List is from https://github.com/explosion/spaCy/blob/b903de3fcb56df2f7247e5b6cfa6b66f4ff02b62/spacy/errors.py#L789
                OLD_MODEL_SHORTCUTS = spacy.errors.OLD_MODEL_SHORTCUTS if hasattr(spacy.errors, 'OLD_MODEL_SHORTCUTS') else {}
                if language not in OLD_MODEL_SHORTCUTS:
                    raise
                import warnings
                warnings.warn(f'Spacy model "{language}" could not be loaded, trying "{OLD_MODEL_SHORTCUTS[language]}" instead')
                spacy = spacy.load(OLD_MODEL_SHORTCUTS[language])
            return partial(_spacy_tokenize, spacy=spacy)
        except ImportError:
            print("Please install SpaCy. "
                  "See the docs at https://spacy.io for more information.")
            raise
        except AttributeError:
            print("Please install SpaCy and the SpaCy {} tokenizer. "
                  "See the docs at https://spacy.io for more "
                  "information.".format(language))
            raise
    elif tokenizer == "moses":
        try:
            from sacremoses import MosesTokenizer
            moses_tokenizer = MosesTokenizer()
            return moses_tokenizer.tokenize
        except ImportError:
            print("Please install SacreMoses. "
                  "See the docs at https://github.com/alvations/sacremoses "
                  "for more information.")
            raise
    elif tokenizer == "toktok":
        try:
            from nltk.tokenize.toktok import ToktokTokenizer
            toktok = ToktokTokenizer()
            return toktok.tokenize
        except ImportError:
            print("Please install NLTK. "
                  "See the docs at https://nltk.org  for more information.")
            raise
    elif tokenizer == 'revtok':
        try:
            import revtok
            return revtok.tokenize
        except ImportError:
            print("Please install revtok.")
            raise
    elif tokenizer == 'subword':
        try:
            import revtok
            return partial(revtok.tokenize, decap=True)
        except ImportError:
            print("Please install revtok.")
            raise
    raise ValueError("Requested tokenizer {}, valid choices are a "
                     "callable that takes a single string as input, "
                     "\"revtok\" for the revtok reversible tokenizer, "
                     "\"subword\" for the revtok caps-aware tokenizer, "
                     "\"spacy\" for the SpaCy English tokenizer, or "
                     "\"moses\" for the NLTK port of the Moses tokenization "
                     "script.".format(tokenizer))