592 lines
16 KiB
Python
592 lines
16 KiB
Python
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# Generated content DO NOT EDIT
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class Model:
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"""
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Base class for all models
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The model represents the actual tokenization algorithm. This is the part that
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will contain and manage the learned vocabulary.
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This class cannot be constructed directly. Please use one of the concrete models.
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"""
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def get_trainer(self):
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"""
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Get the associated :class:`~tokenizers.trainers.Trainer`
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Retrieve the :class:`~tokenizers.trainers.Trainer` associated to this
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:class:`~tokenizers.models.Model`.
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Returns:
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:class:`~tokenizers.trainers.Trainer`: The Trainer used to train this model
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"""
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pass
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def id_to_token(self, id):
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"""
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Get the token associated to an ID
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Args:
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id (:obj:`int`):
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An ID to convert to a token
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Returns:
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:obj:`str`: The token associated to the ID
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"""
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pass
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def save(self, folder, prefix):
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"""
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Save the current model
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Save the current model in the given folder, using the given prefix for the various
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files that will get created.
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Any file with the same name that already exists in this folder will be overwritten.
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Args:
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folder (:obj:`str`):
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The path to the target folder in which to save the various files
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prefix (:obj:`str`, `optional`):
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An optional prefix, used to prefix each file name
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Returns:
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:obj:`List[str]`: The list of saved files
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"""
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pass
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def token_to_id(self, tokens):
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"""
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Get the ID associated to a token
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Args:
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token (:obj:`str`):
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A token to convert to an ID
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Returns:
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:obj:`int`: The ID associated to the token
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"""
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pass
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def tokenize(self, sequence):
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"""
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Tokenize a sequence
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Args:
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sequence (:obj:`str`):
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A sequence to tokenize
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Returns:
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A :obj:`List` of :class:`~tokenizers.Token`: The generated tokens
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"""
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pass
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class BPE(Model):
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"""
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An implementation of the BPE (Byte-Pair Encoding) algorithm
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Args:
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vocab (:obj:`Dict[str, int]`, `optional`):
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A dictionnary of string keys and their ids :obj:`{"am": 0,...}`
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merges (:obj:`List[Tuple[str, str]]`, `optional`):
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A list of pairs of tokens (:obj:`Tuple[str, str]`) :obj:`[("a", "b"),...]`
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cache_capacity (:obj:`int`, `optional`):
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The number of words that the BPE cache can contain. The cache allows
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to speed-up the process by keeping the result of the merge operations
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for a number of words.
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dropout (:obj:`float`, `optional`):
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A float between 0 and 1 that represents the BPE dropout to use.
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unk_token (:obj:`str`, `optional`):
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The unknown token to be used by the model.
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continuing_subword_prefix (:obj:`str`, `optional`):
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The prefix to attach to subword units that don't represent a beginning of word.
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end_of_word_suffix (:obj:`str`, `optional`):
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The suffix to attach to subword units that represent an end of word.
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fuse_unk (:obj:`bool`, `optional`):
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Whether to fuse any subsequent unknown tokens into a single one
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byte_fallback (:obj:`bool`, `optional`):
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Whether to use spm byte-fallback trick (defaults to False)
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ignore_merges (:obj:`bool`, `optional`):
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Whether or not to match tokens with the vocab before using merges.
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"""
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def __init__(
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self,
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vocab=None,
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merges=None,
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cache_capacity=None,
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dropout=None,
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unk_token=None,
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continuing_subword_prefix=None,
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end_of_word_suffix=None,
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fuse_unk=None,
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byte_fallback=False,
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ignore_merges=False,
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):
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pass
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@staticmethod
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def from_file(cls, vocab, merge, **kwargs):
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"""
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Instantiate a BPE model from the given files.
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This method is roughly equivalent to doing::
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vocab, merges = BPE.read_file(vocab_filename, merges_filename)
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bpe = BPE(vocab, merges)
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If you don't need to keep the :obj:`vocab, merges` values lying around,
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this method is more optimized than manually calling
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:meth:`~tokenizers.models.BPE.read_file` to initialize a :class:`~tokenizers.models.BPE`
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Args:
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vocab (:obj:`str`):
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The path to a :obj:`vocab.json` file
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merges (:obj:`str`):
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The path to a :obj:`merges.txt` file
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Returns:
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:class:`~tokenizers.models.BPE`: An instance of BPE loaded from these files
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"""
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pass
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def get_trainer(self):
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"""
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Get the associated :class:`~tokenizers.trainers.Trainer`
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Retrieve the :class:`~tokenizers.trainers.Trainer` associated to this
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:class:`~tokenizers.models.Model`.
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Returns:
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:class:`~tokenizers.trainers.Trainer`: The Trainer used to train this model
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"""
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pass
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def id_to_token(self, id):
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"""
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Get the token associated to an ID
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Args:
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id (:obj:`int`):
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An ID to convert to a token
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Returns:
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:obj:`str`: The token associated to the ID
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"""
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pass
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@staticmethod
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def read_file(self, vocab, merges):
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"""
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Read a :obj:`vocab.json` and a :obj:`merges.txt` files
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This method provides a way to read and parse the content of these files,
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returning the relevant data structures. If you want to instantiate some BPE models
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from memory, this method gives you the expected input from the standard files.
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Args:
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vocab (:obj:`str`):
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The path to a :obj:`vocab.json` file
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merges (:obj:`str`):
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The path to a :obj:`merges.txt` file
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Returns:
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A :obj:`Tuple` with the vocab and the merges:
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The vocabulary and merges loaded into memory
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"""
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pass
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def save(self, folder, prefix):
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"""
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Save the current model
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Save the current model in the given folder, using the given prefix for the various
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files that will get created.
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Any file with the same name that already exists in this folder will be overwritten.
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Args:
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folder (:obj:`str`):
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The path to the target folder in which to save the various files
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prefix (:obj:`str`, `optional`):
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An optional prefix, used to prefix each file name
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Returns:
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:obj:`List[str]`: The list of saved files
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"""
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pass
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def token_to_id(self, tokens):
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"""
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Get the ID associated to a token
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Args:
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token (:obj:`str`):
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A token to convert to an ID
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Returns:
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:obj:`int`: The ID associated to the token
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"""
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pass
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def tokenize(self, sequence):
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"""
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Tokenize a sequence
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Args:
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sequence (:obj:`str`):
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A sequence to tokenize
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Returns:
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A :obj:`List` of :class:`~tokenizers.Token`: The generated tokens
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"""
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pass
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class Unigram(Model):
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"""
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An implementation of the Unigram algorithm
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Args:
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vocab (:obj:`List[Tuple[str, float]]`, `optional`, `optional`):
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A list of vocabulary items and their relative score [("am", -0.2442),...]
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"""
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def __init__(self, vocab, unk_id, byte_fallback):
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pass
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def get_trainer(self):
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"""
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Get the associated :class:`~tokenizers.trainers.Trainer`
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Retrieve the :class:`~tokenizers.trainers.Trainer` associated to this
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:class:`~tokenizers.models.Model`.
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Returns:
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:class:`~tokenizers.trainers.Trainer`: The Trainer used to train this model
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"""
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pass
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def id_to_token(self, id):
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"""
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Get the token associated to an ID
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Args:
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id (:obj:`int`):
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An ID to convert to a token
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Returns:
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:obj:`str`: The token associated to the ID
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"""
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pass
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def save(self, folder, prefix):
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"""
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Save the current model
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Save the current model in the given folder, using the given prefix for the various
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files that will get created.
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Any file with the same name that already exists in this folder will be overwritten.
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Args:
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folder (:obj:`str`):
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The path to the target folder in which to save the various files
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prefix (:obj:`str`, `optional`):
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An optional prefix, used to prefix each file name
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Returns:
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:obj:`List[str]`: The list of saved files
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"""
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pass
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def token_to_id(self, tokens):
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"""
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Get the ID associated to a token
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Args:
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token (:obj:`str`):
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A token to convert to an ID
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Returns:
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:obj:`int`: The ID associated to the token
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"""
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pass
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def tokenize(self, sequence):
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"""
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Tokenize a sequence
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Args:
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sequence (:obj:`str`):
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A sequence to tokenize
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Returns:
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A :obj:`List` of :class:`~tokenizers.Token`: The generated tokens
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"""
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pass
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class WordLevel(Model):
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"""
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An implementation of the WordLevel algorithm
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Most simple tokenizer model based on mapping tokens to their corresponding id.
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Args:
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vocab (:obj:`str`, `optional`):
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A dictionnary of string keys and their ids :obj:`{"am": 0,...}`
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unk_token (:obj:`str`, `optional`):
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The unknown token to be used by the model.
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"""
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def __init__(self, vocab, unk_token):
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pass
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@staticmethod
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def from_file(vocab, unk_token):
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"""
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Instantiate a WordLevel model from the given file
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This method is roughly equivalent to doing::
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vocab = WordLevel.read_file(vocab_filename)
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wordlevel = WordLevel(vocab)
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If you don't need to keep the :obj:`vocab` values lying around, this method is
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more optimized than manually calling :meth:`~tokenizers.models.WordLevel.read_file` to
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initialize a :class:`~tokenizers.models.WordLevel`
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Args:
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vocab (:obj:`str`):
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The path to a :obj:`vocab.json` file
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Returns:
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:class:`~tokenizers.models.WordLevel`: An instance of WordLevel loaded from file
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"""
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pass
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def get_trainer(self):
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"""
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Get the associated :class:`~tokenizers.trainers.Trainer`
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Retrieve the :class:`~tokenizers.trainers.Trainer` associated to this
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:class:`~tokenizers.models.Model`.
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Returns:
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:class:`~tokenizers.trainers.Trainer`: The Trainer used to train this model
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"""
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pass
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def id_to_token(self, id):
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"""
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Get the token associated to an ID
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Args:
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id (:obj:`int`):
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An ID to convert to a token
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Returns:
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:obj:`str`: The token associated to the ID
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"""
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pass
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@staticmethod
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def read_file(vocab):
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"""
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Read a :obj:`vocab.json`
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This method provides a way to read and parse the content of a vocabulary file,
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returning the relevant data structures. If you want to instantiate some WordLevel models
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from memory, this method gives you the expected input from the standard files.
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Args:
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vocab (:obj:`str`):
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The path to a :obj:`vocab.json` file
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Returns:
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:obj:`Dict[str, int]`: The vocabulary as a :obj:`dict`
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"""
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pass
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def save(self, folder, prefix):
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"""
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Save the current model
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|
||
|
|
Save the current model in the given folder, using the given prefix for the various
|
||
|
|
files that will get created.
|
||
|
|
Any file with the same name that already exists in this folder will be overwritten.
|
||
|
|
|
||
|
|
Args:
|
||
|
|
folder (:obj:`str`):
|
||
|
|
The path to the target folder in which to save the various files
|
||
|
|
|
||
|
|
prefix (:obj:`str`, `optional`):
|
||
|
|
An optional prefix, used to prefix each file name
|
||
|
|
|
||
|
|
Returns:
|
||
|
|
:obj:`List[str]`: The list of saved files
|
||
|
|
"""
|
||
|
|
pass
|
||
|
|
|
||
|
|
def token_to_id(self, tokens):
|
||
|
|
"""
|
||
|
|
Get the ID associated to a token
|
||
|
|
|
||
|
|
Args:
|
||
|
|
token (:obj:`str`):
|
||
|
|
A token to convert to an ID
|
||
|
|
|
||
|
|
Returns:
|
||
|
|
:obj:`int`: The ID associated to the token
|
||
|
|
"""
|
||
|
|
pass
|
||
|
|
|
||
|
|
def tokenize(self, sequence):
|
||
|
|
"""
|
||
|
|
Tokenize a sequence
|
||
|
|
|
||
|
|
Args:
|
||
|
|
sequence (:obj:`str`):
|
||
|
|
A sequence to tokenize
|
||
|
|
|
||
|
|
Returns:
|
||
|
|
A :obj:`List` of :class:`~tokenizers.Token`: The generated tokens
|
||
|
|
"""
|
||
|
|
pass
|
||
|
|
|
||
|
|
class WordPiece(Model):
|
||
|
|
"""
|
||
|
|
An implementation of the WordPiece algorithm
|
||
|
|
|
||
|
|
Args:
|
||
|
|
vocab (:obj:`Dict[str, int]`, `optional`):
|
||
|
|
A dictionnary of string keys and their ids :obj:`{"am": 0,...}`
|
||
|
|
|
||
|
|
unk_token (:obj:`str`, `optional`):
|
||
|
|
The unknown token to be used by the model.
|
||
|
|
|
||
|
|
max_input_chars_per_word (:obj:`int`, `optional`):
|
||
|
|
The maximum number of characters to authorize in a single word.
|
||
|
|
"""
|
||
|
|
def __init__(self, vocab, unk_token, max_input_chars_per_word):
|
||
|
|
pass
|
||
|
|
|
||
|
|
@staticmethod
|
||
|
|
def from_file(vocab, **kwargs):
|
||
|
|
"""
|
||
|
|
Instantiate a WordPiece model from the given file
|
||
|
|
|
||
|
|
This method is roughly equivalent to doing::
|
||
|
|
|
||
|
|
vocab = WordPiece.read_file(vocab_filename)
|
||
|
|
wordpiece = WordPiece(vocab)
|
||
|
|
|
||
|
|
If you don't need to keep the :obj:`vocab` values lying around, this method is
|
||
|
|
more optimized than manually calling :meth:`~tokenizers.models.WordPiece.read_file` to
|
||
|
|
initialize a :class:`~tokenizers.models.WordPiece`
|
||
|
|
|
||
|
|
Args:
|
||
|
|
vocab (:obj:`str`):
|
||
|
|
The path to a :obj:`vocab.txt` file
|
||
|
|
|
||
|
|
Returns:
|
||
|
|
:class:`~tokenizers.models.WordPiece`: An instance of WordPiece loaded from file
|
||
|
|
"""
|
||
|
|
pass
|
||
|
|
|
||
|
|
def get_trainer(self):
|
||
|
|
"""
|
||
|
|
Get the associated :class:`~tokenizers.trainers.Trainer`
|
||
|
|
|
||
|
|
Retrieve the :class:`~tokenizers.trainers.Trainer` associated to this
|
||
|
|
:class:`~tokenizers.models.Model`.
|
||
|
|
|
||
|
|
Returns:
|
||
|
|
:class:`~tokenizers.trainers.Trainer`: The Trainer used to train this model
|
||
|
|
"""
|
||
|
|
pass
|
||
|
|
|
||
|
|
def id_to_token(self, id):
|
||
|
|
"""
|
||
|
|
Get the token associated to an ID
|
||
|
|
|
||
|
|
Args:
|
||
|
|
id (:obj:`int`):
|
||
|
|
An ID to convert to a token
|
||
|
|
|
||
|
|
Returns:
|
||
|
|
:obj:`str`: The token associated to the ID
|
||
|
|
"""
|
||
|
|
pass
|
||
|
|
|
||
|
|
@staticmethod
|
||
|
|
def read_file(vocab):
|
||
|
|
"""
|
||
|
|
Read a :obj:`vocab.txt` file
|
||
|
|
|
||
|
|
This method provides a way to read and parse the content of a standard `vocab.txt`
|
||
|
|
file as used by the WordPiece Model, returning the relevant data structures. If you
|
||
|
|
want to instantiate some WordPiece models from memory, this method gives you the
|
||
|
|
expected input from the standard files.
|
||
|
|
|
||
|
|
Args:
|
||
|
|
vocab (:obj:`str`):
|
||
|
|
The path to a :obj:`vocab.txt` file
|
||
|
|
|
||
|
|
Returns:
|
||
|
|
:obj:`Dict[str, int]`: The vocabulary as a :obj:`dict`
|
||
|
|
"""
|
||
|
|
pass
|
||
|
|
|
||
|
|
def save(self, folder, prefix):
|
||
|
|
"""
|
||
|
|
Save the current model
|
||
|
|
|
||
|
|
Save the current model in the given folder, using the given prefix for the various
|
||
|
|
files that will get created.
|
||
|
|
Any file with the same name that already exists in this folder will be overwritten.
|
||
|
|
|
||
|
|
Args:
|
||
|
|
folder (:obj:`str`):
|
||
|
|
The path to the target folder in which to save the various files
|
||
|
|
|
||
|
|
prefix (:obj:`str`, `optional`):
|
||
|
|
An optional prefix, used to prefix each file name
|
||
|
|
|
||
|
|
Returns:
|
||
|
|
:obj:`List[str]`: The list of saved files
|
||
|
|
"""
|
||
|
|
pass
|
||
|
|
|
||
|
|
def token_to_id(self, tokens):
|
||
|
|
"""
|
||
|
|
Get the ID associated to a token
|
||
|
|
|
||
|
|
Args:
|
||
|
|
token (:obj:`str`):
|
||
|
|
A token to convert to an ID
|
||
|
|
|
||
|
|
Returns:
|
||
|
|
:obj:`int`: The ID associated to the token
|
||
|
|
"""
|
||
|
|
pass
|
||
|
|
|
||
|
|
def tokenize(self, sequence):
|
||
|
|
"""
|
||
|
|
Tokenize a sequence
|
||
|
|
|
||
|
|
Args:
|
||
|
|
sequence (:obj:`str`):
|
||
|
|
A sequence to tokenize
|
||
|
|
|
||
|
|
Returns:
|
||
|
|
A :obj:`List` of :class:`~tokenizers.Token`: The generated tokens
|
||
|
|
"""
|
||
|
|
pass
|