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Diffstat (limited to '.venv/lib/python3.12/site-packages/tokenizers/models/__init__.pyi')
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1 files changed, 591 insertions, 0 deletions
diff --git a/.venv/lib/python3.12/site-packages/tokenizers/models/__init__.pyi b/.venv/lib/python3.12/site-packages/tokenizers/models/__init__.pyi new file mode 100644 index 00000000..955b9a16 --- /dev/null +++ b/.venv/lib/python3.12/site-packages/tokenizers/models/__init__.pyi @@ -0,0 +1,591 @@ +# Generated content DO NOT EDIT +class Model: + """ + Base class for all models + + The model represents the actual tokenization algorithm. This is the part that + will contain and manage the learned vocabulary. + + This class cannot be constructed directly. Please use one of the concrete models. + """ + 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 + + 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 + +class BPE(Model): + """ + An implementation of the BPE (Byte-Pair Encoding) algorithm + + Args: + vocab (:obj:`Dict[str, int]`, `optional`): + A dictionnary of string keys and their ids :obj:`{"am": 0,...}` + + merges (:obj:`List[Tuple[str, str]]`, `optional`): + A list of pairs of tokens (:obj:`Tuple[str, str]`) :obj:`[("a", "b"),...]` + + cache_capacity (:obj:`int`, `optional`): + The number of words that the BPE cache can contain. The cache allows + to speed-up the process by keeping the result of the merge operations + for a number of words. + + dropout (:obj:`float`, `optional`): + A float between 0 and 1 that represents the BPE dropout to use. + + unk_token (:obj:`str`, `optional`): + The unknown token to be used by the model. + + continuing_subword_prefix (:obj:`str`, `optional`): + The prefix to attach to subword units that don't represent a beginning of word. + + end_of_word_suffix (:obj:`str`, `optional`): + The suffix to attach to subword units that represent an end of word. + + fuse_unk (:obj:`bool`, `optional`): + Whether to fuse any subsequent unknown tokens into a single one + + byte_fallback (:obj:`bool`, `optional`): + Whether to use spm byte-fallback trick (defaults to False) + + ignore_merges (:obj:`bool`, `optional`): + Whether or not to match tokens with the vocab before using merges. + """ + def __init__( + self, + vocab=None, + merges=None, + cache_capacity=None, + dropout=None, + unk_token=None, + continuing_subword_prefix=None, + end_of_word_suffix=None, + fuse_unk=None, + byte_fallback=False, + ignore_merges=False, + ): + pass + + @staticmethod + def from_file(cls, vocab, merge, **kwargs): + """ + Instantiate a BPE model from the given files. + + This method is roughly equivalent to doing:: + + vocab, merges = BPE.read_file(vocab_filename, merges_filename) + bpe = BPE(vocab, merges) + + If you don't need to keep the :obj:`vocab, merges` values lying around, + this method is more optimized than manually calling + :meth:`~tokenizers.models.BPE.read_file` to initialize a :class:`~tokenizers.models.BPE` + + Args: + vocab (:obj:`str`): + The path to a :obj:`vocab.json` file + + merges (:obj:`str`): + The path to a :obj:`merges.txt` file + + Returns: + :class:`~tokenizers.models.BPE`: An instance of BPE loaded from these files + """ + 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(self, vocab, merges): + """ + Read a :obj:`vocab.json` and a :obj:`merges.txt` files + + This method provides a way to read and parse the content of these files, + returning the relevant data structures. If you want to instantiate some BPE models + from memory, this method gives you the expected input from the standard files. + + Args: + vocab (:obj:`str`): + The path to a :obj:`vocab.json` file + + merges (:obj:`str`): + The path to a :obj:`merges.txt` file + + Returns: + A :obj:`Tuple` with the vocab and the merges: + The vocabulary and merges loaded into memory + """ + 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 + +class Unigram(Model): + """ + An implementation of the Unigram algorithm + + Args: + vocab (:obj:`List[Tuple[str, float]]`, `optional`, `optional`): + A list of vocabulary items and their relative score [("am", -0.2442),...] + """ + def __init__(self, vocab, unk_id, byte_fallback): + 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 + + 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 + +class WordLevel(Model): + """ + An implementation of the WordLevel algorithm + + Most simple tokenizer model based on mapping tokens to their corresponding id. + + Args: + vocab (:obj:`str`, `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. + """ + def __init__(self, vocab, unk_token): + pass + + @staticmethod + def from_file(vocab, unk_token): + """ + Instantiate a WordLevel model from the given file + + This method is roughly equivalent to doing:: + + vocab = WordLevel.read_file(vocab_filename) + wordlevel = WordLevel(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.WordLevel.read_file` to + initialize a :class:`~tokenizers.models.WordLevel` + + Args: + vocab (:obj:`str`): + The path to a :obj:`vocab.json` file + + Returns: + :class:`~tokenizers.models.WordLevel`: An instance of WordLevel 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.json` + + This method provides a way to read and parse the content of a vocabulary file, + returning the relevant data structures. If you want to instantiate some WordLevel models + from memory, this method gives you the expected input from the standard files. + + Args: + vocab (:obj:`str`): + The path to a :obj:`vocab.json` 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 + +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 |