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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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|
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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 dictionary 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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|
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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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|
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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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|
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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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|
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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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|
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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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|
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 |
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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: |
|
|
id (:obj:`int`): |
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|
An ID to convert to a token |
|
|
|
|
|
Returns: |
|
|
:obj:`str`: The token associated to the ID |
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|
""" |
|
|
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 dictionary 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): |
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|
pass |
|
|
|
|
|
@staticmethod |
|
|
def from_file(vocab, unk_token): |
|
|
""" |
|
|
Instantiate a WordLevel model from the given file |
|
|
|
|
|
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 |
|
|
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 dictionary 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): |
|
|
""" |
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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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