FM / tokenizers

/usr/local/lib64/python3.6/site-packages/tokenizers/

/usr/local/lib64/python3.6/site-packages/tokenizers

Name	Size	Mode	Actions
decoders/	-	0755	rm
implementations/	-	0755	rm
models/	-	0755	rm
normalizers/	-	0755	rm
pre_tokenizers/	-	0755	rm
processors/	-	0755	rm
tools/	-	0755	rm
trainers/	-	0755	rm
__pycache__/	-	0755	rm
tokenizers.cpython-36m-x86_64-linux-gnu.so	16463952	0644	edit dl rm
__init__.py	2743	0644	edit dl rm
__init__.pyi	37610	0644	edit dl rm

Edit: /usr/local/lib64/python3.6/site-packages/tokenizers/__init__.py (2743B)

__version__ = "0.12.1"

from typing import Tuple, Union, Tuple, List
from enum import Enum

Offsets = Tuple[int, int]

TextInputSequence = str
"""A :obj:`str` that represents an input sequence """

PreTokenizedInputSequence = Union[List[str], Tuple[str]]
"""A pre-tokenized input sequence. Can be one of:

- A :obj:`List` of :obj:`str`
    - A :obj:`Tuple` of :obj:`str`
"""

TextEncodeInput = Union[
    TextInputSequence,
    Tuple[TextInputSequence, TextInputSequence],
    List[TextInputSequence],
]
"""Represents a textual input for encoding. Can be either:

- A single sequence: :data:`~tokenizers.TextInputSequence`
    - A pair of sequences:

- A :obj:`Tuple` of :data:`~tokenizers.TextInputSequence`
      - Or a :obj:`List` of :data:`~tokenizers.TextInputSequence` of size 2
"""

PreTokenizedEncodeInput = Union[
    PreTokenizedInputSequence,
    Tuple[PreTokenizedInputSequence, PreTokenizedInputSequence],
    List[PreTokenizedInputSequence],
]
"""Represents a pre-tokenized input for encoding. Can be either:

- A single sequence: :data:`~tokenizers.PreTokenizedInputSequence`
    - A pair of sequences:

- A :obj:`Tuple` of :data:`~tokenizers.PreTokenizedInputSequence`
      - Or a :obj:`List` of :data:`~tokenizers.PreTokenizedInputSequence` of size 2
"""

InputSequence = Union[TextInputSequence, PreTokenizedInputSequence]
"""Represents all the possible types of input sequences for encoding. Can be:

- When ``is_pretokenized=False``: :data:`~TextInputSequence`
    - When ``is_pretokenized=True``: :data:`~PreTokenizedInputSequence`
"""

EncodeInput = Union[TextEncodeInput, PreTokenizedEncodeInput]
"""Represents all the possible types of input for encoding. Can be:

- When ``is_pretokenized=False``: :data:`~TextEncodeInput`
    - When ``is_pretokenized=True``: :data:`~PreTokenizedEncodeInput`
"""

class OffsetReferential(Enum):
    ORIGINAL = "original"
    NORMALIZED = "normalized"

class OffsetType(Enum):
    BYTE = "byte"
    CHAR = "char"

class SplitDelimiterBehavior(Enum):
    REMOVED = "removed"
    ISOLATED = "isolated"
    MERGED_WITH_PREVIOUS = "merged_with_previous"
    MERGED_WITH_NEXT = "merged_with_next"
    CONTIGUOUS = "contiguous"

from .tokenizers import (
    Tokenizer,
    Encoding,
    AddedToken,
    Regex,
    NormalizedString,
    PreTokenizedString,
    Token,
)
from .tokenizers import decoders
from .tokenizers import models
from .tokenizers import normalizers
from .tokenizers import pre_tokenizers
from .tokenizers import processors
from .tokenizers import trainers

from .implementations import (
    ByteLevelBPETokenizer,
    CharBPETokenizer,
    SentencePieceBPETokenizer,
    SentencePieceUnigramTokenizer,
    BertWordPieceTokenizer,
)

__version__ = "0.12.1" from typing import Tuple, Union, Tuple, List from enum import Enum Offsets = Tuple[int, int] TextInputSequence = str """A :obj:`str` that represents an input sequence """ PreTokenizedInputSequence = Union[List[str], Tuple[str]] """A pre-tokenized input sequence. Can be one of: - A :obj:`List` of :obj:`str` - A :obj:`Tuple` of :obj:`str` """ TextEncodeInput = Union[ TextInputSequence, Tuple[TextInputSequence, TextInputSequence], List[TextInputSequence], ] """Represents a textual input for encoding. Can be either: - A single sequence: :data:`~tokenizers.TextInputSequence` - A pair of sequences: - A :obj:`Tuple` of :data:`~tokenizers.TextInputSequence` - Or a :obj:`List` of :data:`~tokenizers.TextInputSequence` of size 2 """ PreTokenizedEncodeInput = Union[ PreTokenizedInputSequence, Tuple[PreTokenizedInputSequence, PreTokenizedInputSequence], List[PreTokenizedInputSequence], ] """Represents a pre-tokenized input for encoding. Can be either: - A single sequence: :data:`~tokenizers.PreTokenizedInputSequence` - A pair of sequences: - A :obj:`Tuple` of :data:`~tokenizers.PreTokenizedInputSequence` - Or a :obj:`List` of :data:`~tokenizers.PreTokenizedInputSequence` of size 2 """ InputSequence = Union[TextInputSequence, PreTokenizedInputSequence] """Represents all the possible types of input sequences for encoding. Can be: - When ``is_pretokenized=False``: :data:`~TextInputSequence` - When ``is_pretokenized=True``: :data:`~PreTokenizedInputSequence` """ EncodeInput = Union[TextEncodeInput, PreTokenizedEncodeInput] """Represents all the possible types of input for encoding. Can be: - When ``is_pretokenized=False``: :data:`~TextEncodeInput` - When ``is_pretokenized=True``: :data:`~PreTokenizedEncodeInput` """ class OffsetReferential(Enum): ORIGINAL = "original" NORMALIZED = "normalized" class OffsetType(Enum): BYTE = "byte" CHAR = "char" class SplitDelimiterBehavior(Enum): REMOVED = "removed" ISOLATED = "isolated" MERGED_WITH_PREVIOUS = "merged_with_previous" MERGED_WITH_NEXT = "merged_with_next" CONTIGUOUS = "contiguous" from .tokenizers import ( Tokenizer, Encoding, AddedToken, Regex, NormalizedString, PreTokenizedString, Token, ) from .tokenizers import decoders from .tokenizers import models from .tokenizers import normalizers from .tokenizers import pre_tokenizers from .tokenizers import processors from .tokenizers import trainers from .implementations import ( ByteLevelBPETokenizer, CharBPETokenizer, SentencePieceBPETokenizer, SentencePieceUnigramTokenizer, BertWordPieceTokenizer, )