Black *Version* check.

This commit is contained in:
Nicolas Patry
2020-09-23 11:39:22 +02:00
parent 9b1ef9d895
commit 35ee1968c0
5 changed files with 30 additions and 9 deletions

View File

@@ -9,7 +9,8 @@ TextInputSequence = str
PreTokenizedInputSequence = Union[List[str], Tuple[str]]
TextEncodeInput = Union[TextInputSequence, Tuple[TextInputSequence, TextInputSequence]]
PreTokenizedEncodeInput = Union[
PreTokenizedInputSequence, Tuple[PreTokenizedInputSequence, PreTokenizedInputSequence],
PreTokenizedInputSequence,
Tuple[PreTokenizedInputSequence, PreTokenizedInputSequence],
]
InputSequence = Union[TextInputSequence, PreTokenizedInputSequence]

View File

@@ -21,7 +21,8 @@ TextInputSequence = str
PreTokenizedInputSequence = Union[List[str], Tuple[str]]
TextEncodeInput = Union[TextInputSequence, Tuple[TextInputSequence, TextInputSequence]]
PreTokenizedEncodeInput = Union[
PreTokenizedInputSequence, Tuple[PreTokenizedInputSequence, PreTokenizedInputSequence],
PreTokenizedInputSequence,
Tuple[PreTokenizedInputSequence, PreTokenizedInputSequence],
]
InputSequence = Union[TextInputSequence, PreTokenizedInputSequence]
@@ -827,7 +828,10 @@ class Tokenizer:
"""
pass
def post_process(
self, encoding: Encoding, pair: Optional[Encoding] = None, add_special_tokens: bool = True,
self,
encoding: Encoding,
pair: Optional[Encoding] = None,
add_special_tokens: bool = True,
) -> Encoding:
"""Apply all the post-processing steps to the given encodings.

View File

@@ -21,7 +21,10 @@ class SentencePieceUnigramTokenizer(BaseTokenizer):
"""
def __init__(
self, vocab: Optional[str] = None, replacement: str = "", add_prefix_space: bool = True,
self,
vocab: Optional[str] = None,
replacement: str = "",
add_prefix_space: bool = True,
):
if vocab is not None:
# Let Unigram(..) fail if only one of them is None
@@ -29,7 +32,12 @@ class SentencePieceUnigramTokenizer(BaseTokenizer):
else:
tokenizer = Tokenizer(Unigram())
tokenizer.normalizer = normalizers.Sequence([normalizers.Nmt(), normalizers.NFKC(),])
tokenizer.normalizer = normalizers.Sequence(
[
normalizers.Nmt(),
normalizers.NFKC(),
]
)
tokenizer.pre_tokenizer = pre_tokenizers.Sequence(
[
pre_tokenizers.WhitespaceSplit(),
@@ -60,7 +68,9 @@ class SentencePieceUnigramTokenizer(BaseTokenizer):
""" Train the model using the given files """
trainer = trainers.UnigramTrainer(
vocab_size=vocab_size, special_tokens=special_tokens, show_progress=show_progress,
vocab_size=vocab_size,
special_tokens=special_tokens,
show_progress=show_progress,
)
if isinstance(files, str):