SUMIN/HuggingFace_transformer
1
0
Fork 0
Code Issues Pull Requests Actions 7 Packages Projects Releases Wiki Activity

Use FutureWarning to deprecate (#6111)

Browse Source
This commit is contained in:
Sylvain Gugger
2020-07-29 05:20:53 -04:00
committed by GitHub
parent 640550fc7a
commit 25de74ccfe
2 changed files with 3 additions and 3 deletions
Download Patch File Download Diff File Expand all files Collapse all files

2
src/transformers/modeling_albert.py
View File

@@ -823,7 +823,7 @@ class AlbertForMaskedLM(AlbertPreTrainedModel):
if "masked_lm_labels" in kwargs: if "masked_lm_labels" in kwargs:
warnings.warn( warnings.warn(
"The `masked_lm_labels` argument is deprecated and will be removed in a future version, use `labels` instead.", "The `masked_lm_labels` argument is deprecated and will be removed in a future version, use `labels` instead.",
DeprecationWarning, FutureWarning,
) )
labels = kwargs.pop("masked_lm_labels") labels = kwargs.pop("masked_lm_labels")
assert kwargs == {}, f"Unexpected keyword arguments: {list(kwargs.keys())}." assert kwargs == {}, f"Unexpected keyword arguments: {list(kwargs.keys())}."

4
src/transformers/tokenization_utils_base.py
View File

@@ -1466,7 +1466,7 @@ class PreTrainedTokenizerBase(SpecialTokensMixin):
"use `padding='max_length'` to pad to a max length. In this case, you can give a specific " "use `padding='max_length'` to pad to a max length. In this case, you can give a specific "
"length with `max_length` (e.g. `max_length=45`) or leave max_length to None to pad to the " "length with `max_length` (e.g. `max_length=45`) or leave max_length to None to pad to the "
"maximal input size of the model (e.g. 512 for Bert).", "maximal input size of the model (e.g. 512 for Bert).",
DeprecationWarning, FutureWarning,
) )
if max_length is None: if max_length is None:
padding_strategy = PaddingStrategy.LONGEST padding_strategy = PaddingStrategy.LONGEST
@@ -1492,7 +1492,7 @@ class PreTrainedTokenizerBase(SpecialTokensMixin):
"`truncation='only_first'` (will only truncate the first sentence in the pairs) " "`truncation='only_first'` (will only truncate the first sentence in the pairs) "
"`truncation='only_second'` (will only truncate the second sentence in the pairs) " "`truncation='only_second'` (will only truncate the second sentence in the pairs) "
"or `truncation='longest_first'` (will iteratively remove tokens from the longest sentence in the pairs).", "or `truncation='longest_first'` (will iteratively remove tokens from the longest sentence in the pairs).",
DeprecationWarning, FutureWarning,
) )
truncation_strategy = TruncationStrategy(old_truncation_strategy) truncation_strategy = TruncationStrategy(old_truncation_strategy)
elif truncation is not False: elif truncation is not False: