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Fixed bug where in masked_lm transformations only subwords were candidates for top_words #417

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merged 19 commits into from
Feb 15, 2021
Merged

Fixed bug where in masked_lm transformations only subwords were candidates for top_words #417

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b0a9c97
Fixed bug where only subwords were candidates for top_words
Feb 10, 2021
3828c74
Update README.md
tk-dev11 Feb 11, 2021
4316c02
update test output to ignore num_queries
jinyongyoo Feb 12, 2021
08302ea
update test
jinyongyoo Feb 12, 2021
50daaa9
update test to fix inconsistency introduced by new stanza resource
jinyongyoo Feb 12, 2021
261c026
Merge pull request #421 from QData/fix-test
jinyongyoo Feb 12, 2021
aa2ccb5
Update README.md
qiyanjun Feb 13, 2021
4019eb1
reduce font of Model/readme.md
qiyanjun Feb 13, 2021
29bf26f
make all url smaller font in models/readme.md
qiyanjun Feb 13, 2021
e32476a
fix minor errors
qiyanjun Feb 14, 2021
20f79e1
add more details in the model page on readthedoc
qiyanjun Feb 14, 2021
47a03e3
add in sphinx-markdown-tables
qiyanjun Feb 14, 2021
2009a77
Merge pull request #419 from tahmid-kazi/patch-4
qiyanjun Feb 14, 2021
2884cbf
sphinx-markdown-tables runs fine on readthedoc , but not in Github Wo…
qiyanjun Feb 14, 2021
91e364a
bypass the sphinx issue on ubuntu-latest to ubuntu-18.04
qiyanjun Feb 14, 2021
c2bc09f
Revert "bypass the sphinx issue on ubuntu-latest to ubuntu-18.04"
qiyanjun Feb 14, 2021
5780b17
Update requirements.txt
qiyanjun Feb 14, 2021
86a3d31
Fixed bug where only subwords were candidates for top_words
Feb 10, 2021
203dba9
Merge remote-tracking branch 'origin/fix_transformation_masked_lm' in…
Feb 15, 2021
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18 changes: 9 additions & 9 deletions textattack/transformations/word_insertions/word_insertion_masked_lm.py
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Original file line number Diff line number Diff line change
Expand Up @@ -113,21 +113,21 @@ def _get_new_words(self, current_text, indices_to_modify):
top_words = []
for _id in ranked_indices:
_id = _id.item()
token = self._lm_tokenizer.convert_ids_to_tokens(_id)
word = self._lm_tokenizer.convert_ids_to_tokens(_id)
if utils.check_if_subword(
token,
word,
self._language_model.config.model_type,
(masked_index == 1),
):
word = utils.strip_BPE_artifacts(
token, self._language_model.config.model_type
word, self._language_model.config.model_type
)
if (
mask_token_probs[_id] >= self.min_confidence
and utils.is_one_word(word)
and not utils.check_if_punctuations(word)
):
top_words.append(word)
if (
mask_token_probs[_id] >= self.min_confidence
and utils.is_one_word(word)
and not utils.check_if_punctuations(word)
):
top_words.append(word)

if (
len(top_words) >= self.max_candidates
Expand Down
18 changes: 9 additions & 9 deletions textattack/transformations/word_merges/word_merge_masked_lm.py
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Original file line number Diff line number Diff line change
Expand Up @@ -112,21 +112,21 @@ def _get_merged_words(self, current_text, indices_to_modify):
top_words = []
for _id in ranked_indices:
_id = _id.item()
token = self._lm_tokenizer.convert_ids_to_tokens(_id)
word = self._lm_tokenizer.convert_ids_to_tokens(_id)
if utils.check_if_subword(
token,
word,
self._language_model.config.model_type,
(masked_index == 1),
):
word = utils.strip_BPE_artifacts(
token, self._language_model.config.model_type
word, self._language_model.config.model_type
)
if (
mask_token_probs[_id] >= self.min_confidence
and utils.is_one_word(word)
and not utils.check_if_punctuations(word)
):
top_words.append(word)
if (
mask_token_probs[_id] >= self.min_confidence
and utils.is_one_word(word)
and not utils.check_if_punctuations(word)
):
top_words.append(word)

if (
len(top_words) >= self.max_candidates
Expand Down
18 changes: 9 additions & 9 deletions textattack/transformations/word_swaps/word_swap_masked_lm.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -136,21 +136,21 @@ def _bae_replacement_words(self, current_text, indices_to_modify):
top_words = []
for _id in ranked_indices:
_id = _id.item()
token = self._lm_tokenizer.convert_ids_to_tokens(_id)
word = self._lm_tokenizer.convert_ids_to_tokens(_id)
if utils.check_if_subword(
token,
word,
self._language_model.config.model_type,
(masked_index == 1),
):
word = utils.strip_BPE_artifacts(
token, self._language_model.config.model_type
word, self._language_model.config.model_type
)
if (
mask_token_probs[_id] >= self.min_confidence
and utils.is_one_word(word)
and not utils.check_if_punctuations(word)
):
top_words.append(word)
if (
mask_token_probs[_id] >= self.min_confidence
and utils.is_one_word(word)
and not utils.check_if_punctuations(word)
):
top_words.append(word)

if (
len(top_words) >= self.max_candidates
Expand Down