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Fix lowercase bug in wordpiece tokenizer #1543

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Merged
merged 4 commits into from
Apr 4, 2024
Merged

Fix lowercase bug in wordpiece tokenizer #1543

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6d6f930
Fix lowercase bug
abuelnasr0 Apr 2, 2024
6bb9d34
Add a comment to explain
abuelnasr0 Apr 3, 2024
5c9f61e
Change mask builder
abuelnasr0 Apr 3, 2024
78fa60a
Revert "Change mask builder"
abuelnasr0 Apr 3, 2024
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14 changes: 12 additions & 2 deletions keras_nlp/tokenizers/word_piece_tokenizer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -151,8 +151,6 @@ def pretokenize(
text = tf.expand_dims(text, 0)
if split_on_cjk and split:
text = tf.strings.regex_replace(text, CJK_REGEX, r" \0 ")
if lowercase:
text = tf_text.case_fold_utf8(text)
if strip_accents:
# Normalize unicode to NFD, which splits out accent mark characters.
text = tf_text.normalize_utf8(text, "NFD")
Expand Down Expand Up @@ -187,6 +185,18 @@ def pretokenize(
delim_regex_pattern=split_pattern,
keep_delim_regex_pattern=keep_split_pattern,
)
if lowercase:
if special_tokens_pattern is not None:
# Do not lowercase special tokens in string space. They often
# contain capital letters, e.g. `"[CLS]"`.
mask = (
tf.strings.regex_replace(text, special_tokens_pattern, "६")
== "६"
)
text = tf.where(mask, text, tf_text.case_fold_utf8(text))
else:
text = tf_text.case_fold_utf8(text)

return text


Expand Down
15 changes: 15 additions & 0 deletions keras_nlp/tokenizers/word_piece_tokenizer_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -110,6 +110,21 @@ def test_special_tokens_int_dtype(self):
output = tokenizer(input_data)
self.assertAllEqual(output, [[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]])

def test_special_tokens_with_lowecase(self):
input_data = ["[UNK] [MASK] [SEP] [PAD] [CLS] THE QUICK BROWN FOX."]
special_tokens = ["[UNK]", "[MASK]", "[SEP]", "[PAD]", "[CLS]"]
vocab_data = ["the", "qu", "##ick", "br", "##own", "fox", "."]
vocab_data = [*special_tokens, *vocab_data]

tokenizer = WordPieceTokenizer(
vocabulary=vocab_data,
lowercase=True,
special_tokens=special_tokens,
special_tokens_in_strings=True,
)
output = tokenizer(input_data)
self.assertAllEqual(output, [[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]])

def test_cjk_tokens(self):
input_data = ["ah半推zz"]
vocab_data = ["[UNK]", "推", "敐", "乐", "半", "偷", "匕", "ah", "zz"]
Expand Down