[Whisper] Make tokenizer normalization public (#28136)

* [Whisper] Make tokenizer normalization public

* add to docs
This commit is contained in:
Sanchit Gandhi
2024-01-29 16:07:35 +00:00
committed by GitHub
parent e694e985d7
commit da3c79b245
3 changed files with 41 additions and 5 deletions

View File

@@ -102,6 +102,8 @@ python convert_hf_to_openai.py \
- save_vocabulary
- batch_decode
- decode
- basic_normalize
- normalize
## WhisperTokenizerFast
@@ -113,6 +115,8 @@ python convert_hf_to_openai.py \
- save_vocabulary
- batch_decode
- decode
- basic_normalize
- normalize
## WhisperFeatureExtractor

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@@ -15,6 +15,7 @@
"""Tokenization classes for Whisper."""
import json
import os
import warnings
from functools import lru_cache
from typing import List, Optional, Tuple, Union
@@ -507,6 +508,20 @@ class WhisperTokenizer(PreTrainedTokenizer):
return self.decoder.get(index, "")
def _normalize(self, text):
warnings.warn(
"The private method `_normalize` is deprecated and will be removed in v5 of Transformers."
"You can normalize an input string using the Whisper English normalizer using the `normalize` method."
)
return self.normalize(text)
def _basic_normalize(self, text, remove_diacritics=False):
warnings.warn(
"The private method `_basic_normalize` is deprecated and will be removed in v5 of Transformers."
"You can normalize an input string using the Whisper basic normalizer using the `basic_normalize` method."
)
return self.basic_normalize(text, remove_diacritics=remove_diacritics)
def normalize(self, text):
"""
Normalize a given string using the `EnglishTextNormalizer` class, which preforms commons transformation on
english text.
@@ -515,7 +530,7 @@ class WhisperTokenizer(PreTrainedTokenizer):
return normalizer(text)
@staticmethod
def _basic_normalize(text, remove_diacritics=False):
def basic_normalize(text, remove_diacritics=False):
"""
Normalize a given string using the `BasicTextNormalizer` class, which preforms commons transformation on
multilingual text.
@@ -745,10 +760,10 @@ class WhisperTokenizer(PreTrainedTokenizer):
text = "".join(sub_texts)
if normalize:
clean_text = self._normalize(text)
clean_text = self.normalize(text)
return clean_text
elif basic_normalize:
clean_text = self._basic_normalize(text, remove_diacritics=remove_diacritics)
clean_text = self.basic_normalize(text, remove_diacritics=remove_diacritics)
return clean_text
else:
return text

View File

@@ -16,6 +16,7 @@
import json
import os
import re
import warnings
from functools import lru_cache
from typing import List, Optional, Tuple
@@ -427,6 +428,22 @@ class WhisperTokenizerFast(PreTrainedTokenizerFast):
# Copied from transformers.models.whisper.tokenization_whisper.WhisperTokenizer._normalize
def _normalize(self, text):
warnings.warn(
"The private method `_normalize` is deprecated and will be removed in v5 of Transformers."
"You can normalize an input string using the Whisper English normalizer using the `normalize` method."
)
return self.normalize(text)
# Copied from transformers.models.whisper.tokenization_whisper.WhisperTokenizer._basic_normalize
def _basic_normalize(self, text, remove_diacritics=False):
warnings.warn(
"The private method `_basic_normalize` is deprecated and will be removed in v5 of Transformers."
"You can normalize an input string using the Whisper basic normalizer using the `basic_normalize` method."
)
return self.basic_normalize(text, remove_diacritics=remove_diacritics)
# Copied from transformers.models.whisper.tokenization_whisper.WhisperTokenizer.normalize
def normalize(self, text):
"""
Normalize a given string using the `EnglishTextNormalizer` class, which preforms commons transformation on
english text.
@@ -435,8 +452,8 @@ class WhisperTokenizerFast(PreTrainedTokenizerFast):
return normalizer(text)
@staticmethod
# Copied from transformers.models.whisper.tokenization_whisper.WhisperTokenizer._basic_normalize
def _basic_normalize(text, remove_diacritics=False):
# Copied from transformers.models.whisper.tokenization_whisper.WhisperTokenizer.basic_normalize
def basic_normalize(text, remove_diacritics=False):
"""
Normalize a given string using the `BasicTextNormalizer` class, which preforms commons transformation on
multilingual text.