ai-content-maker/.venv/Lib/site-packages/TTS/tts/utils/text/tokenizer.py

217 lines
8.8 KiB
Python

from typing import Callable, Dict, List, Union
from TTS.tts.utils.text import cleaners
from TTS.tts.utils.text.characters import Graphemes, IPAPhonemes
from TTS.tts.utils.text.phonemizers import DEF_LANG_TO_PHONEMIZER, get_phonemizer_by_name
from TTS.tts.utils.text.phonemizers.multi_phonemizer import MultiPhonemizer
from TTS.utils.generic_utils import get_import_path, import_class
class TTSTokenizer:
"""🐸TTS tokenizer to convert input characters to token IDs and back.
Token IDs for OOV chars are discarded but those are stored in `self.not_found_characters` for later.
Args:
use_phonemes (bool):
Whether to use phonemes instead of characters. Defaults to False.
characters (Characters):
A Characters object to use for character-to-ID and ID-to-character mappings.
text_cleaner (callable):
A function to pre-process the text before tokenization and phonemization. Defaults to None.
phonemizer (Phonemizer):
A phonemizer object or a dict that maps language codes to phonemizer objects. Defaults to None.
Example:
>>> from TTS.tts.utils.text.tokenizer import TTSTokenizer
>>> tokenizer = TTSTokenizer(use_phonemes=False, characters=Graphemes())
>>> text = "Hello world!"
>>> ids = tokenizer.text_to_ids(text)
>>> text_hat = tokenizer.ids_to_text(ids)
>>> assert text == text_hat
"""
def __init__(
self,
use_phonemes=False,
text_cleaner: Callable = None,
characters: "BaseCharacters" = None,
phonemizer: Union["Phonemizer", Dict] = None,
add_blank: bool = False,
use_eos_bos=False,
):
self.text_cleaner = text_cleaner
self.use_phonemes = use_phonemes
self.add_blank = add_blank
self.use_eos_bos = use_eos_bos
self.characters = characters
self.not_found_characters = []
self.phonemizer = phonemizer
@property
def characters(self):
return self._characters
@characters.setter
def characters(self, new_characters):
self._characters = new_characters
self.pad_id = self.characters.char_to_id(self.characters.pad) if self.characters.pad else None
self.blank_id = self.characters.char_to_id(self.characters.blank) if self.characters.blank else None
def encode(self, text: str) -> List[int]:
"""Encodes a string of text as a sequence of IDs."""
token_ids = []
for char in text:
try:
idx = self.characters.char_to_id(char)
token_ids.append(idx)
except KeyError:
# discard but store not found characters
if char not in self.not_found_characters:
self.not_found_characters.append(char)
print(text)
print(f" [!] Character {repr(char)} not found in the vocabulary. Discarding it.")
return token_ids
def decode(self, token_ids: List[int]) -> str:
"""Decodes a sequence of IDs to a string of text."""
text = ""
for token_id in token_ids:
text += self.characters.id_to_char(token_id)
return text
def text_to_ids(self, text: str, language: str = None) -> List[int]: # pylint: disable=unused-argument
"""Converts a string of text to a sequence of token IDs.
Args:
text(str):
The text to convert to token IDs.
language(str):
The language code of the text. Defaults to None.
TODO:
- Add support for language-specific processing.
1. Text normalizatin
2. Phonemization (if use_phonemes is True)
3. Add blank char between characters
4. Add BOS and EOS characters
5. Text to token IDs
"""
# TODO: text cleaner should pick the right routine based on the language
if self.text_cleaner is not None:
text = self.text_cleaner(text)
if self.use_phonemes:
text = self.phonemizer.phonemize(text, separator="", language=language)
text = self.encode(text)
if self.add_blank:
text = self.intersperse_blank_char(text, True)
if self.use_eos_bos:
text = self.pad_with_bos_eos(text)
return text
def ids_to_text(self, id_sequence: List[int]) -> str:
"""Converts a sequence of token IDs to a string of text."""
return self.decode(id_sequence)
def pad_with_bos_eos(self, char_sequence: List[str]):
"""Pads a sequence with the special BOS and EOS characters."""
return [self.characters.bos_id] + list(char_sequence) + [self.characters.eos_id]
def intersperse_blank_char(self, char_sequence: List[str], use_blank_char: bool = False):
"""Intersperses the blank character between characters in a sequence.
Use the ```blank``` character if defined else use the ```pad``` character.
"""
char_to_use = self.characters.blank_id if use_blank_char else self.characters.pad
result = [char_to_use] * (len(char_sequence) * 2 + 1)
result[1::2] = char_sequence
return result
def print_logs(self, level: int = 0):
indent = "\t" * level
print(f"{indent}| > add_blank: {self.add_blank}")
print(f"{indent}| > use_eos_bos: {self.use_eos_bos}")
print(f"{indent}| > use_phonemes: {self.use_phonemes}")
if self.use_phonemes:
print(f"{indent}| > phonemizer:")
self.phonemizer.print_logs(level + 1)
if len(self.not_found_characters) > 0:
print(f"{indent}| > {len(self.not_found_characters)} not found characters:")
for char in self.not_found_characters:
print(f"{indent}| > {char}")
@staticmethod
def init_from_config(config: "Coqpit", characters: "BaseCharacters" = None):
"""Init Tokenizer object from config
Args:
config (Coqpit): Coqpit model config.
characters (BaseCharacters): Defines the model character set. If not set, use the default options based on
the config values. Defaults to None.
"""
# init cleaners
text_cleaner = None
if isinstance(config.text_cleaner, (str, list)):
text_cleaner = getattr(cleaners, config.text_cleaner)
# init characters
if characters is None:
# set characters based on defined characters class
if config.characters and config.characters.characters_class:
CharactersClass = import_class(config.characters.characters_class)
characters, new_config = CharactersClass.init_from_config(config)
# set characters based on config
else:
if config.use_phonemes:
# init phoneme set
characters, new_config = IPAPhonemes().init_from_config(config)
else:
# init character set
characters, new_config = Graphemes().init_from_config(config)
else:
characters, new_config = characters.init_from_config(config)
# set characters class
new_config.characters.characters_class = get_import_path(characters)
# init phonemizer
phonemizer = None
if config.use_phonemes:
if "phonemizer" in config and config.phonemizer == "multi_phonemizer":
lang_to_phonemizer_name = {}
for dataset in config.datasets:
if dataset.language != "":
lang_to_phonemizer_name[dataset.language] = dataset.phonemizer
else:
raise ValueError("Multi phonemizer requires language to be set for each dataset.")
phonemizer = MultiPhonemizer(lang_to_phonemizer_name)
else:
phonemizer_kwargs = {"language": config.phoneme_language}
if "phonemizer" in config and config.phonemizer:
phonemizer = get_phonemizer_by_name(config.phonemizer, **phonemizer_kwargs)
else:
try:
phonemizer = get_phonemizer_by_name(
DEF_LANG_TO_PHONEMIZER[config.phoneme_language], **phonemizer_kwargs
)
new_config.phonemizer = phonemizer.name()
except KeyError as e:
raise ValueError(
f"""No phonemizer found for language {config.phoneme_language}.
You may need to install a third party library for this language."""
) from e
return (
TTSTokenizer(
config.use_phonemes, text_cleaner, characters, phonemizer, config.add_blank, config.enable_eos_bos_chars
),
new_config,
)