update export_jit

This commit is contained in:
lyuxiang.lx
2025-12-23 15:23:29 +08:00
parent 59cb2bf16c
commit 7538c6a73d
2 changed files with 26 additions and 22 deletions

View File

@@ -24,9 +24,8 @@ ROOT_DIR = os.path.dirname(os.path.abspath(__file__))
sys.path.append('{}/../..'.format(ROOT_DIR))
sys.path.append('{}/../../third_party/Matcha-TTS'.format(ROOT_DIR))
from cosyvoice.cli.cosyvoice import AutoModel
from cosyvoice.cli.model import CosyVoiceModel, CosyVoice2Model, CosyVoice3Model
from cosyvoice.cli.model import CosyVoiceModel, CosyVoice2Model
from cosyvoice.utils.file_utils import logging
from cosyvoice.utils.class_utils import get_model_type
def get_args():
@@ -61,7 +60,7 @@ def main():
model = AutoModel(model_dir=args.model_dir)
if get_model_type(model.model) == CosyVoiceModel:
if isinstance(model.model, CosyVoiceModel):
# 1. export llm text_encoder
llm_text_encoder = model.model.llm.text_encoder
script = get_optimized_script(llm_text_encoder)
@@ -85,7 +84,7 @@ def main():
script = get_optimized_script(flow_encoder.half())
script.save('{}/flow.encoder.fp16.zip'.format(args.model_dir))
logging.info('successfully export flow_encoder')
elif get_model_type(model.model) == CosyVoice2Model:
elif isinstance(model.model, CosyVoice2Model):
# 1. export flow encoder
flow_encoder = model.model.flow.encoder
script = get_optimized_script(flow_encoder)

View File

@@ -20,18 +20,9 @@ import numpy as np
import whisper
from typing import Callable
import torchaudio.compliance.kaldi as kaldi
import torchaudio
import os
import re
import inflect
try:
import ttsfrd
use_ttsfrd = True
except ImportError:
print("failed to import ttsfrd, use wetext instead")
from wetext import Normalizer as ZhNormalizer
from wetext import Normalizer as EnNormalizer
use_ttsfrd = False
from cosyvoice.utils.file_utils import logging, load_wav
from cosyvoice.utils.frontend_utils import contains_chinese, replace_blank, replace_corner_mark, remove_bracket, spell_out_number, split_paragraph, is_only_punctuation
@@ -60,17 +51,29 @@ class CosyVoiceFrontEnd:
else:
self.spk2info = {}
self.allowed_special = allowed_special
self.use_ttsfrd = use_ttsfrd
if self.use_ttsfrd:
self.inflect_parser = inflect.engine()
# NOTE compatible when no text frontend tool is avaliable
try:
import ttsfrd
self.frd = ttsfrd.TtsFrontendEngine()
ROOT_DIR = os.path.dirname(os.path.abspath(__file__))
assert self.frd.initialize('{}/../../pretrained_models/CosyVoice-ttsfrd/resource'.format(ROOT_DIR)) is True, \
'failed to initialize ttsfrd resource'
self.frd.set_lang_type('pinyinvg')
else:
self.zh_tn_model = ZhNormalizer(remove_erhua=False)
self.en_tn_model = EnNormalizer()
self.inflect_parser = inflect.engine()
self.text_frontend = 'ttsfrd'
logging.info('use ttsfrd frontend')
except:
try:
from wetext import Normalizer as ZhNormalizer
from wetext import Normalizer as EnNormalizer
self.zh_tn_model = ZhNormalizer(remove_erhua=False)
self.en_tn_model = EnNormalizer()
self.text_frontend = 'wetext'
logging.info('use wetext frontend')
except:
self.text_frontend = ''
logging.info('no frontend is avaliable')
def _extract_text_token(self, text):
if isinstance(text, Generator):
@@ -131,12 +134,13 @@ class CosyVoiceFrontEnd:
if text_frontend is False or text == '':
return [text] if split is True else text
text = text.strip()
if self.use_ttsfrd:
if self.text_frontend == 'ttsfrd':
texts = [i["text"] for i in json.loads(self.frd.do_voicegen_frd(text))["sentences"]]
text = ''.join(texts)
else:
if contains_chinese(text):
text = self.zh_tn_model.normalize(text)
if self.text_frontend == 'wetext':
text = self.zh_tn_model.normalize(text)
text = text.replace("\n", "")
text = replace_blank(text)
text = replace_corner_mark(text)
@@ -147,7 +151,8 @@ class CosyVoiceFrontEnd:
texts = list(split_paragraph(text, partial(self.tokenizer.encode, allowed_special=self.allowed_special), "zh", token_max_n=80,
token_min_n=60, merge_len=20, comma_split=False))
else:
text = self.en_tn_model.normalize(text)
if self.text_frontend == 'wetext':
text = self.en_tn_model.normalize(text)
text = spell_out_number(text, self.inflect_parser)
texts = list(split_paragraph(text, partial(self.tokenizer.encode, allowed_special=self.allowed_special), "en", token_max_n=80,
token_min_n=60, merge_len=20, comma_split=False))