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2025-12-30 06:47:34 -08:00
parent 0f14ca5c65
commit 1e9cfa340f
7 changed files with 18 additions and 7 deletions
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5
lib/classes/tts_engines/bark.py
View File

@@ -9,7 +9,6 @@ class Bark(TTSUtils, TTSRegistry, name='bark'):
self.cache_dir = tts_dir
self.speakers_path = None
self.tts_key = self.session['model_cache']
self.tts_zs_key = default_vc_model.rsplit('/',1)[-1]
self.pth_voice_file = None
self.sentences_total_time = 0.0
self.sentence_idx = 1
@@ -30,7 +29,6 @@ class Bark(TTSUtils, TTSRegistry, name='bark'):
self._apply_cuda_policy(using_gpu=using_gpu, enough_vram=enough_vram, seed=seed)
self.xtts_speakers = self._load_xtts_builtin_list()
self.engine = self._load_engine()
self.engine_zs = self._load_engine_zs()
except Exception as e:
error = f'__init__() error: {e}'
raise ValueError(error)
@@ -123,7 +121,6 @@ class Bark(TTSUtils, TTSRegistry, name='bark'):
print(msg)
return False
if self.engine:
device = devices['CUDA']['proc'] if self.session['device'] in ['cuda', 'jetson'] else self.session['device']
final_sentence_file = os.path.join(self.session['chapters_dir_sentences'], f'{sentence_index}.{default_audio_proc_format}')
if sentence == TTS_SML['break']:
silence_time = int(np.random.uniform(0.3, 0.6) * 100) / 100
@@ -186,6 +183,7 @@ class Bark(TTSUtils, TTSRegistry, name='bark'):
**fine_tuned_params
)
"""
device = devices['CUDA']['proc'] if self.session['device'] in ['cuda', 'jetson'] else self.session['device']
self.engine.to(device)
audio_sentence = self.engine.tts(
text=sentence,
@@ -194,6 +192,7 @@ class Bark(TTSUtils, TTSRegistry, name='bark'):
**tts_dyn_params,
**fine_tuned_params
)
self.engine.to('cpu')
if is_audio_data_valid(audio_sentence):
src_tensor = self._tensor_type(audio_sentence)
audio_tensor = src_tensor.clone().detach().unsqueeze(0).cpu()

3
lib/classes/tts_engines/common/utils.py
View File

@@ -203,6 +203,8 @@ class TTSUtils:
if self.session.get(key) is not None
}
with torch.no_grad():
device = devices['CUDA']['proc'] if self.session['device'] in ['cuda', 'jetson'] else self.session['device']
engine.to(device)
result = engine.inference(
text=default_text.strip(),
language=self.session['language_iso1'],
@@ -210,6 +212,7 @@ class TTSUtils:
speaker_embedding=speaker_embedding,
**fine_tuned_params,
)
engine.to('cpu')
audio_sentence = result.get('wav')
if is_audio_data_valid(audio_sentence):
sourceTensor = self._tensor_type(audio_sentence)

3
lib/classes/tts_engines/fairseq.py
View File

@@ -107,6 +107,7 @@ class Fairseq(TTSUtils, TTSRegistry, name='fairseq'):
file_path=tmp_in_wav,
**speaker_argument
)
self.engine.to('cpu')
if self.params['voice_path'] in self.params['semitones'].keys():
semitones = self.params['semitones'][self.params['voice_path']]
else:
@@ -150,6 +151,7 @@ class Fairseq(TTSUtils, TTSRegistry, name='fairseq'):
source_wav=source_wav,
target_wav=target_wav
)
self.engine_zs.to('cpu')
else:
error = f'Engine {self.tts_zs_key} is None'
print(error)
@@ -167,6 +169,7 @@ class Fairseq(TTSUtils, TTSRegistry, name='fairseq'):
text=re.sub(not_supported_punc_pattern, ' ', sentence),
**speaker_argument
)
self.engine.to('cpu')
if is_audio_data_valid(audio_sentence):
src_tensor = self._tensor_type(audio_sentence)
audio_tensor = src_tensor.clone().detach().unsqueeze(0).cpu()

3
lib/classes/tts_engines/tacotron.py
View File

@@ -135,6 +135,7 @@ class Tacotron2(TTSUtils, TTSRegistry, name='tacotron'):
file_path=tmp_in_wav,
**speaker_argument
)
self.engine.to('cpu')
if self.params['voice_path'] in self.params['semitones'].keys():
semitones = self.params['semitones'][self.params['voice_path']]
else:
@@ -178,6 +179,7 @@ class Tacotron2(TTSUtils, TTSRegistry, name='tacotron'):
source_wav=source_wav,
target_wav=target_wav
)
self.engine_zs.to('cpu')
else:
error = f'Engine {self.tts_zs_key} is None'
print(error)
@@ -195,6 +197,7 @@ class Tacotron2(TTSUtils, TTSRegistry, name='tacotron'):
text=re.sub(not_supported_punc_pattern, ' ', sentence),
**speaker_argument
)
self.engine.to('cpu')
if is_audio_data_valid(audio_sentence):
src_tensor = self._tensor_type(audio_sentence)
audio_tensor = src_tensor.clone().detach().unsqueeze(0).cpu()

3
lib/classes/tts_engines/vits.py
View File

@@ -120,6 +120,7 @@ class Vits(TTSUtils, TTSRegistry, name='vits'):
file_path=tmp_in_wav,
**speaker_argument
)
self.engine.to('cpu')
if self.params['voice_path'] in self.params['semitones'].keys():
semitones = self.params['semitones'][self.params['voice_path']]
else:
@@ -163,6 +164,7 @@ class Vits(TTSUtils, TTSRegistry, name='vits'):
source_wav=source_wav,
target_wav=target_wav
)
self.engine_zs.to('cpu')
else:
error = f'Engine {self.tts_zs_key} is None'
print(error)
@@ -180,6 +182,7 @@ class Vits(TTSUtils, TTSRegistry, name='vits'):
text=sentence,
**speaker_argument
)
self.engine.to('cpu')
if is_audio_data_valid(audio_sentence):
src_tensor = self._tensor_type(audio_sentence)
audio_tensor = src_tensor.clone().detach().unsqueeze(0).cpu()

3
lib/classes/tts_engines/xtts.py
View File

@@ -84,7 +84,6 @@ class XTTSv2(TTSUtils, TTSRegistry, name='xtts'):
print(msg)
return False
if self.engine:
device = devices['CUDA']['proc'] if self.session['device'] in ['cuda', 'jetson'] else self.session['device']
final_sentence_file = os.path.join(self.session['chapters_dir_sentences'], f'{sentence_index}.{default_audio_proc_format}')
if sentence == TTS_SML['break']:
silence_time = int(np.random.uniform(0.3, 0.6) * 100) / 100
@@ -131,6 +130,7 @@ class XTTSv2(TTSUtils, TTSRegistry, name='xtts'):
if self.session.get(key) is not None
}
with torch.no_grad():
device = devices['CUDA']['proc'] if self.session['device'] in ['cuda', 'jetson'] else self.session['device']
self.engine.to(device)
result = self.engine.inference(
text=sentence,
@@ -139,6 +139,7 @@ class XTTSv2(TTSUtils, TTSRegistry, name='xtts'):
speaker_embedding=self.params['speaker_embedding'],
**fine_tuned_params
)
self.engine.to('cpu')
audio_sentence = result.get('wav')
if is_audio_data_valid(audio_sentence):
src_tensor = self._tensor_type(audio_sentence)

5
lib/classes/tts_engines/yourtts.py
View File

@@ -9,7 +9,6 @@ class YourTTS(TTSUtils, TTSRegistry, name='yourtts'):
self.cache_dir = tts_dir
self.speakers_path = None
self.tts_key = self.session['model_cache']
self.tts_zs_key = default_vc_model.rsplit('/',1)[-1]
self.pth_voice_file = None
self.sentences_total_time = 0.0
self.sentence_idx = 1
@@ -30,7 +29,6 @@ class YourTTS(TTSUtils, TTSRegistry, name='yourtts'):
self._apply_cuda_policy(using_gpu=using_gpu, enough_vram=enough_vram, seed=seed)
self.xtts_speakers = self._load_xtts_builtin_list()
self.engine = self._load_engine()
self.engine_zs = self._load_engine_zs()
except Exception as e:
error = f'__init__() error: {e}'
raise ValueError(error)
@@ -75,7 +73,6 @@ class YourTTS(TTSUtils, TTSRegistry, name='yourtts'):
print(msg)
return False
if self.engine:
device = devices['CUDA']['proc'] if self.session['device'] in ['cuda', 'jetson'] else self.session['device']
final_sentence_file = os.path.join(self.session['chapters_dir_sentences'], f'{sentence_index}.{default_audio_proc_format}')
if sentence == TTS_SML['break']:
silence_time = int(np.random.uniform(0.3, 0.6) * 100) / 100
@@ -102,12 +99,14 @@ class YourTTS(TTSUtils, TTSRegistry, name='yourtts'):
voice_key = default_engine_settings[self.session['tts_engine']]['voices']['ElectroMale-2']
speaker_argument = {"speaker": voice_key}
with torch.no_grad():
device = devices['CUDA']['proc'] if self.session['device'] in ['cuda', 'jetson'] else self.session['device']
self.engine.to(device)
audio_sentence = self.engine.tts(
text=re.sub(not_supported_punc_pattern, ' ', sentence),
language=language,
**speaker_argument
)
self.engine.to('cpu')
if is_audio_data_valid(audio_sentence):
src_tensor = self._tensor_type(audio_sentence)
audio_tensor = src_tensor.clone().detach().unsqueeze(0).cpu()