we do a little garbage collection
This commit is contained in:
parent
58c981d714
commit
fc5b303319
66
src/utils.py
66
src/utils.py
|
|
@ -15,6 +15,7 @@ import base64
|
|||
import re
|
||||
import urllib.request
|
||||
import signal
|
||||
import gc
|
||||
|
||||
import tqdm
|
||||
import torch
|
||||
|
|
@ -40,6 +41,9 @@ webui = None
|
|||
voicefixer = None
|
||||
whisper_model = None
|
||||
|
||||
def do_gc():
|
||||
gc.collect()
|
||||
|
||||
def get_args():
|
||||
global args
|
||||
return args
|
||||
|
|
@ -152,6 +156,8 @@ def generate(
|
|||
if not tts:
|
||||
raise Exception("TTS is uninitialized or still initializing...")
|
||||
|
||||
do_gc()
|
||||
|
||||
if voice != "microphone":
|
||||
voices = [voice]
|
||||
else:
|
||||
|
|
@ -307,6 +313,9 @@ def generate(
|
|||
# save here in case some error happens mid-batch
|
||||
torchaudio.save(f'{outdir}/{voice}_{name}.wav', audio, tts.output_sample_rate)
|
||||
|
||||
del gen
|
||||
do_gc()
|
||||
|
||||
for k in audio_cache:
|
||||
audio = audio_cache[k]['audio']
|
||||
|
||||
|
|
@ -480,19 +489,44 @@ def setup_tortoise(restart=False):
|
|||
global args
|
||||
global tts
|
||||
|
||||
if args.voice_fixer and not restart:
|
||||
do_gc()
|
||||
|
||||
if args.voice_fixer:
|
||||
setup_voicefixer(restart=restart)
|
||||
|
||||
if restart:
|
||||
del tts
|
||||
tts = None
|
||||
|
||||
print("Initializating TorToiSe...")
|
||||
print(f"Initializating TorToiSe... (using model: {args.autoregressive_model})")
|
||||
tts = TextToSpeech(minor_optimizations=not args.low_vram, autoregressive_model_path=args.autoregressive_model)
|
||||
get_model_path('dvae.pth')
|
||||
print("TorToiSe initialized, ready for generation.")
|
||||
return tts
|
||||
|
||||
def compute_latents(voice, voice_latents_chunks, progress=gr.Progress(track_tqdm=True)):
|
||||
global tts
|
||||
global args
|
||||
|
||||
if not tts:
|
||||
raise Exception("TTS is uninitialized or still initializing...")
|
||||
|
||||
do_gc()
|
||||
|
||||
voice_samples, conditioning_latents = load_voice(voice, load_latents=False)
|
||||
|
||||
if voice_samples is None:
|
||||
return
|
||||
|
||||
conditioning_latents = tts.get_conditioning_latents(voice_samples, return_mels=not args.latents_lean_and_mean, progress=progress, slices=voice_latents_chunks, force_cpu=args.force_cpu_for_conditioning_latents)
|
||||
|
||||
if len(conditioning_latents) == 4:
|
||||
conditioning_latents = (conditioning_latents[0], conditioning_latents[1], conditioning_latents[2], None)
|
||||
|
||||
torch.save(conditioning_latents, f'{get_voice_dir()}/{voice}/cond_latents.pth')
|
||||
|
||||
return voice
|
||||
|
||||
def save_training_settings( iterations=None, batch_size=None, learning_rate=None, print_rate=None, save_rate=None, name=None, dataset_name=None, dataset_path=None, validation_name=None, validation_path=None, output_name=None ):
|
||||
settings = {
|
||||
"iterations": iterations if iterations else 500,
|
||||
|
|
@ -737,32 +771,12 @@ def update_autoregressive_model(path_name):
|
|||
raise Exception("TTS is uninitialized or still initializing...")
|
||||
|
||||
print(f"Loading model: {path_name}")
|
||||
if hasattr(tts, 'load_autoregressive_model') and tts.load_autoregressive_model(path_name):
|
||||
args.autoregressive_model = path_name
|
||||
save_args_settings()
|
||||
# polyfill in case a user did NOT update the packages
|
||||
else:
|
||||
from tortoise.models.autoregressive import UnifiedVoice
|
||||
|
||||
previous_path = tts.autoregressive_model_path
|
||||
tts.autoregressive_model_path = path_name if path_name and os.path.exists(path_name) else get_model_path('autoregressive.pth')
|
||||
|
||||
del tts.autoregressive
|
||||
tts.autoregressive = UnifiedVoice(max_mel_tokens=604, max_text_tokens=402, max_conditioning_inputs=2, layers=30,
|
||||
model_dim=1024,
|
||||
heads=16, number_text_tokens=255, start_text_token=255, checkpointing=False,
|
||||
train_solo_embeddings=False).cpu().eval()
|
||||
tts.autoregressive.load_state_dict(torch.load(tts.autoregressive_model_path))
|
||||
tts.autoregressive.post_init_gpt2_config(kv_cache=tts.use_kv_cache)
|
||||
if tts.preloaded_tensors:
|
||||
tts.autoregressive = tts.autoregressive.to(tts.device)
|
||||
|
||||
if previous_path != tts.autoregressive_model_path:
|
||||
args.autoregressive_model = path_name
|
||||
save_args_settings()
|
||||
|
||||
tts.load_autoregressive_model(path_name)
|
||||
print(f"Loaded model: {tts.autoregressive_model_path}")
|
||||
|
||||
args.autoregressive_model = path_name
|
||||
save_args_settings()
|
||||
|
||||
return path_name
|
||||
|
||||
def update_args( listen, share, check_for_updates, models_from_local_only, low_vram, embed_output_metadata, latents_lean_and_mean, voice_fixer, voice_fixer_use_cuda, force_cpu_for_conditioning_latents, defer_tts_load, device_override, sample_batch_size, concurrency_count, output_sample_rate, output_volume ):
|
||||
|
|
|
|||
21
src/webui.py
21
src/webui.py
|
|
@ -86,27 +86,6 @@ def run_generation(
|
|||
gr.update(value=stats, visible=True),
|
||||
)
|
||||
|
||||
def compute_latents(voice, voice_latents_chunks, progress=gr.Progress(track_tqdm=True)):
|
||||
global tts
|
||||
global args
|
||||
|
||||
if not tts:
|
||||
raise Exception("TTS is uninitialized or still initializing...")
|
||||
|
||||
voice_samples, conditioning_latents = load_voice(voice, load_latents=False)
|
||||
|
||||
if voice_samples is None:
|
||||
return
|
||||
|
||||
conditioning_latents = tts.get_conditioning_latents(voice_samples, return_mels=not args.latents_lean_and_mean, progress=progress, slices=voice_latents_chunks, force_cpu=args.force_cpu_for_conditioning_latents)
|
||||
|
||||
if len(conditioning_latents) == 4:
|
||||
conditioning_latents = (conditioning_latents[0], conditioning_latents[1], conditioning_latents[2], None)
|
||||
|
||||
torch.save(conditioning_latents, f'{get_voice_dir()}/{voice}/cond_latents.pth')
|
||||
|
||||
return voice
|
||||
|
||||
def update_presets(value):
|
||||
PRESETS = {
|
||||
'Ultra Fast': {'num_autoregressive_samples': 16, 'diffusion_iterations': 30, 'cond_free': False},
|
||||
|
|
|
|||
Loading…
Reference in New Issue
Block a user