forked from mrq/ai-voice-cloning
cleanup block that makes embedding latents for random/microphone happen, remove builtin voice options from voice list to avoid duplicates
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797882336b
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20
src/utils.py
20
src/utils.py
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@ -268,20 +268,15 @@ def generate(**kwargs):
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if latents and "latents" not in info:
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if latents and "latents" not in info:
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voice = info['voice']
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voice = info['voice']
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latents_path = f'{get_voice_dir()}/{voice}/cond_latents.pth'
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model_hash = settings["model_hash"][:8] if settings is not None and "model_hash" in settings else tts.autoregressive_model_hash[:8]
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dir = f'{get_voice_dir()}/{voice}/'
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latents_path = f'{dir}/cond_latents_{model_hash}.pth'
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if voice == "random" or voice == "microphone":
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if voice == "random" or voice == "microphone":
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if latents and settings is not None and settings['conditioning_latents']:
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if latents and settings is not None and settings['conditioning_latents']:
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dir = f'{get_voice_dir()}/{voice}/'
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os.makedirs(dir, exist_ok=True)
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if not os.path.isdir(dir):
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os.makedirs(dir, exist_ok=True)
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latents_path = f'{dir}/cond_latents.pth'
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torch.save(conditioning_latents, latents_path)
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torch.save(conditioning_latents, latents_path)
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else:
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if settings is not None and "model_hash" in settings:
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latents_path = f'{get_voice_dir()}/{voice}/cond_latents_{settings["model_hash"][:8]}.pth'
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else:
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latents_path = f'{get_voice_dir()}/{voice}/cond_latents_{tts.autoregressive_model_hash[:8]}.pth'
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if latents_path and os.path.exists(latents_path):
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if latents_path and os.path.exists(latents_path):
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try:
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try:
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@ -1526,10 +1521,11 @@ def import_voices(files, saveAs=None, progress=None):
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print(f"Imported voice to {path}")
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print(f"Imported voice to {path}")
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def get_voice_list(dir=get_voice_dir(), append_defaults=False):
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def get_voice_list(dir=get_voice_dir(), append_defaults=False):
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defaults = [ "random", "microphone" ]
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os.makedirs(dir, exist_ok=True)
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os.makedirs(dir, exist_ok=True)
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res = sorted([d for d in os.listdir(dir) if os.path.isdir(os.path.join(dir, d)) and len(os.listdir(os.path.join(dir, d))) > 0 ])
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res = sorted([d for d in os.listdir(dir) if d is not in defaults and os.path.isdir(os.path.join(dir, d)) and len(os.listdir(os.path.join(dir, d))) > 0 ])
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if append_defaults:
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if append_defaults:
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res = res + ["random", "microphone"]
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res = res + defaults
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return res
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return res
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def get_autoregressive_models(dir="./models/finetunes/", prefixed=False):
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def get_autoregressive_models(dir="./models/finetunes/", prefixed=False):
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