forked from mrq/ai-voice-cloning
oops
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@ -297,14 +297,14 @@ def generate(
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latents_path = f'{get_voice_dir()}/{voice}/cond_latents.pth'
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latents_path = f'{get_voice_dir()}/{voice}/cond_latents.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['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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dir = f'{get_voice_dir()}/{voice}/'
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if not os.path.isdir(dir):
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if not os.path.isdir(dir):
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os.makedirs(dir, exist_ok=True)
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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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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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else:
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if settings and "model_hash" in settings:
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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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latents_path = f'{get_voice_dir()}/{voice}/cond_latents_{settings["model_hash"][:8]}.pth'
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else:
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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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latents_path = f'{get_voice_dir()}/{voice}/cond_latents_{tts.autoregressive_model_hash[:8]}.pth'
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