arg to skip voice latents for grabbing voice lists (for preparing datasets)
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parent
b255a77a05
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00cb19b6cf
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@ -77,7 +77,7 @@ def dynamic_range_decompression(x, C=1):
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return torch.exp(x) / C
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return torch.exp(x) / C
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def get_voices(extra_voice_dirs=[]):
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def get_voices(extra_voice_dirs=[], load_latents=True):
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dirs = [get_voice_dir()] + extra_voice_dirs
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dirs = [get_voice_dir()] + extra_voice_dirs
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voices = {}
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voices = {}
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for d in dirs:
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for d in dirs:
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@ -85,7 +85,9 @@ def get_voices(extra_voice_dirs=[]):
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for sub in subs:
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for sub in subs:
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subj = os.path.join(d, sub)
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subj = os.path.join(d, sub)
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if os.path.isdir(subj):
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if os.path.isdir(subj):
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voices[sub] = list(glob(f'{subj}/*.wav')) + list(glob(f'{subj}/*.mp3')) + list(glob(f'{subj}/*.pth'))
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voices[sub] = list(glob(f'{subj}/*.wav')) + list(glob(f'{subj}/*.mp3'))
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if load_latents:
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voices[sub] = voices[sub] + list(glob(f'{subj}/*.pth'))
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return voices
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return voices
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@ -93,7 +95,7 @@ def load_voice(voice, extra_voice_dirs=[], load_latents=True, sample_rate=22050,
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if voice == 'random':
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if voice == 'random':
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return None, None
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return None, None
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voices = get_voices(extra_voice_dirs)
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voices = get_voices(extra_voice_dirs=extra_voice_dirs, load_latents=load_latents)
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paths = voices[voice]
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paths = voices[voice]
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mtime = 0
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mtime = 0
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