mirror of
https://github.com/w-okada/voice-changer.git
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41 lines
1.7 KiB
Python
41 lines
1.7 KiB
Python
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from torch import device
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from const import EnumEmbedderTypes
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from voice_changer.RVC.embedder.Embedder import Embedder
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from voice_changer.RVC.embedder.FairseqContentvec import FairseqContentvec
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from voice_changer.RVC.embedder.FairseqHubert import FairseqHubert
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from voice_changer.RVC.embedder.FairseqHubertJp import FairseqHubertJp
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class EmbedderManager:
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currentEmbedder: Embedder | None = None
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@classmethod
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def getEmbedder(
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cls, embederType: EnumEmbedderTypes, file: str, isHalf: bool, dev: device
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) -> Embedder:
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if cls.currentEmbedder is None:
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print("[Voice Changer] generate new embedder. (no embedder)")
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cls.currentEmbedder = cls.loadEmbedder(embederType, file, isHalf, dev)
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elif cls.currentEmbedder.matchCondition(embederType, file) is False:
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print("[Voice Changer] generate new embedder. (not match)")
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cls.currentEmbedder = cls.loadEmbedder(embederType, file, isHalf, dev)
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else:
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cls.currentEmbedder.setDevice(dev)
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cls.currentEmbedder.setHalf(isHalf)
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return cls.currentEmbedder
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@classmethod
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def loadEmbedder(
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cls, embederType: EnumEmbedderTypes, file: str, isHalf: bool, dev: device
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) -> Embedder:
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if embederType == EnumEmbedderTypes.hubert:
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return FairseqHubert().loadModel(file, dev, isHalf)
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elif embederType == EnumEmbedderTypes.hubert_jp: # same as hubert
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return FairseqHubertJp().loadModel(file, dev, isHalf)
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elif embederType == EnumEmbedderTypes.contentvec: # same as hubert
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return FairseqContentvec().loadModel(file, dev, isHalf)
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else:
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# return hubert as default
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return FairseqHubert().loadModel(file, dev, isHalf)
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