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https://github.com/w-okada/voice-changer.git
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63 lines
2.5 KiB
Python
63 lines
2.5 KiB
Python
from torch import device
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from const import EmbedderType
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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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from voice_changer.RVC.embedder.OnnxContentvec import OnnxContentvec
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from voice_changer.utils.VoiceChangerParams import VoiceChangerParams
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class EmbedderManager:
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currentEmbedder: Embedder | None = None
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params: VoiceChangerParams
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@classmethod
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def initialize(cls, params: VoiceChangerParams):
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cls.params = params
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@classmethod
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def getEmbedder(
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cls, embederType: EmbedderType, 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, isHalf, dev)
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elif cls.currentEmbedder.matchCondition(embederType) is False:
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print("[Voice Changer] generate new embedder. (not match)")
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cls.currentEmbedder = cls.loadEmbedder(embederType, isHalf, dev)
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else:
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print("[Voice Changer] generate new embedder. (anyway)")
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cls.currentEmbedder = cls.loadEmbedder(embederType, isHalf, dev)
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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: EmbedderType, isHalf: bool, dev: device
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) -> Embedder:
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if embederType == "hubert_base":
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try:
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file = cls.params.content_vec_500_onnx
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return OnnxContentvec().loadModel(file, dev)
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except Exception as e:
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print(e)
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file = cls.params.hubert_base
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return FairseqHubert().loadModel(file, dev, isHalf)
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elif embederType == "hubert-base-japanese":
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file = cls.params.hubert_base_jp
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return FairseqHubertJp().loadModel(file, dev, isHalf)
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elif embederType == "contentvec":
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try:
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file = cls.params.content_vec_500_onnx
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return OnnxContentvec().loadModel(file, dev)
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except Exception as e:
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print(e)
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file = cls.params.hubert_base
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return FairseqContentvec().loadModel(file, dev, isHalf)
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else:
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return FairseqHubert().loadModel(file, dev, isHalf)
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