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https://github.com/w-okada/voice-changer.git
synced 2025-02-02 16:23:58 +03:00
WIP: refactoring
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wataru
parent
308fd190f3
commit
8121c3a849
17
server/voice_changer/RVC/ModelSlot.py
Normal file
17
server/voice_changer/RVC/ModelSlot.py
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@ -0,0 +1,17 @@
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from dataclasses import dataclass
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from voice_changer.RVC.const import RVC_MODEL_TYPE_RVC
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@dataclass
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class ModelSlot:
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pyTorchModelFile: str = ""
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onnxModelFile: str = ""
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featureFile: str = ""
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indexFile: str = ""
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defaultTrans: int = 0
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modelType: int = RVC_MODEL_TYPE_RVC
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samplingRate: int = -1
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f0: bool = True
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embChannels: int = 256
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deprecated: bool = False
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embedder: str = "hubert_base" # "hubert_base", "contentvec", "distilhubert"
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@ -4,10 +4,11 @@ import json
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import resampy
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from voice_changer.RVC.ModelWrapper import ModelWrapper
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from Exceptions import NoModeLoadedException
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from voice_changer.RVC.RVCSettings import RVCSettings
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from voice_changer.utils.LoadModelParams import LoadModelParams
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from voice_changer.utils.VoiceChangerParams import VoiceChangerParams
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from dataclasses import dataclass, asdict, field
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from dataclasses import asdict
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import numpy as np
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import torch
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@ -44,62 +45,6 @@ providers = [
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]
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@dataclass
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class ModelSlot:
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pyTorchModelFile: str = ""
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onnxModelFile: str = ""
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featureFile: str = ""
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indexFile: str = ""
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defaultTrans: int = 0
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modelType: int = RVC_MODEL_TYPE_RVC
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samplingRate: int = -1
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f0: bool = True
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embChannels: int = 256
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deprecated: bool = False
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embedder: str = "hubert_base" # "hubert_base", "contentvec", "distilhubert"
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@dataclass
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class RVCSettings:
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gpu: int = 0
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dstId: int = 0
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f0Detector: str = "pm" # pm or harvest
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tran: int = 20
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silentThreshold: float = 0.00001
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extraConvertSize: int = 1024 * 32
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clusterInferRatio: float = 0.1
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framework: str = "PyTorch" # PyTorch or ONNX
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pyTorchModelFile: str = ""
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onnxModelFile: str = ""
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configFile: str = ""
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modelSlots: list[ModelSlot] = field(
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default_factory=lambda: [ModelSlot(), ModelSlot(), ModelSlot()]
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)
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indexRatio: float = 0
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rvcQuality: int = 0
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silenceFront: int = 1 # 0:off, 1:on
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modelSamplingRate: int = 48000
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modelSlotIndex: int = -1
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speakers: dict[str, int] = field(default_factory=lambda: {})
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# ↓mutableな物だけ列挙
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intData = [
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"gpu",
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"dstId",
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"tran",
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"extraConvertSize",
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"rvcQuality",
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"modelSamplingRate",
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"silenceFront",
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"modelSlotIndex",
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]
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floatData = ["silentThreshold", "indexRatio"]
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strData = ["framework", "f0Detector"]
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class RVC:
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def __init__(self, params: VoiceChangerParams):
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self.initialLoad = True
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@ -123,41 +68,44 @@ class RVC:
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print("mps: ", self.mps_enabled)
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def loadModel(self, props: LoadModelParams):
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"""
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loadModelはスロットへのエントリ（推論向けにはロードしない）。
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例外的に、まだ一つも推論向けにロードされていない場合は、ロードする。
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"""
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self.is_half = props.isHalf
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tmp_slot = props.slot
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params_str = props.params
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params = json.loads(params_str)
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newSlot = asdict(self.settings.modelSlots[tmp_slot])
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newSlot.update(
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{
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"pyTorchModelFile": props.files.pyTorchModelFilename,
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"onnxModelFile": props.files.onnxModelFilename,
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"featureFile": props.files.featureFilename,
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"indexFile": props.files.indexFilename,
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"defaultTrans": params["trans"],
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}
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)
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self.settings.modelSlots[tmp_slot] = ModelSlot(**newSlot)
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self.settings.modelSlots[
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tmp_slot
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].pyTorchModelFile = props.files.pyTorchModelFilename
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self.settings.modelSlots[tmp_slot].onnxModelFile = props.files.onnxModelFilename
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self.settings.modelSlots[tmp_slot].featureFile = props.files.featureFilename
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self.settings.modelSlots[tmp_slot].indexFile = props.files.indexFilename
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self.settings.modelSlots[tmp_slot].defaultTrans = params["trans"]
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print("[Voice Changer] RVC loading... slot:", tmp_slot)
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# Load metadata
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if (
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self.settings.modelSlots[tmp_slot].pyTorchModelFile is not None
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and self.settings.modelSlots[tmp_slot].pyTorchModelFile != ""
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):
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self._setInfoByPytorch(
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tmp_slot, self.settings.modelSlots[tmp_slot].pyTorchModelFile
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isONNX = (
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True
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if self.settings.modelSlots[tmp_slot].onnxModelFile is not None
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else False
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)
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if (
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self.settings.modelSlots[tmp_slot].onnxModelFile is not None
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and self.settings.modelSlots[tmp_slot].onnxModelFile != ""
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):
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# メタデータ設定
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if isONNX:
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self._setInfoByONNX(
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tmp_slot, self.settings.modelSlots[tmp_slot].onnxModelFile
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)
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else:
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self._setInfoByPytorch(
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tmp_slot, self.settings.modelSlots[tmp_slot].pyTorchModelFile
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)
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print(
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f"[Voice Changer] RVC loading... slot:{tmp_slot}",
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asdict(self.settings.modelSlots[tmp_slot]),
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)
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# hubertロード
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try:
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hubert_path = self.params.hubert_base
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models, saved_cfg, task = checkpoint_utils.load_model_ensemble_and_task(
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@ -173,6 +121,7 @@ class RVC:
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except Exception as e:
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print("EXCEPTION during loading hubert/contentvec model", e)
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# 初回のみロード
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if self.initialLoad or tmp_slot == self.currentSlot:
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self.prepareModel(tmp_slot)
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self.settings.modelSlotIndex = tmp_slot
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@ -197,7 +146,6 @@ class RVC:
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self.settings.modelSlots[slot].embedder = self.settings.modelSlots[
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slot
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].embedder[:-3]
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print("embedder....", self.settings.modelSlots[slot].embedder)
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self.settings.modelSlots[slot].f0 = True if cpt["f0"] == 1 else False
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self.settings.modelSlots[slot].samplingRate = cpt["config"][-1]
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@ -208,84 +156,55 @@ class RVC:
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tmp_onnx_session = ModelWrapper(file)
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self.settings.modelSlots[slot].modelType = tmp_onnx_session.getModelType()
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self.settings.modelSlots[slot].embChannels = tmp_onnx_session.getEmbChannels()
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self.settings.modelSlots[slot].embedder = tmp_onnx_session.getEmbedder()
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self.settings.modelSlots[slot].f0 = tmp_onnx_session.getF0()
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self.settings.modelSlots[slot].samplingRate = tmp_onnx_session.getSamplingRate()
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self.settings.modelSlots[slot].deprecated = tmp_onnx_session.getDeprecated()
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self.settings.modelSlots[slot].embedder = tmp_onnx_session.getEmbedder()
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print("embedder....", self.settings.modelSlots[slot].embedder)
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def prepareModel(self, slot: int):
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print("[Voice Changer] Prepare Model of slot:", slot)
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pyTorchModelFile = self.settings.modelSlots[slot].pyTorchModelFile
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onnxModelFile = self.settings.modelSlots[slot].onnxModelFile
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# PyTorchモデル生成
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if pyTorchModelFile != None and pyTorchModelFile != "":
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isONNX = (
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True if self.settings.modelSlots[slot].onnxModelFile is not None else False
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)
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if isONNX:
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print("[Voice Changer] Loading ONNX Model...")
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self.next_onnx_session = ModelWrapper(onnxModelFile)
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self.next_net_g = None
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else:
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print("[Voice Changer] Loading Pytorch Model...")
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cpt = torch.load(pyTorchModelFile, map_location="cpu")
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"""
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(1) オリジナルとrvc-webuiのモデル判定 ⇒ config全体の形状
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■ ノーマル256
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[1025, 32, 192, 192, 768, 2, 6, 3, 0, '1', [3, 7, 11], [[1, 3, 5], [1, 3, 5], [1, 3, 5]], [10, 6, 2, 2, 2], 512, [16, 16, 4, 4, 4], 109, 256, 48000]
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■ ノーマル 768対応
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[1025, 32, 192, 192, 768, 2, 6, 3, 0, '1', [3, 7, 11], [[1, 3, 5], [1, 3, 5], [1, 3, 5]], [10, 6, 2, 2, 2], 512, [16, 16, 4, 4, 4], 109, 256, 768, 48000]
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⇒ 18: オリジナル, 19: rvc-webui
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(2-1) オリジナルのノーマルorPitchレス判定 ⇒ ckp["f0"]で判定
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0: ピッチレス, 1:ノーマル
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(2-2) rvc-webuiの、(256 or 768) x (ノーマルor pitchレス)判定 ⇒ 256, or 768 は17番目の要素で判定。, ノーマルor pitchレスはckp["f0"]で判定
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"""
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torchModelSlot = self.settings.modelSlots[slot]
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cpt = torch.load(torchModelSlot.pyTorchModelFile, map_location="cpu")
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if (
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self.settings.modelSlots[slot].modelType == RVC_MODEL_TYPE_RVC
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and self.settings.modelSlots[slot].f0 is True
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torchModelSlot.modelType == RVC_MODEL_TYPE_RVC
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and torchModelSlot.f0 is True
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):
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net_g = SynthesizerTrnMs256NSFsid(*cpt["config"], is_half=self.is_half)
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elif (
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self.settings.modelSlots[slot].modelType == RVC_MODEL_TYPE_RVC
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and self.settings.modelSlots[slot].f0 is False
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torchModelSlot.modelType == RVC_MODEL_TYPE_RVC
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and torchModelSlot.f0 is False
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):
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net_g = SynthesizerTrnMs256NSFsid_nono(*cpt["config"])
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elif (
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self.settings.modelSlots[slot].modelType == RVC_MODEL_TYPE_WEBUI
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and self.settings.modelSlots[slot].f0 is True
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torchModelSlot.modelType == RVC_MODEL_TYPE_WEBUI
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and torchModelSlot.f0 is True
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):
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net_g = SynthesizerTrnMsNSFsid_webui(
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**cpt["params"], is_half=self.is_half
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)
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elif (
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self.settings.modelSlots[slot].modelType == RVC_MODEL_TYPE_WEBUI
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and self.settings.modelSlots[slot].f0 is False
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):
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else:
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net_g = SynthesizerTrnMsNSFsidNono_webui(
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**cpt["params"], is_half=self.is_half
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)
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else:
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print("unknwon")
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net_g.eval()
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net_g.load_state_dict(cpt["weight"], strict=False)
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if self.is_half:
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net_g = net_g.half()
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self.next_net_g = net_g
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else:
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print("[Voice Changer] Skip Loading Pytorch Model...")
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self.next_net_g = None
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# ONNXモデル生成
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if onnxModelFile != None and onnxModelFile != "":
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print("[Voice Changer] Loading ONNX Model...")
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self.next_onnx_session = ModelWrapper(onnxModelFile)
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# self.settings.modelSlots[slot].samplingRateOnnx = self.next_onnx_session.getSamplingRate()
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# self.settings.modelSlots[slot].f0Onnx = self.next_onnx_session.getF0()
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# self.settings.modelSlots[slot].embChannelsOnnx = self.next_onnx_session.getEmbChannels()
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# # ONNXがある場合は、ONNXの設定を優先
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# self.settings.modelSlots[slot].samplingRate = self.settings.modelSlots[slot].samplingRateOnnx
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# self.settings.modelSlots[slot].f0 = self.settings.modelSlots[slot].f0Onnx
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# self.settings.modelSlots[slot].embChannels = self.settings.modelSlots[slot].embChannelsOnnx
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else:
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print("[Voice Changer] Skip Loading ONNX Model...")
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self.next_onnx_session = None
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self.next_feature_file = self.settings.modelSlots[slot].featureFile
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@ -295,15 +214,11 @@ class RVC:
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self.next_framework = (
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"ONNX" if self.next_onnx_session is not None else "PyTorch"
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)
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print(
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"[Voice Changer] Prepare done.",
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)
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print("[Voice Changer] Prepare done.")
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return self.get_info()
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def switchModel(self):
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print(
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"[Voice Changer] Switching model..",
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)
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print("[Voice Changer] Switching model..")
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# del self.net_g
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# del self.onnx_session
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self.net_g = self.next_net_g
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44
server/voice_changer/RVC/RVCSettings.py
Normal file
44
server/voice_changer/RVC/RVCSettings.py
Normal file
@ -0,0 +1,44 @@
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from dataclasses import dataclass, field
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from voice_changer.RVC.ModelSlot import ModelSlot
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@dataclass
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class RVCSettings:
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gpu: int = 0
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dstId: int = 0
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f0Detector: str = "pm" # pm or harvest
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tran: int = 20
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silentThreshold: float = 0.00001
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extraConvertSize: int = 1024 * 32
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clusterInferRatio: float = 0.1
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framework: str = "PyTorch" # PyTorch or ONNX
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pyTorchModelFile: str = ""
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onnxModelFile: str = ""
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configFile: str = ""
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modelSlots: list[ModelSlot] = field(
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default_factory=lambda: [ModelSlot(), ModelSlot(), ModelSlot()]
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)
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indexRatio: float = 0
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rvcQuality: int = 0
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silenceFront: int = 1 # 0:off, 1:on
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modelSamplingRate: int = 48000
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modelSlotIndex: int = -1
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speakers: dict[str, int] = field(default_factory=lambda: {})
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# ↓mutableな物だけ列挙
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intData = [
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"gpu",
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"dstId",
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"tran",
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"extraConvertSize",
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"rvcQuality",
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"modelSamplingRate",
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"silenceFront",
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"modelSlotIndex",
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]
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floatData = ["silentThreshold", "indexRatio"]
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strData = ["framework", "f0Detector"]
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@ -3,12 +3,12 @@ from dataclasses import dataclass
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@dataclass
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class FilePaths:
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configFilename: str
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pyTorchModelFilename: str
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onnxModelFilename: str
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clusterTorchModelFilename: str
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featureFilename: str
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indexFilename: str
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configFilename: str | None
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pyTorchModelFilename: str | None
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onnxModelFilename: str | None
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clusterTorchModelFilename: str | None
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featureFilename: str | None
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indexFilename: str | None
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@dataclass
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