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WIP: support so-vits-svc 40v2. can not store content vec in indexeddb.
This commit is contained in:
wataru
parent
d5cc5c9e28
commit
76ddef5ee1
6
client/demo_so-vits-svc_40v2/dist/index.js
vendored
6
client/demo_so-vits-svc_40v2/dist/index.js
vendored
File diff suppressed because one or more lines are too long
@ -86,6 +86,26 @@ export const useModelSettingArea = (): ServerSettingState => {
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})
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}
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const onClusterFileLoadClicked = async () => {
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const file = await fileSelector("")
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if (file.name.endsWith(".pth") == false) {
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alert("モデルファイルの拡張子はpthである必要があります。")
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return
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}
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appState.serverSetting.setFileUploadSetting({
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...appState.serverSetting.fileUploadSetting,
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clusterTorchModel: {
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file: file
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}
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})
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}
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const onClusterFileClearClicked = () => {
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appState.serverSetting.setFileUploadSetting({
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...appState.serverSetting.fileUploadSetting,
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clusterTorchModel: null
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})
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}
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// const onOnnxFileLoadClicked = async () => {
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// const file = await fileSelector("")
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// if (file.name.endsWith(".onnx") == false) {
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@ -116,6 +136,7 @@ export const useModelSettingArea = (): ServerSettingState => {
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const configFilenameText = appState.serverSetting.fileUploadSetting.configFile?.filename || appState.serverSetting.fileUploadSetting.configFile?.file?.name || ""
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const hubertModelFilenameText = appState.serverSetting.fileUploadSetting.hubertTorchModel?.filename || appState.serverSetting.fileUploadSetting.hubertTorchModel?.file?.name || ""
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const clusterModelFilenameText = appState.serverSetting.fileUploadSetting.clusterTorchModel?.filename || appState.serverSetting.fileUploadSetting.clusterTorchModel?.file?.name || ""
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// const onnxModelFilenameText = appState.serverSetting.fileUploadSetting.onnxModel?.filename || appState.serverSetting.fileUploadSetting.onnxModel?.file?.name || ""
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const pyTorchFilenameText = appState.serverSetting.fileUploadSetting.pyTorchModel?.filename || appState.serverSetting.fileUploadSetting.pyTorchModel?.file?.name || ""
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@ -159,6 +180,16 @@ export const useModelSettingArea = (): ServerSettingState => {
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<div className="body-button left-margin-1" onClick={onHubertFileClearClicked}>clear</div>
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</div>
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</div>
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<div className="body-row split-3-3-4 left-padding-1 guided">
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<div className="body-item-title left-padding-2">cluster(.pth)</div>
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<div className="body-item-text">
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<div>{clusterModelFilenameText}</div>
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</div>
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<div className="body-button-container">
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<div className="body-button" onClick={onClusterFileLoadClicked}>select</div>
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<div className="body-button left-margin-1" onClick={onClusterFileClearClicked}>clear</div>
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</div>
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</div>
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{/* <div className="body-row split-3-3-4 left-padding-1 guided">
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<div className="body-item-title left-padding-2">Onnx(.onnx)</div>
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<div className="body-item-text">
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@ -66,6 +66,26 @@ export const useSpeakerSetting = () => {
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])
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const clusterInferRatioRow = useMemo(() => {
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return (
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<div className="body-row split-3-3-4 left-padding-1 guided">
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<div className="body-item-title left-padding-1 ">Cluster infer ratio</div>
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<div>
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<input type="range" className="body-item-input-slider" min="0" max="1" step="0.1" value={appState.serverSetting.serverSetting.clusterInferRatio} onChange={(e) => {
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appState.serverSetting.updateServerSettings({ ...appState.serverSetting.serverSetting, clusterInferRatio: Number(e.target.value) })
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}}></input>
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<span className="body-item-input-slider-val">{appState.serverSetting.serverSetting.clusterInferRatio}</span>
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</div>
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<div className="body-button-container">
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</div>
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</div>
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)
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}, [
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appState.serverSetting.serverSetting,
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appState.serverSetting.updateServerSettings
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])
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const noiceScaleRow = useMemo(() => {
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return (
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<div className="body-row split-3-3-4 left-padding-1 guided">
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@ -122,6 +142,7 @@ export const useSpeakerSetting = () => {
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<div className="partition-content">
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{dstIdRow}
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{tranRow}
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{clusterInferRatioRow}
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{noiceScaleRow}
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{silentThresholdRow}
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</div>
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@ -109,7 +109,7 @@ export class ServerConfigurator {
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})
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}
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loadModel = async (configFilename: string, pyTorchModelFilename: string | null, onnxModelFilename: string | null, hubertTorchModelFilename: string | null) => {
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loadModel = async (configFilename: string, pyTorchModelFilename: string | null, onnxModelFilename: string | null, hubertTorchModelFilename: string | null, clusterTorchModelFilename: string | null) => {
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const url = this.serverUrl + "/load_model"
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const info = new Promise<ServerInfo>(async (resolve) => {
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const formData = new FormData();
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@ -117,6 +117,8 @@ export class ServerConfigurator {
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formData.append("onnxModelFilename", onnxModelFilename || "-");
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formData.append("configFilename", configFilename);
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formData.append("hubertTorchModelFilename", hubertTorchModelFilename || "-");
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formData.append("clusterTorchModelFilename", clusterTorchModelFilename || "-");
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const request = new Request(url, {
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method: 'POST',
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@ -243,8 +243,8 @@ export class VoiceChangerClient {
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concatUploadedFile = (filename: string, chunkNum: number) => {
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return this.configurator.concatUploadedFile(filename, chunkNum)
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}
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loadModel = (configFilename: string, pyTorchModelFilename: string | null, onnxModelFilename: string | null, hubertTorchModelFilename: string | null) => {
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return this.configurator.loadModel(configFilename, pyTorchModelFilename, onnxModelFilename, hubertTorchModelFilename)
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loadModel = (configFilename: string, pyTorchModelFilename: string | null, onnxModelFilename: string | null, hubertTorchModelFilename: string | null, clusterTorchModelFilename: string | null) => {
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return this.configurator.loadModel(configFilename, pyTorchModelFilename, onnxModelFilename, hubertTorchModelFilename, clusterTorchModelFilename)
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}
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//## Worklet ##//
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@ -71,6 +71,7 @@ export const ServerSettingKey = {
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"predictF0": "predictF0",
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"silentThreshold": "silentThreshold",
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"extraConvertSize": "extraConvertSize",
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"clusterInferRatio": "clusterInferRatio",
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"inputSampleRate": "inputSampleRate",
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} as const
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@ -98,6 +99,7 @@ export type VoiceChangerServerSetting = {
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predictF0: number // so-vits-svc
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silentThreshold: number // so-vits-svc
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extraConvertSize: number// so-vits-svc
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clusterInferRatio: number // so-vits-svc
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inputSampleRate: InputSampleRate
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}
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@ -130,6 +132,7 @@ export const DefaultServerSetting_MMVCv15: ServerInfo = {
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predictF0: 0,
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silentThreshold: 0,
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extraConvertSize: 0,
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clusterInferRatio: 0,
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inputSampleRate: 24000,
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@ -161,6 +164,7 @@ export const DefaultServerSetting_MMVCv13: ServerInfo = {
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predictF0: 0,
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silentThreshold: 0,
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extraConvertSize: 0,
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clusterInferRatio: 0,
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inputSampleRate: 24000,
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@ -196,6 +200,7 @@ export const DefaultServerSetting_so_vits_svc_40v2: ServerInfo = {
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predictF0: 0,
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silentThreshold: 0.00001,
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extraConvertSize: 1024 * 32,
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clusterInferRatio: 0.1,
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inputSampleRate: 24000,
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@ -15,13 +15,15 @@ export type FileUploadSetting = {
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onnxModel: ModelData | null
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configFile: ModelData | null
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hubertTorchModel: ModelData | null
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clusterTorchModel: ModelData | null
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}
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const InitialFileUploadSetting: FileUploadSetting = {
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pyTorchModel: null,
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configFile: null,
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onnxModel: null,
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hubertTorchModel: null
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hubertTorchModel: null,
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clusterTorchModel: null
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}
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export type UseServerSettingProps = {
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@ -172,9 +174,12 @@ export const useServerSetting = (props: UseServerSettingProps): ServerSettingSta
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fileUploadSetting.hubertTorchModel!.data = await fileUploadSetting.hubertTorchModel!.file!.arrayBuffer()
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fileUploadSetting.hubertTorchModel!.filename = await fileUploadSetting.hubertTorchModel!.file!.name
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}
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if (props.clientType == "so_vits_svc_40v2c" && !fileUploadSetting.clusterTorchModel!.data) {
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fileUploadSetting.clusterTorchModel!.data = await fileUploadSetting.clusterTorchModel!.file!.arrayBuffer()
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fileUploadSetting.clusterTorchModel!.filename = await fileUploadSetting.clusterTorchModel!.file!.name
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}
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// ファイルをサーバにアップロード
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const models = [fileUploadSetting.onnxModel, fileUploadSetting.pyTorchModel, fileUploadSetting.hubertTorchModel].filter(x => { return x != null }) as ModelData[]
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const models = [fileUploadSetting.onnxModel, fileUploadSetting.pyTorchModel, fileUploadSetting.hubertTorchModel, fileUploadSetting.clusterTorchModel].filter(x => { return x != null }) as ModelData[]
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for (let i = 0; i < models.length; i++) {
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const progRate = 1 / models.length
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const progOffset = 100 * i * progRate
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@ -188,19 +193,26 @@ export const useServerSetting = (props: UseServerSettingProps): ServerSettingSta
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console.log(progress, end)
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})
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const loadPromise = props.voiceChangerClient.loadModel(fileUploadSetting.configFile.filename!, fileUploadSetting.pyTorchModel?.filename || null, fileUploadSetting.onnxModel?.filename || null, fileUploadSetting.hubertTorchModel?.filename || null)
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const loadPromise = props.voiceChangerClient.loadModel(fileUploadSetting.configFile.filename!, fileUploadSetting.pyTorchModel?.filename || null, fileUploadSetting.onnxModel?.filename || null, fileUploadSetting.hubertTorchModel?.filename || null, fileUploadSetting.clusterTorchModel?.filename || null)
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// サーバでロード中にキャッシュにセーブ
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const saveData: FileUploadSetting = {
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pyTorchModel: fileUploadSetting.pyTorchModel ? { data: fileUploadSetting.pyTorchModel.data, filename: fileUploadSetting.pyTorchModel.filename } : null,
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onnxModel: fileUploadSetting.onnxModel ? { data: fileUploadSetting.onnxModel.data, filename: fileUploadSetting.onnxModel.filename } : null,
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configFile: { data: fileUploadSetting.configFile.data, filename: fileUploadSetting.configFile.filename },
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hubertTorchModel: fileUploadSetting.hubertTorchModel ? {
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data: fileUploadSetting.hubertTorchModel.data, filename: fileUploadSetting.hubertTorchModel.filename
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} : null
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try {
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const saveData: FileUploadSetting = {
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pyTorchModel: fileUploadSetting.pyTorchModel ? { data: fileUploadSetting.pyTorchModel.data, filename: fileUploadSetting.pyTorchModel.filename } : null,
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onnxModel: fileUploadSetting.onnxModel ? { data: fileUploadSetting.onnxModel.data, filename: fileUploadSetting.onnxModel.filename } : null,
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configFile: { data: fileUploadSetting.configFile.data, filename: fileUploadSetting.configFile.filename },
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hubertTorchModel: fileUploadSetting.hubertTorchModel ? {
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data: fileUploadSetting.hubertTorchModel.data, filename: fileUploadSetting.hubertTorchModel.filename
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} : null,
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clusterTorchModel: fileUploadSetting.clusterTorchModel ? {
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data: fileUploadSetting.clusterTorchModel.data, filename: fileUploadSetting.clusterTorchModel.filename
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} : null
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}
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setItem(INDEXEDDB_KEY_MODEL_DATA, saveData)
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} catch (e) {
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console.log("Excpetion:::::::::", e)
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}
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setItem(INDEXEDDB_KEY_MODEL_DATA, saveData)
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await loadPromise
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setUploadProgress(0)
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@ -40,6 +40,7 @@ def setupArgParser():
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parser.add_argument("--modelType", type=str,
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default="MMVCv15", help="model type: MMVCv13, MMVCv15, so-vits-svc-40v2")
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parser.add_argument("--hubert", type=str, help="path to hubert model")
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parser.add_argument("--cluster", type=str, help="path to cluster model")
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return parser
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@ -81,6 +82,7 @@ CONFIG = args.c
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MODEL = args.m if args.m != None else None
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ONNX_MODEL = args.o if args.o != None else None
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HUBERT_MODEL = args.hubert if args.hubert != None else None
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CLUSTER_MODEL = args.cluster if args.cluster != None else None
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MODEL_TYPE = os.environ.get('MODEL_TYPE', None)
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if MODEL_TYPE == None:
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MODEL_TYPE = args.modelType
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@ -103,9 +105,9 @@ if args.colab == True:
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voiceChangerManager = VoiceChangerManager.get_instance()
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if CONFIG and (MODEL or ONNX_MODEL):
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if MODEL_TYPE == "MMVCv15" or MODEL_TYPE == "MMVCv13":
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voiceChangerManager.loadModel(CONFIG, MODEL, ONNX_MODEL, None)
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voiceChangerManager.loadModel(CONFIG, MODEL, ONNX_MODEL, None, None)
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else:
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voiceChangerManager.loadModel(CONFIG, MODEL, ONNX_MODEL, HUBERT_MODEL)
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voiceChangerManager.loadModel(CONFIG, MODEL, ONNX_MODEL, HUBERT_MODEL, CLUSTER_MODEL)
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app_fastapi = MMVC_Rest.get_instance(voiceChangerManager)
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app_socketio = MMVC_SocketIOApp.get_instance(app_fastapi, voiceChangerManager)
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@ -54,15 +54,18 @@ class MMVC_Rest_Fileuploader:
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pyTorchModelFilename: str = Form(...),
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onnxModelFilename: str = Form(...),
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configFilename: str = Form(...),
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hubertTorchModelFilename: str = Form(...)
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hubertTorchModelFilename: str = Form(...),
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clusterTorchModelFilename: str = Form(...)
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):
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print("Hubert:", hubertTorchModelFilename)
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pyTorchModelFilePath = os.path.join(UPLOAD_DIR, pyTorchModelFilename) if pyTorchModelFilename != "-" else None
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onnxModelFilePath = os.path.join(UPLOAD_DIR, onnxModelFilename) if onnxModelFilename != "-" else None
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configFilePath = os.path.join(UPLOAD_DIR, configFilename)
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hubertTorchModelFilePath = os.path.join(UPLOAD_DIR, hubertTorchModelFilename) if hubertTorchModelFilename != "-" else None
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clusterTorchModelFilePath = os.path.join(UPLOAD_DIR, clusterTorchModelFilename) if clusterTorchModelFilename != "-" else None
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info = self.voiceChangerManager.loadModel(configFilePath, pyTorchModelFilePath, onnxModelFilePath, hubertTorchModelFilePath)
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info = self.voiceChangerManager.loadModel(configFilePath, pyTorchModelFilePath, onnxModelFilePath,
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hubertTorchModelFilePath, clusterTorchModelFilePath)
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json_compatible_item_data = jsonable_encoder(info)
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return JSONResponse(content=json_compatible_item_data)
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# return {"load": f"{configFilePath}, {pyTorchModelFilePath}, {onnxModelFilePath}"}
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@ -19,6 +19,7 @@ import onnxruntime
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import pyworld as pw
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from models import SynthesizerTrn
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import cluster
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import utils
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from fairseq import checkpoint_utils
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import librosa
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@ -36,6 +37,7 @@ class SoVitsSvc40v2Settings():
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predictF0: int = 0 # 0:False, 1:True
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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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@ -44,7 +46,7 @@ class SoVitsSvc40v2Settings():
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# ↓mutableな物だけ列挙
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intData = ["gpu", "dstId", "tran", "predictF0", "extraConvertSize"]
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floatData = ["noiceScale", "silentThreshold"]
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floatData = ["noiceScale", "silentThreshold", "clusterInferRatio"]
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strData = ["framework", "f0Detector"]
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@ -58,20 +60,40 @@ class SoVitsSvc40v2:
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self.gpu_num = torch.cuda.device_count()
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self.prevVol = 0
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def loadModel(self, config: str, pyTorch_model_file: str = None, onnx_model_file: str = None, hubertTorchModel: str = None):
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def loadModel(self, config: str, pyTorch_model_file: str = None, onnx_model_file: str = None, hubertTorchModel: str = None, clusterTorchModel: str = None):
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self.settings.configFile = config
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self.hps = utils.get_hparams_from_file(config)
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# hubert model
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# vec_path = "hubert/checkpoint_best_legacy_500.pt"
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vec_path = hubertTorchModel
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models, saved_cfg, task = checkpoint_utils.load_model_ensemble_and_task(
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[vec_path],
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suffix="",
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)
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model = models[0]
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model.eval()
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self.hubert_model = utils.get_hubert_model().cpu()
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try:
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vec_path = hubertTorchModel
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print("hubert 1 ", hubertTorchModel)
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models, saved_cfg, task = checkpoint_utils.load_model_ensemble_and_task(
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[vec_path],
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suffix="",
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)
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print("hubert 2 ", hubertTorchModel)
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model = models[0]
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print("hubert 3 ", hubertTorchModel)
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model.eval()
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print("hubert 4 ", hubertTorchModel)
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self.hubert_model = model.cpu()
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print("hubert 5 ", hubertTorchModel)
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except Exception as e:
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print("EXCEPTION1", e)
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# cluster
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try:
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if os.path.exists(clusterTorchModel):
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print("load kmean11", clusterTorchModel)
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self.cluster_model = cluster.get_cluster_model(clusterTorchModel)
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print("load kmean12", clusterTorchModel)
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else:
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print("load kmean21", clusterTorchModel)
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self.cluster_model = None
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print("load kmean22", clusterTorchModel)
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except Exception as e:
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print("EXCEPTION2", e)
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if pyTorch_model_file != None:
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self.settings.pyTorchModelFile = pyTorch_model_file
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@ -157,6 +179,14 @@ class SoVitsSvc40v2:
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wav16k = torch.from_numpy(wav16k)
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c = utils.get_hubert_content(self.hubert_model, wav_16k_tensor=wav16k)
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c = utils.repeat_expand_2d(c.squeeze(0), f0.shape[1])
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if self.settings.clusterInferRatio != 0 and self.cluster_model != None:
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# self.hsp.spk.tsukuyomi
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cluster_c = cluster.get_cluster_center_result(self.cluster_model, c.cpu().numpy().T, "tsukuyomi").T
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# cluster_c = cluster.get_cluster_center_result(self.cluster_model, c.cpu().numpy().T, self.settings.dstId).T
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cluster_c = torch.FloatTensor(cluster_c).cpu()
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c = self.settings.clusterInferRatio * cluster_c + (1 - self.settings.clusterInferRatio) * c
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c = c.unsqueeze(0)
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return c, f0, uv
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||||
|
||||
@ -70,11 +70,11 @@ class VoiceChanger():
|
||||
|
||||
print(f"VoiceChanger Initialized (GPU_NUM:{self.gpu_num}, mps_enabled:{self.mps_enabled})")
|
||||
|
||||
def loadModel(self, config: str, pyTorch_model_file: str = None, onnx_model_file: str = None, hubertTorchModel: str = None):
|
||||
def loadModel(self, config: str, pyTorch_model_file: str = None, onnx_model_file: str = None, hubertTorchModel: str = None, clusterTorchModel: str = None):
|
||||
if self.modelType == "MMVCv15" or self.modelType == "MMVCv13":
|
||||
return self.voiceChanger.loadModel(config, pyTorch_model_file, onnx_model_file)
|
||||
else: # so-vits-svc-40v2
|
||||
return self.voiceChanger.loadModel(config, pyTorch_model_file, onnx_model_file, hubertTorchModel)
|
||||
return self.voiceChanger.loadModel(config, pyTorch_model_file, onnx_model_file, hubertTorchModel, clusterTorchModel)
|
||||
|
||||
def get_info(self):
|
||||
data = asdict(self.settings)
|
||||
|
||||
@ -10,8 +10,8 @@ class VoiceChangerManager():
|
||||
cls._instance.voiceChanger = VoiceChanger()
|
||||
return cls._instance
|
||||
|
||||
def loadModel(self, config, model, onnx_model, hubertTorchModel):
|
||||
info = self.voiceChanger.loadModel(config, model, onnx_model, hubertTorchModel)
|
||||
def loadModel(self, config, model, onnx_model, hubertTorchModel, clusterTorchModel):
|
||||
info = self.voiceChanger.loadModel(config, model, onnx_model, hubertTorchModel, clusterTorchModel)
|
||||
info["status"] = "OK"
|
||||
return info
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user