Upload folder using huggingface_hub

.gitignore

@@ -0,0 +1,13 @@
+checkpoints/*
+hubert/*.pt
+*.wav
+
+# Byte-compiled / optimized / DLL files
+__pycache__/
+pretrained_models/
+*.py[cod]
+*$py.class
+
+.idea/
+
+temp/

README.md

@@ -1,13 +1,44 @@
----
-title: VIST UI
-emoji: ⚡
-colorFrom: indigo
-colorTo: blue
-sdk: gradio
-sdk_version: 4.40.0
-app_file: app.py
-pinned: false
-license: mit
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# SO-VITS-SVC 4.0 WEBUI
+
+## Features
+- 支持so-vits-svc 4.0，添加4.0的一些参数；
+- 支持批量转换，输出文件名暂定为原文件名，执行打包下载；
+- 添加人声提取Tab，需要Spleeter；
+- Python 3.8。
+- Gradio框架：python main.py 简单快捷
+- Tornado框架可以python maint.py 鲁棒性强点
+- Tornado框架目前api only
+- TBD：a frontend webpage for tornado framework
+
+
+
+## Install & Run
+### 预先下载的模型文件
++ contentvec ：[checkpoint_best_legacy_500.pt](https://ibm.box.com/s/z1wgl1stco8ffooyatzdwsqn2psd9lrr)
+  + 放在`hubert`目录下
+```shell
+# 一键下载
+# contentvec
+http://obs.cstcloud.cn/share/obs/sankagenkeshi/checkpoint_best_legacy_500.pt
+# 也可手动下载放在hubert目录
+```
+
+### 配置
+0. 新建"checkpoints"文件夹，并在文件夹下面新建角色名字的子文件夹
+1. 将模型文件命名为“model.pth”，并和kmeans_10000.pt与config.json一同拷贝到角色名的子文件夹中
+2. 运行
+```bash
+pip install -r requirements.txt
+pip install setuptools==59.5.0
+```
+安装依赖
+
+3. 运行
+```bash
+python main.py
+```
+运行程序
+
+
+## Known Issue
+- Gradio在本地运行OK，但是在服务端由于需要经过Nginx/Apache的反向代理以及Gradio的queue机制（websocket）经常reset导致不能正常运行。

api/base.py

@@ -0,0 +1,32 @@
+# -*- coding: utf-8 -*-
+import json
+import tornado.web
+
+
+# noinspection PyAbstractClass
+class ApiHandler(tornado.web.RequestHandler):
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        self.json_args = None
+
+    def set_default_headers(self):
+        # 跨域测试
+        if not self.application.settings['debug']:
+            return
+        self.set_header('Access-Control-Allow-Origin', '*')
+        self.set_header('Access-Control-Allow-Methods', 'OPTIONS, PUT, POST, GET, DELETE')
+        if 'Access-Control-Request-Headers' in self.request.headers:
+            self.set_header('Access-Control-Allow-Headers',
+                            self.request.headers['Access-Control-Allow-Headers'])
+
+    def prepare(self):
+        if not self.request.headers.get('Content-Type', '').startswith('application/json'):
+            return
+        try:
+            self.json_args = json.loads(self.request.body)
+        except json.JSONDecodeError:
+            pass
+
+    async def options(self, *_args, **_kwargs):
+        # 跨域测试
+        self.set_status(204 if self.application.settings['debug'] else 405)

api/main.py

@@ -0,0 +1,15 @@
+# -*- coding: utf-8 -*-
+import tornado.web
+
+
+# noinspection PyAbstractClass
+class MainHandler(tornado.web.StaticFileHandler):
+    """为了使用Vue Router的history模式，把不存在的文件请求转发到index.html"""
+    async def get(self, path, include_body=True):
+        try:
+            await super().get(path, include_body)
+        except tornado.web.HTTPError as e:
+            if e.status_code != 404:
+                raise
+            # 不存在的文件请求转发到index.html，交给前段路由
+            await super().get('index.html', include_body)

api/svc.py

@@ -0,0 +1,338 @@
+# -*- coding: utf-8 -*-
+import logging
+import tempfile
+
+from inference.infer_tool import Svc
+from typing import *
+import api.base
+import os
+import io
+import wave
+import numpy as np
+from service.tool import audio_normalize, read_wav_file_to_numpy_array
+from utils import get_hparams_from_file
+
+logger = logging.getLogger(__name__)
+
+_svc: Optional[Svc] = None
+_model_paths: Optional[List] = None
+
+
+def init():
+    global _svc, _model_paths
+    _svc = Svc()
+    _model_paths = []
+
+    # get the path to the parent directory
+    parent_dir = os.path.abspath(os.path.join(os.getcwd(), os.curdir))
+
+    # construct the path to the "checkpoints" directory
+    checkpoints_dir = os.path.join(parent_dir, "checkpoints")
+
+    logger.debug(f"CkPoints Dir: {checkpoints_dir}")
+
+    for root, dirs, files in os.walk(checkpoints_dir):
+        for dir in dirs:
+            _model_paths.append(dir)
+
+
+# noinspection PyAbstractClass
+class ModelListHandler(api.base.ApiHandler):
+    async def get(self):
+        self.write({
+            "code": 200,
+            "msg": "ok",
+            "data": _model_paths
+        })
+
+
+# noinspection PyAbstractClass
+class SwitchHandler(api.base.ApiHandler):
+    async def post(self):
+        model_name = self.get_argument("model", "")  # model name
+        mode = self.get_argument("mode", "single")  # running mode: single or batch
+        device = self.get_argument("device", "cuda")  # "cpu" or "cuda"
+
+        if model_name == "":
+            self.set_status(400)
+            self.write({
+                "code": 400,
+                "msg": "未选择模型！",
+                "data": None
+            })
+            return
+
+        if mode not in ("single", "batch"):
+            self.set_status(400)
+            self.write({
+                "code": 400,
+                "msg": "运行模式选择错误！",
+                "data": None
+            })
+            return
+
+        if device not in ("cpu", "cuda"):
+            self.set_status(400)
+            self.write({
+                "code": 400,
+                "msg": "设备选择错误！",
+                "data": None
+            })
+            return
+
+        logger.debug(f"modelname: {model_name}\n"
+                     f"mode: {mode}\n"
+                     f"device: {device}\n")
+        try:
+            _svc.set_device(device=device)
+            logger.debug(f"Device set.")
+            _svc.load_checkpoint(path=model_name)
+            logger.debug(f"Model set.")
+        except Exception as e:
+            logger.exception(e)
+            self.set_status(500)
+            self.write({
+                "code": 500,
+                "msg": "system_error",
+                "data": None
+            })
+            return
+
+        self.write({
+            "code": 200,
+            "msg": "ok",
+            "data": {
+                "mode": mode
+            }
+        })
+
+
+# noinspection PyAbstractClass
+class SingleInferenceHandler(api.base.ApiHandler):
+    async def post(self):
+        try:
+            from scipy.io import wavfile
+
+            dsid = self.get_argument("dsid", "")
+            tran = self.get_argument("tran", "0")
+            th = self.get_argument("th", "-40.0")
+            ns = self.get_argument("ns", "0.4")
+            audiofile_dict = self.request.files.get("srcaudio", [])
+
+            if not audiofile_dict:
+                self.set_status(400)
+                self.write({
+                    "code": 400,
+                    "msg": "未上传文件！",
+                    "data": None
+                })
+                return
+
+            if dsid == "":
+                self.set_status(400)
+                self.write({
+                    "code": 400,
+                    "msg": "未选择模型！",
+                    "data": None
+                })
+                return
+
+            audiofile = audiofile_dict[0]
+            audio_filename = audiofile['filename']
+            audio_filebody = audiofile['body']
+            audio_fileext = os.path.splitext(audio_filename)[-1].lower()
+
+            with tempfile.NamedTemporaryFile(suffix=audio_fileext, delete=False) as temp_file:
+                temp_file.write(audio_filebody)
+                temp_file.close()
+
+                converted_file = await audio_normalize(full_filename=audio_filename, file_data=audio_filebody)
+                # if audio_fileext != ".wav":
+                #     logger.debug(f"file format is {audio_fileext}, not wav\n"
+                #                  f"converting to standard wav data...")
+                #     converted_file = await audio_normalize(full_filename=audio_filename, file_data=audio_filebody)
+                #     logger.debug(f"wav conversion completed.")
+                # else:
+                #     converted_file = temp_file.name
+
+                sampling_rate, audio_array = read_wav_file_to_numpy_array(converted_file)
+                os.remove(converted_file)
+
+            scraudio = (sampling_rate, audio_array)
+
+            logger.debug(f"read file {audio_filename}\n"
+                         f"sampling rate: {sampling_rate}")
+
+            tran = float(tran)
+            th = float(th)
+            ns = float(ns)
+
+            hparams = get_hparams_from_file(f"checkpoints/{dsid}/config.json")
+            spk = hparams.spk
+            real_dsid = ""
+            for k, v in spk.items():
+                if v == 0:
+                    real_dsid = k
+            logger.debug(f"read dsid is: {real_dsid}")
+
+            output_audio_sr, output_audio_array = _svc.inference(srcaudio=scraudio,
+                                                                 chara=real_dsid,
+                                                                 tran=tran,
+                                                                 slice_db=th,
+                                                                 ns=ns)
+
+            logger.debug(f"svc for {audio_filename} succeed. \n"
+                         f"audio data type: {type(output_audio_array)}\n"
+                         f"audio data sr: {output_audio_sr}")
+
+            logger.debug(f"start output data.")
+
+            # Convert the NumPy array to WAV format
+            with io.BytesIO() as wav_file:
+                wavfile.write(wav_file, sampling_rate, output_audio_array)
+                wav_data = wav_file.getvalue()
+
+            # set the response headers and body
+            self.set_header('Content-Type', 'audio/wav')
+            self.set_header('Content-Disposition', f'attachment; filename="svc_output.wav"')
+            self.write(wav_data)
+            await self.flush()
+            logger.debug(f"response completed.")
+        except Exception as e:
+            logger.exception(e)
+            self.set_status(500)
+            self.write({
+                "code": 500,
+                "msg": "system_error",
+                "data": None
+            })
+            return
+
+
+# noinspection PyAbstractClass
+class BatchInferenceHandler(api.base.ApiHandler):
+    async def post(self):
+        try:
+            from zipfile import ZipFile
+            from scipy.io import wavfile
+            import uuid
+
+            dsid = self.get_argument("dsid", "")
+            tran = self.get_argument("tran", "0")
+            th = self.get_argument("th", "-40.0")
+            ns = self.get_argument("ns", "0.4")
+            audiofile_dict = self.request.files.get("srcaudio", [])
+
+            logger.debug(len(self.request.files))
+
+            if not audiofile_dict:
+                self.set_status(400)
+                self.write({
+                    "code": 400,
+                    "msg": "未上传文件！",
+                    "data": None
+                })
+                return
+
+            if dsid == "":
+                self.set_status(400)
+                self.write({
+                    "code": 400,
+                    "msg": "未选择模型！",
+                    "data": None
+                })
+                return
+
+            temp_dir_name = "temp"
+
+            # get the path to the parent directory
+            parent_dir = os.path.abspath(os.path.join(os.getcwd(), os.curdir))
+
+            # construct the path to the "temp" directory
+            temp_dir = os.path.join(parent_dir, temp_dir_name)
+
+            logger.debug(f"TempDir: {temp_dir}")
+
+            if not os.path.exists(temp_dir):
+                os.mkdir(temp_dir)
+
+            tmp_workdir_name = f"{temp_dir}/batch_{uuid.uuid4()}"
+            if not os.path.exists(tmp_workdir_name):
+                os.mkdir(tmp_workdir_name)
+
+            output_files = []
+
+            tran = float(tran)
+            th = float(th)
+            ns = float(ns)
+
+            hparams = get_hparams_from_file(f"checkpoints/{dsid}/config.json")
+            spk = hparams.spk
+            real_dsid = ""
+            for k, v in spk.items():
+                if v == 0:
+                    real_dsid = k
+            logger.debug(f"read dsid is: {real_dsid}")
+
+            for idx, file in enumerate(audiofile_dict):
+                audio_filename = file["filename"]
+                audio_filebody = file["body"]
+                filename = os.path.basename(audio_filename)
+                audio_fileext = os.path.splitext(audio_filename)[-1].lower()
+
+                with tempfile.NamedTemporaryFile(suffix=audio_fileext, delete=False) as temp_file:
+                    temp_file.write(audio_filebody)
+                    temp_file.close()
+
+                    converted_file = await audio_normalize(full_filename=audio_filename, file_data=audio_filebody)
+
+                    # if audio_fileext != ".wav":
+                    #     logger.debug(f"file format is {audio_fileext}, not wav\n"
+                    #                  f"converting to standard wav data...")
+                    #     converted_file = await audio_normalize(full_filename=audio_filename, file_data=audio_filebody)
+                    #     logger.debug(f"wav conversion completed.")
+                    # else:
+                    #     converted_file = temp_file.name
+
+                    sampling_rate, audio_array = read_wav_file_to_numpy_array(converted_file)
+                    os.remove(converted_file)
+
+                scraudio = (sampling_rate, audio_array)
+
+                print(f"{idx}, {len(audio_filebody)}, {filename}")
+
+                output_sampling_rate, output_audio = _svc.inference(scraudio, chara=real_dsid, tran=tran,
+                                                                    slice_db=th, ns=ns)
+                new_filepath = f"{tmp_workdir_name}/{filename}"
+                wavfile.write(filename=new_filepath, rate=output_sampling_rate, data=output_audio)
+                output_files.append(new_filepath)
+
+            zipfilename = f"{tmp_workdir_name}/output.zip"
+            with ZipFile(zipfilename, "w") as zip_obj:
+                for idx, filepath in enumerate(output_files):
+                    zip_obj.write(filepath, os.path.basename(filepath))
+
+            # todo: remove data
+
+            logger.debug(f"start output data.")
+            # set response header and body
+            self.set_header("Content-Type", "application/zip")
+            self.set_header("Content-Disposition", "attachment; filename=output.zip")
+            with open(zipfilename, "rb") as file:
+                self.write(file.read())
+            await self.flush()
+            logger.debug(f"response completed.")
+        except Exception as e:
+            logger.exception(e)
+            self.set_status(500)
+            self.write({
+                "code": 500,
+                "msg": "system_error",
+                "data": None
+            })
+            return
+
+
+if __name__ == "__main__":
+    init()
+    print(_model_paths)

api/tool.py

@@ -0,0 +1,39 @@
+import logging
+import os.path
+import subprocess
+import tempfile
+
+import api.base
+from service.tool import audio_normalize
+
+logger = logging.getLogger(__name__)
+
+
+# noinspection PyAbstractClass
+class AudioNormalizerHandler(api.base.ApiHandler):
+    async def post(self):
+        try:
+            import uuid
+            uploaded_file = self.request.files['srcaudio'][0]
+            file_data = uploaded_file['body']
+            full_filename = uploaded_file['filename']
+
+            output_filename = await audio_normalize(full_filename=full_filename, file_data=file_data)
+
+            if not output_filename:
+                raise SystemError()
+
+            with open(output_filename, 'rb') as f:
+                self.set_header('Content-Type', 'audio/wav')
+                self.set_header('Content-Disposition', 'attachment; filename="converted_audio.wav"')
+                self.write(f.read())
+                await self.flush()
+                os.remove(output_filename)
+        except Exception as e:
+            logger.exception(e)
+            self.set_status(500)
+            self.write({
+                "code": 500,
+                "msg": "system_error",
+                "data": None
+            })

api/vm.py

@@ -0,0 +1,87 @@
+import io
+import logging
+import os
+import tempfile
+import wave
+import uuid
+import zipfile
+from zipfile import ZipFile
+
+import numpy as np
+from scipy.io import wavfile
+
+import api.base
+from service.tool import audio_normalize, read_wav_file_to_numpy_array
+from vextract.vocal_extract import VEX
+
+logger = logging.getLogger(__name__)
+
+
+# noinspection PyAbstractClass
+class VocalRemoverHandler(api.base.ApiHandler):
+    async def post(self):
+        try:
+            uploaded_file = self.request.files['srcaudio'][0]
+            audio_filebody = uploaded_file['body']
+            audio_filename = uploaded_file['filename']
+            audio_fileext = os.path.splitext(audio_filename)[-1].lower()
+
+            if audio_fileext != ".wav":
+                logger.debug(f"file format is {audio_fileext}, not wav\n"
+                             f"converting to standard wav data...")
+                converted_file = await audio_normalize(full_filename=audio_filename, file_data=audio_filebody)
+                with wave.open(converted_file, 'rb') as wav_file:
+                    num_frames = wav_file.getnframes()
+                    audiofile_body = wav_file.readframes(num_frames)
+                    logger.debug(f"wav conversion completed.")
+                    os.remove(converted_file)
+
+            with tempfile.NamedTemporaryFile(suffix=audio_fileext, delete=False) as temp_wav:
+                temp_wav.write(audiofile_body)
+                temp_wav.close()
+
+                converted_file = await audio_normalize(full_filename=audio_filename, file_data=audio_filebody)
+
+                sampling_rate, audio_array = read_wav_file_to_numpy_array(converted_file)
+                os.remove(converted_file)
+
+            print(f"Input Audio Shape: {audio_array.shape}\n"
+                  f"Input Audio Data Type: {audio_array.dtype}")
+
+            v = VEX()
+            [(vocal_sampling_rate, vocal_audio), (accompaniment_sampling_rate, accompaniment_audio)] = v.separate((sampling_rate, audio_array))
+
+            output_dirname = f"{uuid.uuid4()}"
+            output_dir = f"output/{output_dirname}"
+            if not os.path.exists(output_dir):
+                os.mkdir(output_dir)
+            wavfile.write(f"{output_dir}/vocals.wav", vocal_sampling_rate, vocal_audio)
+            wavfile.write(f"{output_dir}/accompaniment.wav", accompaniment_sampling_rate, accompaniment_audio)
+
+            zipfilename = f"{output_dir}/output.zip"
+            with ZipFile(zipfilename, 'w', zipfile.ZIP_DEFLATED) as zip_obj:
+                zip_obj.write(f"{output_dir}/vocals.wav")
+                zip_obj.write(f"{output_dir}/accompaniment.wav")
+
+            logger.debug(f"start output data.")
+            # set response header and body
+            self.set_header("Content-Type", "application/zip")
+            self.set_header("Content-Disposition", "attachment; filename=output.zip")
+
+            with open(zipfilename, "rb") as file:
+                self.write(file.read())
+            await self.flush()
+            logger.debug(f"response completed.")
+
+            os.remove(f"{output_dir}/vocals.wav")
+            os.remove(f"{output_dir}/accompaniment.wav")
+            os.remove(f"{output_dir}/output.zip")
+            os.rmdir(output_dir)
+        except Exception as e:
+            logger.exception(e)
+            self.set_status(500)
+            self.write({
+                "code": 500,
+                "msg": "system_error",
+                "data": None
+            })

cluster/__init__.py

@@ -0,0 +1,33 @@
+import numpy as np
+import torch
+from sklearn.cluster import KMeans
+
+
+def get_cluster_model(ckpt_path):
+    checkpoint = torch.load(ckpt_path)
+    kmeans_dict = {}
+    for spk, ckpt in checkpoint.items():
+        km = KMeans(ckpt["n_features_in_"])
+        km.__dict__["n_features_in_"] = ckpt["n_features_in_"]
+        km.__dict__["_n_threads"] = ckpt["_n_threads"]
+        km.__dict__["cluster_centers_"] = ckpt["cluster_centers_"]
+        kmeans_dict[spk] = km
+    return kmeans_dict
+
+
+def get_cluster_result(model, x, speaker):
+    """
+        x: np.array [t, 256]
+        return cluster class result
+    """
+    return model[speaker].predict(x)
+
+
+def get_cluster_center_result(model, x,speaker):
+    """x: np.array [t, 256]"""
+    predict = model[speaker].predict(x)
+    return model[speaker].cluster_centers_[predict]
+
+
+def get_center(model, x,speaker):
+    return model[speaker].cluster_centers_[x]

config.py

@@ -0,0 +1,77 @@
+# -*- coding: utf-8 -*-
+
+import configparser
+import logging
+import os
+from typing import *
+
+logger = logging.getLogger(__name__)
+
+CONFIG_PATH_LIST = [
+    os.path.join('config', 'config.ini'),
+    os.path.join('config', 'config.example.ini')
+]
+
+_config: Optional['AppConfig'] = None
+
+
+def init():
+    if reload():
+        return
+    logger.warning('Using default config')
+    global _config
+    _config = AppConfig()
+
+
+def reload():
+    config_path = ''
+    for path in CONFIG_PATH_LIST:
+        if os.path.exists(path):
+            config_path = path
+            break
+    if config_path == '':
+        return False
+
+    config = AppConfig()
+    if not config.load(config_path):
+        return False
+    global _config
+    _config = config
+    return True
+
+
+def get_config():
+    return _config
+
+
+class AppConfig:
+    def __init__(self):
+        self.database_url = 'sqlite:///data/database.db'
+        self.tornado_xheaders = False
+
+    def load(self, path):
+        try:
+            config = configparser.ConfigParser()
+            config.read(path, 'utf-8-sig')
+
+            self._load_app_config(config)
+        except Exception as e:
+            logger.exception(f'Failed to load config: {e}')
+            return False
+        return True
+
+    def _load_app_config(self, config):
+        app_section = config['app']
+        self.database_url = app_section['database_url']
+        self.tornado_xheaders = app_section.getboolean('tornado_xheaders')
+
+
+def _str_to_list(value, item_type: Type = str, container_type: Type = list):
+    value = value.strip()
+    if value == '':
+        return container_type
+    items = value.split(',')
+    items = map(lambda item: item.strip(), items)
+    if item_type is not str:
+        items = map(lambda item: item_type(item), items)
+    return container_type(items)

config/config.ini

@@ -0,0 +1,3 @@
+[app]
+database_url = sqlite:///data/database.db
+tornado_xheaders = false

frontend/.eslintrc.cjs

@@ -0,0 +1,15 @@
+/* eslint-env node */
+require('@rushstack/eslint-patch/modern-module-resolution')
+
+module.exports = {
+  root: true,
+  'extends': [
+    'plugin:vue/vue3-essential',
+    'eslint:recommended',
+    '@vue/eslint-config-typescript',
+    '@vue/eslint-config-prettier/skip-formatting'
+  ],
+  parserOptions: {
+    ecmaVersion: 'latest'
+  }
+}

frontend/.gitignore

@@ -0,0 +1,28 @@
+# Logs
+logs
+*.log
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*
+pnpm-debug.log*
+lerna-debug.log*
+
+node_modules
+.DS_Store
+dist
+dist-ssr
+coverage
+*.local
+
+/cypress/videos/
+/cypress/screenshots/
+
+# Editor directories and files
+lilyn-svs/.vscode/extensions.json
+!.vscode/extensions.json
+.idea
+*.suo
+*.ntvs*
+*.njsproj
+*.sln
+*.sw?

frontend/.prettierrc.json

@@ -0,0 +1,8 @@
+{
+  "$schema": "https://json.schemastore.org/prettierrc",
+  "semi": false,
+  "tabWidth": 2,
+  "singleQuote": true,
+  "printWidth": 100,
+  "trailingComma": "none"
+}

frontend/README.md

@@ -0,0 +1,57 @@
+# SVS SYSTEM
+
+## Features
+- 支持SVC模式切换
+- 支持批量/单个处理
+
+## Todos
+- 音频清洗（需要ffmpeg）
+- VocalRemover
+- DiffSinger support coming soon
+
+## Install & Run
+### 预先下载的模型文件
++ 需要装有Node以及npm
++ 在frontend文件夹下
+```shell
+npm i
+```
+
+### 配置
+1. 修改/frontend/src/main.ts文件，将axios.defaults.baseURL修改为服务器运行的IP地址与端口号
+2. 运行
+```bash
+npm run buid
+```
+执行构建
+
+
+## Some npm helpers
+
+```sh
+npm install
+```
+
+### Compile and Hot-Reload for Development
+
+```sh
+npm run dev
+```
+
+### Type-Check, Compile and Minify for Production
+
+```sh
+npm run build
+```
+
+### Run Unit Tests with [Vitest](https://vitest.dev/)
+
+```sh
+npm run test:unit
+```
+
+### Lint with [ESLint](https://eslint.org/)
+
+```sh
+npm run lint
+```

frontend/babel.config.js

@@ -0,0 +1,13 @@
+module.exports = {
+    presets: [
+        '@vue/cli-plugin-babel/preset'
+    ],
+    plugins: [
+        [
+            'component', {
+                'libraryName': 'element-ui',
+                'styleLibraryName': 'theme-chalk'
+            }
+        ]
+    ]
+}

frontend/env.d.ts

@@ -0,0 +1 @@
+/// <reference types="vite/client" />

frontend/index.html

@@ -0,0 +1,13 @@
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+    <meta charset="UTF-8">
+    <link rel="icon" href="/favicon.ico">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>SVS SYSTEM</title>
+  </head>
+  <body>
+    <div id="app"></div>
+    <script type="module" src="/src/main.ts"></script>
+  </body>
+</html>

frontend/package.json

@@ -0,0 +1,44 @@
+{
+  "name": "sys-system",
+  "version": "0.0.0",
+  "private": true,
+  "scripts": {
+    "dev": "vite",
+    "build": "run-p type-check build-only",
+    "preview": "vite preview",
+    "test:unit": "vitest",
+    "build-only": "vite build",
+    "type-check": "vue-tsc --noEmit -p tsconfig.vitest.json --composite false",
+    "lint": "eslint lilyn-svs --ext .vue,.js,.jsx,.cjs,.mjs,.ts,.tsx,.cts,.mts --fix --ignore-path .gitignore",
+    "format": "prettier --write src"
+  },
+  "dependencies": {
+    "@element-plus/icons-vue": "^2.1.0",
+    "axios": "^1.3.4",
+    "downloadjs": "^1.4.7",
+    "element-plus": "^2.3.1",
+    "jszip": "^3.10.1",
+    "pinia": "^2.0.32",
+    "vue": "^3.2.47",
+    "vue-router": "^4.1.6"
+  },
+  "devDependencies": {
+    "@rushstack/eslint-patch": "^1.2.0",
+    "@types/jsdom": "^21.1.0",
+    "@types/node": "^18.14.2",
+    "@vitejs/plugin-vue": "^4.0.0",
+    "@vue/eslint-config-prettier": "^7.1.0",
+    "@vue/eslint-config-typescript": "^11.0.2",
+    "@vue/test-utils": "^2.3.0",
+    "@vue/tsconfig": "^0.1.3",
+    "eslint": "^8.34.0",
+    "eslint-plugin-vue": "^9.9.0",
+    "jsdom": "^21.1.0",
+    "npm-run-all": "^4.1.5",
+    "prettier": "^2.8.4",
+    "typescript": "~4.8.4",
+    "vite": "^4.1.4",
+    "vitest": "^0.29.1",
+    "vue-tsc": "^1.2.0"
+  }
+}

frontend/src/App.vue

@@ -0,0 +1,72 @@
+<template>
+  <div id="app">
+    <router-view></router-view>
+  </div>
+</template>
+
+<script setup lang="ts">
+</script>
+
+<style scoped>
+header {
+  line-height: 1.5;
+  max-height: 100vh;
+}
+
+.logo {
+  display: block;
+  margin: 0 auto 2rem;
+}
+
+nav {
+  width: 100%;
+  font-size: 12px;
+  text-align: center;
+  margin-top: 2rem;
+}
+
+nav a.router-link-exact-active {
+  color: var(--color-text);
+}
+
+nav a.router-link-exact-active:hover {
+  background-color: transparent;
+}
+
+nav a {
+  display: inline-block;
+  padding: 0 1rem;
+  border-left: 1px solid var(--color-border);
+}
+
+nav a:first-of-type {
+  border: 0;
+}
+
+@media (min-width: 1024px) {
+  header {
+    display: flex;
+    place-items: center;
+    padding-right: calc(var(--section-gap) / 2);
+  }
+
+  .logo {
+    margin: 0 2rem 0 0;
+  }
+
+  header .wrapper {
+    display: flex;
+    place-items: flex-start;
+    flex-wrap: wrap;
+  }
+
+  nav {
+    text-align: left;
+    margin-left: -1rem;
+    font-size: 1rem;
+
+    padding: 1rem 0;
+    margin-top: 1rem;
+  }
+}
+</style>

frontend/src/assets/base.css

@@ -0,0 +1,74 @@
+/* color palette from <https://github.com/vuejs/theme> */
+:root {
+  --vt-c-white: #ffffff;
+  --vt-c-white-soft: #f8f8f8;
+  --vt-c-white-mute: #f2f2f2;
+
+  --vt-c-black: #181818;
+  --vt-c-black-soft: #222222;
+  --vt-c-black-mute: #282828;
+
+  --vt-c-indigo: #2c3e50;
+
+  --vt-c-divider-light-1: rgba(60, 60, 60, 0.29);
+  --vt-c-divider-light-2: rgba(60, 60, 60, 0.12);
+  --vt-c-divider-dark-1: rgba(84, 84, 84, 0.65);
+  --vt-c-divider-dark-2: rgba(84, 84, 84, 0.48);
+
+  --vt-c-text-light-1: var(--vt-c-indigo);
+  --vt-c-text-light-2: rgba(60, 60, 60, 0.66);
+  --vt-c-text-dark-1: var(--vt-c-white);
+  --vt-c-text-dark-2: rgba(235, 235, 235, 0.64);
+}
+
+/* semantic color variables for this project */
+:root {
+  --color-background: var(--vt-c-white);
+  --color-background-soft: var(--vt-c-white-soft);
+  --color-background-mute: var(--vt-c-white-mute);
+
+  --color-border: var(--vt-c-divider-light-2);
+  --color-border-hover: var(--vt-c-divider-light-1);
+
+  --color-heading: var(--vt-c-text-light-1);
+  --color-text: var(--vt-c-text-light-1);
+
+  --section-gap: 160px;
+}
+
+@media (prefers-color-scheme: dark) {
+  :root {
+    --color-background: var(--vt-c-black);
+    --color-background-soft: var(--vt-c-black-soft);
+    --color-background-mute: var(--vt-c-black-mute);
+
+    --color-border: var(--vt-c-divider-dark-2);
+    --color-border-hover: var(--vt-c-divider-dark-1);
+
+    --color-heading: var(--vt-c-text-dark-1);
+    --color-text: var(--vt-c-text-dark-2);
+  }
+}
+
+*,
+*::before,
+*::after {
+  box-sizing: border-box;
+  margin: 0;
+  position: relative;
+  font-weight: normal;
+}
+
+body {
+  min-height: 100vh;
+  color: var(--color-text);
+  background: var(--color-background);
+  transition: color 0.5s, background-color 0.5s;
+  line-height: 1.6;
+  font-family: Inter, -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu,
+    Cantarell, 'Fira Sans', 'Droid Sans', 'Helvetica Neue', sans-serif;
+  font-size: 15px;
+  text-rendering: optimizeLegibility;
+  -webkit-font-smoothing: antialiased;
+  -moz-osx-font-smoothing: grayscale;
+}

frontend/src/assets/main.css

@@ -0,0 +1,35 @@
+@import 'base.css';
+
+#app {
+  max-width: 1280px;
+  margin: 0 auto;
+  padding: 2rem;
+
+  font-weight: normal;
+}
+
+a,
+.green {
+  text-decoration: none;
+  color: hsla(160, 100%, 37%, 1);
+  transition: 0.4s;
+}
+
+@media (hover: hover) {
+  a:hover {
+    background-color: hsla(160, 100%, 37%, 0.2);
+  }
+}
+
+@media (min-width: 1024px) {
+  body {
+    display: flex;
+    place-items: center;
+  }
+
+  #app {
+    display: contents;
+    grid-template-columns: 1fr 1fr;
+    padding: 0 2rem;
+  }
+}

frontend/src/components/GreetingAudio.vue

@@ -0,0 +1,47 @@
+<script setup lang="ts">
+defineProps<{
+  src: string
+  title: string
+}>()
+</script>
+
+<template>
+  <div class="greetings">
+    <h3 style="color: #2b2f3a">{{ title }}</h3>
+    <audio class="greetings-audio" controls :src="src"></audio>
+  </div>
+</template>
+
+<style scoped>
+h1 {
+  font-weight: 500;
+  font-size: 2.6rem;
+  top: -10px;
+}
+
+h3 {
+  font-size: 1.2rem;
+}
+
+.greetings {
+  position: fixed;
+  bottom: 0;
+  right: 30px;
+  background-color: #3498db;
+  box-shadow: 0 0 10px rgba(0, 0, 0, 0.5);
+  border-radius: 10px;
+  color: #fff;
+  padding: 10px;
+}
+
+.greetings h3 {
+  text-align: left;
+  margin: 10px;
+}
+
+@media (min-width: 1024px) {
+  .greetings h3 {
+    text-align: left;
+  }
+}
+</style>

frontend/src/components/TheWelcome.vue

@@ -0,0 +1,86 @@
+<script setup lang="ts">
+import WelcomeItem from './WelcomeItem.vue'
+import DocumentationIcon from './icons/IconDocumentation.vue'
+import ToolingIcon from './icons/IconTooling.vue'
+import EcosystemIcon from './icons/IconEcosystem.vue'
+import CommunityIcon from './icons/IconCommunity.vue'
+import SupportIcon from './icons/IconSupport.vue'
+</script>
+
+<template>
+  <WelcomeItem>
+    <template #icon>
+      <DocumentationIcon />
+    </template>
+    <template #heading>Documentation</template>
+
+    Vue’s
+    <a href="https://vuejs.org/" target="_blank" rel="noopener">official documentation</a>
+    provides you with all information you need to get started.
+  </WelcomeItem>
+
+  <WelcomeItem>
+    <template #icon>
+      <ToolingIcon />
+    </template>
+    <template #heading>Tooling</template>
+
+    This project is served and bundled with
+    <a href="https://vitejs.dev/guide/features.html" target="_blank" rel="noopener">Vite</a>. The
+    recommended IDE setup is
+    <a href="https://code.visualstudio.com/" target="_blank" rel="noopener">VSCode</a> +
+    <a href="https://github.com/johnsoncodehk/volar" target="_blank" rel="noopener">Volar</a>. If
+    you need to test your components and web pages, check out
+    <a href="https://www.cypress.io/" target="_blank" rel="noopener">Cypress</a> and
+    <a href="https://on.cypress.io/component" target="_blank">Cypress Component Testing</a>.
+
+    <br />
+
+    More instructions are available in <code>README.md</code>.
+  </WelcomeItem>
+
+  <WelcomeItem>
+    <template #icon>
+      <EcosystemIcon />
+    </template>
+    <template #heading>Ecosystem</template>
+
+    Get official tools and libraries for your project:
+    <a href="https://pinia.vuejs.org/" target="_blank" rel="noopener">Pinia</a>,
+    <a href="https://router.vuejs.org/" target="_blank" rel="noopener">Vue Router</a>,
+    <a href="https://test-utils.vuejs.org/" target="_blank" rel="noopener">Vue Test Utils</a>, and
+    <a href="https://github.com/vuejs/devtools" target="_blank" rel="noopener">Vue Dev Tools</a>. If
+    you need more resources, we suggest paying
+    <a href="https://github.com/vuejs/awesome-vue" target="_blank" rel="noopener">Awesome Vue</a>
+    a visit.
+  </WelcomeItem>
+
+  <WelcomeItem>
+    <template #icon>
+      <CommunityIcon />
+    </template>
+    <template #heading>Community</template>
+
+    Got stuck? Ask your question on
+    <a href="https://chat.vuejs.org" target="_blank" rel="noopener">Vue Land</a>, our official
+    Discord server, or
+    <a href="https://stackoverflow.com/questions/tagged/vue.js" target="_blank" rel="noopener"
+      >StackOverflow</a
+    >. You should also subscribe to
+    <a href="https://news.vuejs.org" target="_blank" rel="noopener">our mailing list</a> and follow
+    the official
+    <a href="https://twitter.com/vuejs" target="_blank" rel="noopener">@vuejs</a>
+    twitter account for latest news in the Vue world.
+  </WelcomeItem>
+
+  <WelcomeItem>
+    <template #icon>
+      <SupportIcon />
+    </template>
+    <template #heading>Support Vue</template>
+
+    As an independent project, Vue relies on community backing for its sustainability. You can help
+    us by
+    <a href="https://vuejs.org/sponsor/" target="_blank" rel="noopener">becoming a sponsor</a>.
+  </WelcomeItem>
+</template>

frontend/src/components/WelcomeItem.vue

@@ -0,0 +1,86 @@
+<template>
+  <div class="item">
+    <i>
+      <slot name="icon"></slot>
+    </i>
+    <div class="details">
+      <h3>
+        <slot name="heading"></slot>
+      </h3>
+      <slot></slot>
+    </div>
+  </div>
+</template>
+
+<style scoped>
+.item {
+  margin-top: 2rem;
+  display: flex;
+}
+
+.details {
+  flex: 1;
+  margin-left: 1rem;
+}
+
+i {
+  display: flex;
+  place-items: center;
+  place-content: center;
+  width: 32px;
+  height: 32px;
+
+  color: var(--color-text);
+}
+
+h3 {
+  font-size: 1.2rem;
+  font-weight: 500;
+  margin-bottom: 0.4rem;
+  color: var(--color-heading);
+}
+
+@media (min-width: 1024px) {
+  .item {
+    margin-top: 0;
+    padding: 0.4rem 0 1rem calc(var(--section-gap) / 2);
+  }
+
+  i {
+    top: calc(50% - 25px);
+    left: -26px;
+    position: absolute;
+    border: 1px solid var(--color-border);
+    background: var(--color-background);
+    border-radius: 8px;
+    width: 50px;
+    height: 50px;
+  }
+
+  .item:before {
+    content: ' ';
+    border-left: 1px solid var(--color-border);
+    position: absolute;
+    left: 0;
+    bottom: calc(50% + 25px);
+    height: calc(50% - 25px);
+  }
+
+  .item:after {
+    content: ' ';
+    border-left: 1px solid var(--color-border);
+    position: absolute;
+    left: 0;
+    top: calc(50% + 25px);
+    height: calc(50% - 25px);
+  }
+
+  .item:first-of-type:before {
+    display: none;
+  }
+
+  .item:last-of-type:after {
+    display: none;
+  }
+}
+</style>

frontend/src/components/icons/IconCommunity.vue

@@ -0,0 +1,7 @@
+<template>
+  <svg xmlns="http://www.w3.org/2000/svg" width="20" height="20" fill="currentColor">
+    <path
+      d="M15 4a1 1 0 1 0 0 2V4zm0 11v-1a1 1 0 0 0-1 1h1zm0 4l-.707.707A1 1 0 0 0 16 19h-1zm-4-4l.707-.707A1 1 0 0 0 11 14v1zm-4.707-1.293a1 1 0 0 0-1.414 1.414l1.414-1.414zm-.707.707l-.707-.707.707.707zM9 11v-1a1 1 0 0 0-.707.293L9 11zm-4 0h1a1 1 0 0 0-1-1v1zm0 4H4a1 1 0 0 0 1.707.707L5 15zm10-9h2V4h-2v2zm2 0a1 1 0 0 1 1 1h2a3 3 0 0 0-3-3v2zm1 1v6h2V7h-2zm0 6a1 1 0 0 1-1 1v2a3 3 0 0 0 3-3h-2zm-1 1h-2v2h2v-2zm-3 1v4h2v-4h-2zm1.707 3.293l-4-4-1.414 1.414 4 4 1.414-1.414zM11 14H7v2h4v-2zm-4 0c-.276 0-.525-.111-.707-.293l-1.414 1.414C5.42 15.663 6.172 16 7 16v-2zm-.707 1.121l3.414-3.414-1.414-1.414-3.414 3.414 1.414 1.414zM9 12h4v-2H9v2zm4 0a3 3 0 0 0 3-3h-2a1 1 0 0 1-1 1v2zm3-3V3h-2v6h2zm0-6a3 3 0 0 0-3-3v2a1 1 0 0 1 1 1h2zm-3-3H3v2h10V0zM3 0a3 3 0 0 0-3 3h2a1 1 0 0 1 1-1V0zM0 3v6h2V3H0zm0 6a3 3 0 0 0 3 3v-2a1 1 0 0 1-1-1H0zm3 3h2v-2H3v2zm1-1v4h2v-4H4zm1.707 4.707l.586-.586-1.414-1.414-.586.586 1.414 1.414z"
+    />
+  </svg>
+</template>

frontend/src/components/icons/IconDocumentation.vue

@@ -0,0 +1,7 @@
+<template>
+  <svg xmlns="http://www.w3.org/2000/svg" width="20" height="17" fill="currentColor">
+    <path
+      d="M11 2.253a1 1 0 1 0-2 0h2zm-2 13a1 1 0 1 0 2 0H9zm.447-12.167a1 1 0 1 0 1.107-1.666L9.447 3.086zM1 2.253L.447 1.42A1 1 0 0 0 0 2.253h1zm0 13H0a1 1 0 0 0 1.553.833L1 15.253zm8.447.833a1 1 0 1 0 1.107-1.666l-1.107 1.666zm0-14.666a1 1 0 1 0 1.107 1.666L9.447 1.42zM19 2.253h1a1 1 0 0 0-.447-.833L19 2.253zm0 13l-.553.833A1 1 0 0 0 20 15.253h-1zm-9.553-.833a1 1 0 1 0 1.107 1.666L9.447 14.42zM9 2.253v13h2v-13H9zm1.553-.833C9.203.523 7.42 0 5.5 0v2c1.572 0 2.961.431 3.947 1.086l1.107-1.666zM5.5 0C3.58 0 1.797.523.447 1.42l1.107 1.666C2.539 2.431 3.928 2 5.5 2V0zM0 2.253v13h2v-13H0zm1.553 13.833C2.539 15.431 3.928 15 5.5 15v-2c-1.92 0-3.703.523-5.053 1.42l1.107 1.666zM5.5 15c1.572 0 2.961.431 3.947 1.086l1.107-1.666C9.203 13.523 7.42 13 5.5 13v2zm5.053-11.914C11.539 2.431 12.928 2 14.5 2V0c-1.92 0-3.703.523-5.053 1.42l1.107 1.666zM14.5 2c1.573 0 2.961.431 3.947 1.086l1.107-1.666C18.203.523 16.421 0 14.5 0v2zm3.5.253v13h2v-13h-2zm1.553 12.167C18.203 13.523 16.421 13 14.5 13v2c1.573 0 2.961.431 3.947 1.086l1.107-1.666zM14.5 13c-1.92 0-3.703.523-5.053 1.42l1.107 1.666C11.539 15.431 12.928 15 14.5 15v-2z"
+    />
+  </svg>
+</template>

frontend/src/components/icons/IconEcosystem.vue

@@ -0,0 +1,7 @@
+<template>
+  <svg xmlns="http://www.w3.org/2000/svg" width="18" height="20" fill="currentColor">
+    <path
+      d="M11.447 8.894a1 1 0 1 0-.894-1.789l.894 1.789zm-2.894-.789a1 1 0 1 0 .894 1.789l-.894-1.789zm0 1.789a1 1 0 1 0 .894-1.789l-.894 1.789zM7.447 7.106a1 1 0 1 0-.894 1.789l.894-1.789zM10 9a1 1 0 1 0-2 0h2zm-2 2.5a1 1 0 1 0 2 0H8zm9.447-5.606a1 1 0 1 0-.894-1.789l.894 1.789zm-2.894-.789a1 1 0 1 0 .894 1.789l-.894-1.789zm2 .789a1 1 0 1 0 .894-1.789l-.894 1.789zm-1.106-2.789a1 1 0 1 0-.894 1.789l.894-1.789zM18 5a1 1 0 1 0-2 0h2zm-2 2.5a1 1 0 1 0 2 0h-2zm-5.447-4.606a1 1 0 1 0 .894-1.789l-.894 1.789zM9 1l.447-.894a1 1 0 0 0-.894 0L9 1zm-2.447.106a1 1 0 1 0 .894 1.789l-.894-1.789zm-6 3a1 1 0 1 0 .894 1.789L.553 4.106zm2.894.789a1 1 0 1 0-.894-1.789l.894 1.789zm-2-.789a1 1 0 1 0-.894 1.789l.894-1.789zm1.106 2.789a1 1 0 1 0 .894-1.789l-.894 1.789zM2 5a1 1 0 1 0-2 0h2zM0 7.5a1 1 0 1 0 2 0H0zm8.553 12.394a1 1 0 1 0 .894-1.789l-.894 1.789zm-1.106-2.789a1 1 0 1 0-.894 1.789l.894-1.789zm1.106 1a1 1 0 1 0 .894 1.789l-.894-1.789zm2.894.789a1 1 0 1 0-.894-1.789l.894 1.789zM8 19a1 1 0 1 0 2 0H8zm2-2.5a1 1 0 1 0-2 0h2zm-7.447.394a1 1 0 1 0 .894-1.789l-.894 1.789zM1 15H0a1 1 0 0 0 .553.894L1 15zm1-2.5a1 1 0 1 0-2 0h2zm12.553 2.606a1 1 0 1 0 .894 1.789l-.894-1.789zM17 15l.447.894A1 1 0 0 0 18 15h-1zm1-2.5a1 1 0 1 0-2 0h2zm-7.447-5.394l-2 1 .894 1.789 2-1-.894-1.789zm-1.106 1l-2-1-.894 1.789 2 1 .894-1.789zM8 9v2.5h2V9H8zm8.553-4.894l-2 1 .894 1.789 2-1-.894-1.789zm.894 0l-2-1-.894 1.789 2 1 .894-1.789zM16 5v2.5h2V5h-2zm-4.553-3.894l-2-1-.894 1.789 2 1 .894-1.789zm-2.894-1l-2 1 .894 1.789 2-1L8.553.106zM1.447 5.894l2-1-.894-1.789-2 1 .894 1.789zm-.894 0l2 1 .894-1.789-2-1-.894 1.789zM0 5v2.5h2V5H0zm9.447 13.106l-2-1-.894 1.789 2 1 .894-1.789zm0 1.789l2-1-.894-1.789-2 1 .894 1.789zM10 19v-2.5H8V19h2zm-6.553-3.894l-2-1-.894 1.789 2 1 .894-1.789zM2 15v-2.5H0V15h2zm13.447 1.894l2-1-.894-1.789-2 1 .894 1.789zM18 15v-2.5h-2V15h2z"
+    />
+  </svg>
+</template>

frontend/src/components/icons/IconSupport.vue

@@ -0,0 +1,7 @@
+<template>
+  <svg xmlns="http://www.w3.org/2000/svg" width="20" height="20" fill="currentColor">
+    <path
+      d="M10 3.22l-.61-.6a5.5 5.5 0 0 0-7.666.105 5.5 5.5 0 0 0-.114 7.665L10 18.78l8.39-8.4a5.5 5.5 0 0 0-.114-7.665 5.5 5.5 0 0 0-7.666-.105l-.61.61z"
+    />
+  </svg>
+</template>

frontend/src/components/icons/IconTooling.vue

@@ -0,0 +1,19 @@
+<!-- This icon is from <https://github.com/Templarian/MaterialDesign>, distributed under Apache 2.0 (https://www.apache.org/licenses/LICENSE-2.0) license-->
+<template>
+  <svg
+    xmlns="http://www.w3.org/2000/svg"
+    xmlns:xlink="http://www.w3.org/1999/xlink"
+    aria-hidden="true"
+    role="img"
+    class="iconify iconify--mdi"
+    width="24"
+    height="24"
+    preserveAspectRatio="xMidYMid meet"
+    viewBox="0 0 24 24"
+  >
+    <path
+      d="M20 18v-4h-3v1h-2v-1H9v1H7v-1H4v4h16M6.33 8l-1.74 4H7v-1h2v1h6v-1h2v1h2.41l-1.74-4H6.33M9 5v1h6V5H9m12.84 7.61c.1.22.16.48.16.8V18c0 .53-.21 1-.6 1.41c-.4.4-.85.59-1.4.59H4c-.55 0-1-.19-1.4-.59C2.21 19 2 18.53 2 18v-4.59c0-.32.06-.58.16-.8L4.5 7.22C4.84 6.41 5.45 6 6.33 6H7V5c0-.55.18-1 .57-1.41C7.96 3.2 8.44 3 9 3h6c.56 0 1.04.2 1.43.59c.39.41.57.86.57 1.41v1h.67c.88 0 1.49.41 1.83 1.22l2.34 5.39z"
+      fill="currentColor"
+    ></path>
+  </svg>
+</template>

frontend/src/layout/LayoutFrame.vue

@@ -0,0 +1,151 @@
+<template>
+  <el-container class="app-wrapper" :class="{ mobile: isMobile }">
+    <div v-show="isMobile && !hideSidebar" class="drawer-bg" @click="hideSidebar = true"></div>
+    <el-aside width="230px" class="sidebar-container" :class="{ 'hide-sidebar': hideSidebar }">
+      <div class="logo-container">
+        <router-link to="/">
+          <img class="sidebar-logo" src="../assets/logo.svg" width="100" alt="logo"/>
+          <h1 class="sidebar-title">SVS SYSTEM</h1>
+        </router-link>
+      </div>
+      <div class="version">v1.0.0</div>
+
+      <SideBar></SideBar>
+    </el-aside>
+    <el-main>
+      <el-button
+        v-show="isMobile"
+        class="menu-button"
+        icon="Fold"
+        @click="hideSidebar = false"
+      ></el-button>
+      <keep-alive>
+        <router-view></router-view>
+      </keep-alive>
+    </el-main>
+  </el-container>
+</template>
+
+<script>
+import SideBar from './SideBar.vue'
+export default {
+  name: 'LayoutFrame',
+  components: {
+    SideBar
+  },
+  data() {
+    return {
+      isMobile: false,
+      hideSidebar: true
+    }
+  },
+  mounted() {
+    window.addEventListener('resize', this.onResize)
+    this.onResize()
+  },
+  beforeUnmount() {
+    window.removeEventListener('resize', this.onResize)
+  },
+  methods: {
+    onResize() {
+      this.isMobile = document.body.clientWidth <= 992
+    }
+  }
+}
+</script>
+
+<style>
+html {
+  font-family: 'Helvetica Neue', Helvetica, 'PingFang SC', 'Hiragino Sans GB', 'Microsoft YaHei',
+    '\5FAE \8F6F \96C5 \9ED1 ', '微软雅黑', Arial, sans-serif;
+}
+
+html,
+body,
+#app,
+.app-wrapper,
+.sidebar-container {
+  height: 100%;
+}
+
+body {
+  margin: 0;
+  background-color: #f6f8fa;
+}
+
+a,
+a:focus,
+a:hover {
+  text-decoration: none;
+}
+
+.drawer-bg {
+  background: #000;
+  opacity: 0.3;
+  width: 100%;
+  top: 0;
+  height: 100%;
+  position: absolute;
+  z-index: 999;
+}
+
+.sidebar-container {
+  background-color: #304156;
+  overflow: hidden;
+}
+
+.app-wrapper.mobile .sidebar-container {
+  position: fixed;
+  top: 0;
+  left: 0;
+  transition-duration: 0.3s;
+  z-index: 1001;
+}
+
+.app-wrapper.mobile .sidebar-container.hide-sidebar {
+  pointer-events: none;
+  transition-duration: 0.3s;
+  transform: translate3d(-230px, 0, 0);
+}
+
+.logo-container {
+  width: 100%;
+  height: 50px;
+  line-height: 50px;
+  background: #2b2f3a;
+  text-align: center;
+}
+
+.sidebar-logo {
+  width: 32px;
+  height: 32px;
+  vertical-align: middle;
+  margin-right: 12px;
+}
+
+.sidebar-title {
+  display: inline-block;
+  margin: 0;
+  color: #fff;
+  font-weight: 600;
+  line-height: 50px;
+  font-size: 14px;
+  font-family: Avenir, Helvetica Neue, Arial, Helvetica, sans-serif;
+  vertical-align: middle;
+}
+
+.sidebar-container .version {
+  height: 30px;
+  background: #2b2f3a;
+  color: #aaa;
+  font-weight: 600;
+  line-height: 30px;
+  font-size: 14px;
+  vertical-align: middle;
+  text-align: center;
+}
+
+.sidebar-container .is-horizontal {
+  display: none;
+}
+</style>

frontend/src/layout/SideBar.vue

@@ -0,0 +1,40 @@
+<template>
+  <el-scrollbar wrap-class="scrollbar-wrapper">
+    <el-menu
+      router
+      text-color="#bfcbd9"
+      active-text-color="rgb(64,158,255)"
+      :default-active="$route.path"
+      background-color="transparent"
+    >
+      <el-menu-item index="/">
+        <el-icon><HomeFilled /></el-icon>首页
+      </el-menu-item>
+      <el-menu-item :index="$router.resolve({ name: 'svc' }).href">
+        <el-icon><Refresh /></el-icon>SVC转换
+      </el-menu-item>
+      <el-menu-item index="/">
+        <el-icon><RefreshRight /></el-icon>DiffSinger生成
+      </el-menu-item>
+      <el-menu-item :index="$router.resolve({ name: 'vm' }).href">
+        <el-icon><EditPen /></el-icon>歌曲音声分离
+      </el-menu-item>
+      <a href="https://github.com/realerikk0/so-vits-svc-webui" target="_blank">
+        <el-menu-item>
+          <el-icon><Share /></el-icon>项目地址
+        </el-menu-item>
+      </a>
+    </el-menu>
+  </el-scrollbar>
+</template>
+
+<script>
+export default {
+  name: 'SideBar'
+}
+</script>
+<style>
+.scrollbar-wrapper .el-menu {
+  border: none;
+}
+</style>

frontend/src/main.ts

@@ -0,0 +1,27 @@
+import { createApp } from 'vue'
+import { createPinia } from 'pinia'
+import ElementPlus from 'element-plus'
+import 'element-plus/dist/index.css'
+import * as ElementPlusIconsVue from '@element-plus/icons-vue'
+import App from './App.vue'
+import router from './router'
+import axios from "axios";
+
+import './assets/main.css'
+
+
+axios.defaults.baseURL = 'http://127.0.0.1:7870' // 这里填写服务器的地址
+axios.defaults.timeout = 10 * 60 * 1000
+
+const app = createApp(App)
+
+let name, comp;
+for ([name, comp] of Object.entries(ElementPlusIconsVue)) {
+  app.component(name, comp);
+}
+
+app.use(createPinia())
+app.use(router)
+app.use(ElementPlus)
+
+app.mount('#app')

frontend/src/router/index.ts

@@ -0,0 +1,30 @@
+import { createRouter, createWebHistory } from 'vue-router'
+import LayoutFrame from '../layout/LayoutFrame.vue'
+import SVCView from "../views/SVCView.vue";
+import HomeView from "../views/HomeView.vue";
+import RMView from "../views/RMView.vue";
+
+const router = createRouter({
+  history: createWebHistory(import.meta.env.BASE_URL),
+  routes: [
+    {
+      path: '/',
+      component: LayoutFrame,
+      children: [
+        { path: '', component: HomeView },
+        { path: 'svc', name:'svc', component: SVCView},
+        { path: 'vm', name: 'vm', component: RMView },
+      ]
+    },
+    {
+      path: '/about',
+      name: 'about',
+      // route level code-splitting
+      // this generates a separate chunk (About.[hash].js) for this route
+      // which is lazy-loaded when the route is visited.
+      component: () => import('../views/AboutView.vue')
+    }
+  ]
+})
+
+export default router

frontend/src/stores/counter.ts

@@ -0,0 +1,12 @@
+import { ref, computed } from 'vue'
+import { defineStore } from 'pinia'
+
+export const useCounterStore = defineStore('counter', () => {
+  const count = ref(0)
+  const doubleCount = computed(() => count.value * 2)
+  function increment() {
+    count.value++
+  }
+
+  return { count, doubleCount, increment }
+})

frontend/src/views/AboutView.vue

@@ -0,0 +1,15 @@
+<template>
+  <div class="about">
+    <h1>This is an about page</h1>
+  </div>
+</template>
+
+<style>
+@media (min-width: 1024px) {
+  .about {
+    min-height: 100vh;
+    display: flex;
+    align-items: center;
+  }
+}
+</style>

frontend/src/views/HomeView.vue

@@ -0,0 +1,10 @@
+<script setup lang="ts">
+// import TheWelcome from '../components/TheWelcome.vue'
+</script>
+
+<template>
+  <main>
+<!--    <TheWelcome />-->
+    Hi from Lilyn
+  </main>
+</template>

frontend/src/views/RMView.vue

@@ -0,0 +1,134 @@
+<template>
+  <div class="svc-container">
+    <div class="svc-wrapper">
+      <div class="form-panel single-run">
+        <h1 class="form-title">歌曲音声分离</h1>
+        <h3 class="model-tips">上传歌曲，运行可下载人声（vocals.wav）与背景音乐（accompaniment.wav）</h3>
+        <el-form class="svc-form single-run-form" :model="singleForm" label-width="150px">
+          <el-upload
+              ref="audioSingleUpload"
+              class="audio-upload"
+              action=""
+              accept=".wav,.mp3,.flac"
+              :http-request="handleSingleUpload"
+          >
+            <template #trigger>
+              <el-button type="primary" v-loading="isRuningSingle">选择音频文件并开始转换！</el-button>
+            </template>
+
+            <template #tip>
+              <div class="el-upload__tip">
+                需要是wav或者mp3文件哦
+              </div>
+            </template>
+          </el-upload>
+        </el-form>
+      </div>
+
+    </div>
+
+<!--    <GreetingAudio :title="audioTitle" :src="audioSrc" v-if="audioLoaded"></GreetingAudio>-->
+  </div>
+</template>
+
+<script>
+import axios from "axios";
+import JSZip from "jszip";
+import GreetingAudio from "@/components/GreetingAudio.vue";
+
+export default {
+  name: 'RMView',
+  components: {GreetingAudio},
+  data() {
+    return {
+      singleForm: {
+        srcaudio: null,
+      },
+      isRuningSingle: false,
+    }
+  },
+  mounted() {
+  },
+  methods: {
+    async handleSingleUpload(file) {
+      try {
+        this.isRuningSingle = true
+        console.log("HANDLE UPLOAD")
+        console.log(file)
+        let srcaudio = file.file
+        if (srcaudio) {
+          console.log(srcaudio)
+          let runData = new FormData()
+          runData.append("srcaudio", srcaudio)
+
+          let resp = await axios.post('/api/vm/run', runData, {
+            responseType: 'arraybuffer'
+          })
+          if (resp.status === 200) {
+            const zipBlob = new Blob([resp.data], { type: 'application/zip' });
+
+            // Create a temporary link element to trigger the download
+            const link = document.createElement('a');
+            link.href = URL.createObjectURL(zipBlob);
+            link.download = 'output.zip';
+
+            // Trigger the download
+            document.body.appendChild(link);
+            link.click();
+            document.body.removeChild(link);
+
+            this.isRuningSingle = false
+          } else {
+            this.$message.error('Failed to load model: ' + resp.data.msg)
+            this.isRuningSingle = false
+          }
+        } else {
+          this.$message.error('Error unable to get audio files')
+          this.isRuningSingle = false
+        }
+      } catch (e) {
+        this.$message.error('Failed to run: ' + e)
+      } finally {
+        this.isRuningSingle = false
+      }
+    },
+    getFileURL(file) {
+      // Create a blob URL for the file
+      const blob = new Blob([file], { type: 'audio/wav' })
+      return URL.createObjectURL(blob)
+    }
+  }
+}
+</script>
+
+<style scoped>
+.svc-container {
+  height: 100%;
+  width: 100%;
+}
+
+.svc-wrapper {
+  top: 60px;
+  display: flex;
+  flex-direction: column;
+  justify-content: center;
+  align-items: center;
+  /*background-color: #ccc;*/
+}
+
+.svc-form {
+  max-width: 460px;
+}
+
+.svc-form el-alert {
+  margin: 10px auto;
+}
+
+.svc-form el-form-item {
+  margin-top: 10px;
+}
+
+.form-title {
+  margin: 20px auto;
+}
+</style>

frontend/src/views/SVCView.vue

@@ -0,0 +1,320 @@
+<template>
+  <div class="svc-container">
+    <div class="svc-wrapper">
+      <div class="form-panel">
+        <h1 class="form-title">基本设置</h1>
+        <el-form class="svc-form" :model="initForm" label-width="150px">
+          <el-alert type="info" show-icon :closable="false">
+            单个文件处理需要提供音频文件，输出会是单个音频文件； <br>
+            批量处理支持上传多个音频文件，输出会是一个zip压缩包。
+          </el-alert>
+          <el-form-item label="运行模式" required>
+            <el-select v-model="initForm.mode" placeholder="选择运行模式" default-first-option=default-first-option>
+              <el-option label="单个处理" value="single"></el-option>
+              <el-option label="批量处理" value="batch"></el-option>
+            </el-select>
+          </el-form-item>
+
+          <el-alert type="info" show-icon :closable="false">
+            运行设备，默认选择cuda，即GPU计算；如果没有支持的GPU设备可以选择cpu。
+          </el-alert>
+          <el-form-item label="计算设备" required>
+            <el-select v-model="initForm.device" placeholder="选择计算设备" default-first-option="default-first-option">
+              <el-option label="GPU(cuda)" value="cuda"></el-option>
+              <el-option label="CPU" value="cpu"></el-option>
+            </el-select>
+          </el-form-item>
+
+          <el-alert type="info" show-icon :closable="false">
+            选择一个语音模型
+          </el-alert>
+          <el-form-item label="语音模型" required>
+            <el-select v-model="initForm.model" placeholder="选择语音模型">
+              <el-option
+                  v-for="modelName in this.models"
+                  :key="modelName"
+                  :label="modelName"
+                  :value="modelName"
+              />
+            </el-select>
+          </el-form-item>
+
+          <el-button type="primary" @click="loadModel" v-loading="isLoadingModel">加载模型</el-button>
+        </el-form>
+      </div>
+
+      <el-divider v-if="displaySVCForm" />
+
+      <div class="form-panel single-run" v-if="displaySingleSVCForm">
+        <h1 class="form-title">制作一个歌曲。</h1>
+        <h3 class="model-tips">你使用的语音模型是 {{initForm.model}}</h3>
+        <el-form class="svc-form single-run-form" :model="singleForm" label-width="150px">
+          <el-upload
+              ref="audioSingleUpload"
+              class="audio-upload"
+              action=""
+              accept=".wav,.mp3"
+              :http-request="handleSingleUpload"
+          >
+            <template #trigger>
+              <el-button type="primary" v-loading="isRuningSingle">选择音频文件并开始制作！</el-button>
+            </template>
+
+            <template #tip>
+              <div class="el-upload__tip">
+                需要是wav文件哦
+              </div>
+            </template>
+          </el-upload>
+        </el-form>
+      </div>
+
+      <div class="form-panel batch-run" v-if="displayBatchSVCForm">
+        <h1 class="form-title">制作多个歌曲。</h1>
+        <h3 class="model-tips">你使用的语音模型是 {{initForm.model}}</h3>
+        <el-form class="svc-form batch-run-form" :model="batchForm" label-width="150px">
+          <el-upload
+              ref="audioBatchUpload"
+              class="audio-upload"
+              action=""
+              accept=".wav,.mp3"
+              :http-request="mergeBatchFiles"
+              multiple
+          >
+            <template #trigger>
+              <el-button type="primary">选择音频文件</el-button>
+            </template>
+
+            <el-button type="warning" v-loading="isRunningBatch" @click="handleBatchUpload">开始制作！</el-button>
+
+            <template #tip>
+              <div class="el-upload__tip">
+                需要是wav文件哦
+              </div>
+            </template>
+          </el-upload>
+        </el-form>
+      </div>
+
+    </div>
+
+    <GreetingAudio :title="audioTitle" :src="audioSrc" v-if="audioLoaded"></GreetingAudio>
+  </div>
+</template>
+
+<script>
+import axios from "axios";
+import JSZip from "jszip";
+import GreetingAudio from "@/components/GreetingAudio.vue";
+
+export default {
+  name: 'SVCView',
+  components: {GreetingAudio},
+  data() {
+    return {
+      models: [],
+      initForm: {
+        mode: '',
+        model: '',
+        device: '',
+      },
+      singleForm: {
+        dsid: '',
+        srcaudio: null,
+      },
+      batchForm: {
+        dsid: '',
+        srcaudio: [],
+      },
+      displaySVCForm: false,
+      displaySingleSVCForm: false,
+      displayBatchSVCForm: false,
+      isLoadingModel: false,
+      isRuningSingle: false,
+      isRunningBatch: false,
+      audioLoaded: false,
+      audioTitle: '',
+      audioSrc: '',
+      selectedFiles: []
+    }
+  },
+  mounted() {
+    this.getModelLists()
+  },
+  methods: {
+    axios,
+    async getModelLists() {
+      try {
+        let resp = (await axios.get('/api/svc/model')).data
+        if (resp.code === 200) {
+          this.models = resp.data
+          console.log(this.models)
+        } else {
+          this.$message.error('Failed to fetch model information: ' + resp.msg)
+        }
+      } catch (e) {
+        this.$message.error('Failed to fetch model information: ' + e)
+      }
+    },
+    async loadModel() {
+      try {
+        this.audioLoaded = false
+        this.selectedFiles = []
+        this.isLoadingModel = true
+        let initFormData = new FormData()
+        initFormData.append("mode", this.initForm.mode)
+        initFormData.append("device", this.initForm.device)
+        initFormData.append("model", this.initForm.model)
+        if (this.initForm.mode === "" || this.initForm.model === "" || this.initForm.device === "") {
+          this.$message.error('都选一下。')
+          return
+        }
+        let resp = (await axios.post('/api/svc/switch', initFormData)).data
+        if (resp.code === 200) {
+          this.displaySVCForm = true
+          console.log(resp.data.mode)
+          if (resp.data.mode === "single") {
+            this.displaySingleSVCForm = true
+            this.displayBatchSVCForm = false
+          } else if (resp.data.mode === "batch") {
+            this.displaySingleSVCForm = false
+            this.displayBatchSVCForm = true
+          }
+        } else {
+          this.$message.error('Failed to load model: ' + resp.msg)
+        }
+      } catch (e) {
+        this.$message.error('Failed to load model: ' + e)
+      } finally {
+        this.isLoadingModel = false
+      }
+    },
+    async handleSingleUpload(file) {
+      try {
+        this.isRuningSingle = true
+        this.isLoadingModel = true
+        console.log("HANDLE UPLOAD")
+        console.log(file)
+        let srcaudio = file.file
+        if (srcaudio) {
+          console.log(srcaudio)
+          let audioFileName = srcaudio.name
+          let runData = new FormData()
+          runData.append("srcaudio", srcaudio)
+          runData.append("dsid", this.initForm.model)
+
+          let resp = await axios.post('/api/svc/run', runData, {
+            responseType: 'arraybuffer'
+          })
+          if (resp.status === 200) {
+            const audioData = resp.data
+            if (audioData) {
+              const audioBlob = new Blob([audioData], { type: 'audio/wav' });
+              const audioUrl = URL.createObjectURL(audioBlob);
+
+              this.audioLoaded = true
+              this.audioSrc = audioUrl
+              this.audioTitle = audioFileName
+            }
+          } else {
+            this.$message.error('Failed to load model: ' + resp.data.msg)
+            this.isRuningSingle = false
+            this.isLoadingModel = false
+          }
+        } else {
+          this.$message.error('Error unable to get audio file')
+          this.isRuningSingle = false
+          this.isLoadingModel = false
+        }
+      } catch (e) {
+        this.$message.error('Failed to run: ' + e)
+      } finally {
+        this.isRuningSingle = false
+        this.isLoadingModel = false
+      }
+    },
+    mergeBatchFiles(file) {
+      this.selectedFiles.push(file.file)
+    },
+    async handleBatchUpload() {
+      try {
+        this.isRunningBatch = true
+        this.isLoadingModel = true
+
+        const audioFiles = this.selectedFiles
+        if (audioFiles.length > 0) {
+          let runData = new FormData()
+          // runData.append('srcaudio', audioFiles)
+          for (let i = 0; i < audioFiles.length; i++) {
+            runData.append('srcaudio', audioFiles[i])
+          }
+          runData.append("dsid", this.initForm.model)
+
+          let resp = await axios.post('/api/svc/batch', runData, {
+            responseType: 'arraybuffer'
+          })
+          if (resp.status === 200) {
+            const zipBlob = new Blob([resp.data], { type: 'application/zip' });
+
+            // Create a temporary link element to trigger the download
+            const link = document.createElement('a');
+            link.href = URL.createObjectURL(zipBlob);
+            link.download = 'output.zip';
+
+            // Trigger the download
+            document.body.appendChild(link);
+            link.click();
+            document.body.removeChild(link);
+
+          } else {
+            this.$message.error('Failed to load model: ' + resp.data.msg)
+            this.isRunningBatch = false
+            this.isLoadingModel = false
+          }
+        } else {
+          this.$message.error('Error unable to get audio file')
+          this.isRunningBatch = false
+          this.isLoadingModel = false
+        }
+      } catch (e) {
+        this.$message.error('Failed to run: ' + e)
+      } finally {
+        this.isRunningBatch = false
+        this.isLoadingModel = false
+      }
+    },
+  }
+}
+</script>
+
+<style scoped>
+.svc-container {
+  height: 100%;
+  width: 100%;
+}
+
+.svc-wrapper {
+  top: 60px;
+  display: flex;
+  flex-direction: column;
+  justify-content: center;
+  align-items: center;
+  /*background-color: #ccc;*/
+}
+
+.svc-form {
+  max-width: 460px;
+}
+
+.svc-form el-alert {
+  margin: 10px auto;
+}
+
+.svc-form el-form-item {
+  margin-top: 10px;
+}
+
+.form-title {
+  margin: 20px auto;
+}
+</style>

frontend/tsconfig.app.json

@@ -0,0 +1,14 @@
+{
+  "extends": "@vue/tsconfig/tsconfig.web.json",
+  "include": [
+    "env.d.ts", "src/**/*", "src/**/*.vue"],
+  "exclude": ["src/**/__tests__/*"],
+  "compilerOptions": {
+    "composite": true,
+    "baseUrl": "./lilyn-svs",
+    "allowJs": true,
+    "paths": {
+      "@/*": ["./src/*"]
+    }
+  }
+}

frontend/tsconfig.json

@@ -0,0 +1,14 @@
+{
+  "files": [],
+  "references": [
+    {
+      "path": "./tsconfig.node.json"
+    },
+    {
+      "path": "./tsconfig.app.json"
+    },
+    {
+      "path": "./tsconfig.vitest.json"
+    }
+  ]
+}

frontend/tsconfig.node.json

@@ -0,0 +1,9 @@
+{
+  "extends": "@vue/tsconfig/tsconfig.node.json",
+  "include": ["vite.config.*", "vitest.config.*", "cypress.config.*", "playwright.config.*"],
+  "compilerOptions": {
+    "composite": true,
+    "types": ["node"],
+    "allowJs": true
+  }
+}

frontend/tsconfig.vitest.json

@@ -0,0 +1,10 @@
+{
+  "extends": "./tsconfig.app.json",
+  "exclude": [],
+  "compilerOptions": {
+    "composite": true,
+    "lib": [],
+    "types": ["node", "jsdom"],
+    "allowJs": true
+  }
+}

frontend/vite.config.ts

@@ -0,0 +1,14 @@
+import { fileURLToPath, URL } from 'node:url'
+
+import { defineConfig } from 'vite'
+import vue from '@vitejs/plugin-vue'
+
+// https://vitejs.dev/config/
+export default defineConfig({
+  plugins: [vue()],
+  resolve: {
+    alias: {
+      '@': fileURLToPath(new URL('./src', import.meta.url))
+    }
+  }
+})

frontend/vitest.config.ts

@@ -0,0 +1,15 @@
+import { fileURLToPath } from 'node:url'
+import { mergeConfig } from 'vite'
+import { configDefaults, defineConfig } from 'vitest/config'
+import viteConfig from './vite.config'
+
+export default mergeConfig(
+  viteConfig,
+  defineConfig({
+    test: {
+      environment: 'jsdom',
+      exclude: [...configDefaults.exclude, 'e2e/*'],
+      root: fileURLToPath(new URL('./', import.meta.url))
+    }
+  })
+)

hubert/hubert_model.py

@@ -0,0 +1,222 @@
+import copy
+import random
+from typing import Optional, Tuple
+
+import torch
+import torch.nn as nn
+import torch.nn.functional as t_func
+from torch.nn.modules.utils import consume_prefix_in_state_dict_if_present
+
+
+class Hubert(nn.Module):
+    def __init__(self, num_label_embeddings: int = 100, mask: bool = True):
+        super().__init__()
+        self._mask = mask
+        self.feature_extractor = FeatureExtractor()
+        self.feature_projection = FeatureProjection()
+        self.positional_embedding = PositionalConvEmbedding()
+        self.norm = nn.LayerNorm(768)
+        self.dropout = nn.Dropout(0.1)
+        self.encoder = TransformerEncoder(
+            nn.TransformerEncoderLayer(
+                768, 12, 3072, activation="gelu", batch_first=True
+            ),
+            12,
+        )
+        self.proj = nn.Linear(768, 256)
+
+        self.masked_spec_embed = nn.Parameter(torch.FloatTensor(768).uniform_())
+        self.label_embedding = nn.Embedding(num_label_embeddings, 256)
+
+    def mask(self, x: torch.Tensor) -> Tuple[torch.Tensor, torch.Tensor]:
+        mask = None
+        if self.training and self._mask:
+            mask = _compute_mask((x.size(0), x.size(1)), 0.8, 10, x.device, 2)
+            x[mask] = self.masked_spec_embed.to(x.dtype)
+        return x, mask
+
+    def encode(
+            self, x: torch.Tensor, layer: Optional[int] = None
+    ) -> Tuple[torch.Tensor, torch.Tensor]:
+        x = self.feature_extractor(x)
+        x = self.feature_projection(x.transpose(1, 2))
+        x, mask = self.mask(x)
+        x = x + self.positional_embedding(x)
+        x = self.dropout(self.norm(x))
+        x = self.encoder(x, output_layer=layer)
+        return x, mask
+
+    def logits(self, x: torch.Tensor) -> torch.Tensor:
+        logits = torch.cosine_similarity(
+            x.unsqueeze(2),
+            self.label_embedding.weight.unsqueeze(0).unsqueeze(0),
+            dim=-1,
+        )
+        return logits / 0.1
+
+    def forward(self, x: torch.Tensor) -> Tuple[torch.Tensor, torch.Tensor]:
+        x, mask = self.encode(x)
+        x = self.proj(x)
+        logits = self.logits(x)
+        return logits, mask
+
+
+class HubertSoft(Hubert):
+    def __init__(self):
+        super().__init__()
+
+    @torch.inference_mode()
+    def units(self, wav: torch.Tensor) -> torch.Tensor:
+        wav = t_func.pad(wav, ((400 - 320) // 2, (400 - 320) // 2))
+        x, _ = self.encode(wav)
+        return self.proj(x)
+
+
+class FeatureExtractor(nn.Module):
+    def __init__(self):
+        super().__init__()
+        self.conv0 = nn.Conv1d(1, 512, 10, 5, bias=False)
+        self.norm0 = nn.GroupNorm(512, 512)
+        self.conv1 = nn.Conv1d(512, 512, 3, 2, bias=False)
+        self.conv2 = nn.Conv1d(512, 512, 3, 2, bias=False)
+        self.conv3 = nn.Conv1d(512, 512, 3, 2, bias=False)
+        self.conv4 = nn.Conv1d(512, 512, 3, 2, bias=False)
+        self.conv5 = nn.Conv1d(512, 512, 2, 2, bias=False)
+        self.conv6 = nn.Conv1d(512, 512, 2, 2, bias=False)
+
+    def forward(self, x: torch.Tensor) -> torch.Tensor:
+        x = t_func.gelu(self.norm0(self.conv0(x)))
+        x = t_func.gelu(self.conv1(x))
+        x = t_func.gelu(self.conv2(x))
+        x = t_func.gelu(self.conv3(x))
+        x = t_func.gelu(self.conv4(x))
+        x = t_func.gelu(self.conv5(x))
+        x = t_func.gelu(self.conv6(x))
+        return x
+
+
+class FeatureProjection(nn.Module):
+    def __init__(self):
+        super().__init__()
+        self.norm = nn.LayerNorm(512)
+        self.projection = nn.Linear(512, 768)
+        self.dropout = nn.Dropout(0.1)
+
+    def forward(self, x: torch.Tensor) -> torch.Tensor:
+        x = self.norm(x)
+        x = self.projection(x)
+        x = self.dropout(x)
+        return x
+
+
+class PositionalConvEmbedding(nn.Module):
+    def __init__(self):
+        super().__init__()
+        self.conv = nn.Conv1d(
+            768,
+            768,
+            kernel_size=128,
+            padding=128 // 2,
+            groups=16,
+        )
+        self.conv = nn.utils.weight_norm(self.conv, name="weight", dim=2)
+
+    def forward(self, x: torch.Tensor) -> torch.Tensor:
+        x = self.conv(x.transpose(1, 2))
+        x = t_func.gelu(x[:, :, :-1])
+        return x.transpose(1, 2)
+
+
+class TransformerEncoder(nn.Module):
+    def __init__(
+            self, encoder_layer: nn.TransformerEncoderLayer, num_layers: int
+    ) -> None:
+        super(TransformerEncoder, self).__init__()
+        self.layers = nn.ModuleList(
+            [copy.deepcopy(encoder_layer) for _ in range(num_layers)]
+        )
+        self.num_layers = num_layers
+
+    def forward(
+            self,
+            src: torch.Tensor,
+            mask: torch.Tensor = None,
+            src_key_padding_mask: torch.Tensor = None,
+            output_layer: Optional[int] = None,
+    ) -> torch.Tensor:
+        output = src
+        for layer in self.layers[:output_layer]:
+            output = layer(
+                output, src_mask=mask, src_key_padding_mask=src_key_padding_mask
+            )
+        return output
+
+
+def _compute_mask(
+        shape: Tuple[int, int],
+        mask_prob: float,
+        mask_length: int,
+        device: torch.device,
+        min_masks: int = 0,
+) -> torch.Tensor:
+    batch_size, sequence_length = shape
+
+    if mask_length < 1:
+        raise ValueError("`mask_length` has to be bigger than 0.")
+
+    if mask_length > sequence_length:
+        raise ValueError(
+            f"`mask_length` has to be smaller than `sequence_length`, but got `mask_length`: {mask_length} and `sequence_length`: {sequence_length}`"
+        )
+
+    # compute number of masked spans in batch
+    num_masked_spans = int(mask_prob * sequence_length / mask_length + random.random())
+    num_masked_spans = max(num_masked_spans, min_masks)
+
+    # make sure num masked indices <= sequence_length
+    if num_masked_spans * mask_length > sequence_length:
+        num_masked_spans = sequence_length // mask_length
+
+    # SpecAugment mask to fill
+    mask = torch.zeros((batch_size, sequence_length), device=device, dtype=torch.bool)
+
+    # uniform distribution to sample from, make sure that offset samples are < sequence_length
+    uniform_dist = torch.ones(
+        (batch_size, sequence_length - (mask_length - 1)), device=device
+    )
+
+    # get random indices to mask
+    mask_indices = torch.multinomial(uniform_dist, num_masked_spans)
+
+    # expand masked indices to masked spans
+    mask_indices = (
+        mask_indices.unsqueeze(dim=-1)
+        .expand((batch_size, num_masked_spans, mask_length))
+        .reshape(batch_size, num_masked_spans * mask_length)
+    )
+    offsets = (
+        torch.arange(mask_length, device=device)[None, None, :]
+        .expand((batch_size, num_masked_spans, mask_length))
+        .reshape(batch_size, num_masked_spans * mask_length)
+    )
+    mask_idxs = mask_indices + offsets
+
+    # scatter indices to mask
+    mask = mask.scatter(1, mask_idxs, True)
+
+    return mask
+
+
+def hubert_soft(
+        path: str,
+) -> HubertSoft:
+    r"""HuBERT-Soft from `"A Comparison of Discrete and Soft Speech Units for Improved Voice Conversion"`.
+    Args:
+        path (str): path of a pretrained model
+    """
+    hubert = HubertSoft()
+    checkpoint = torch.load(path)
+    consume_prefix_in_state_dict_if_present(checkpoint, "module.")
+    hubert.load_state_dict(checkpoint)
+    hubert.eval()
+    return hubert