voice-changer/MMVCTrainerFrontendDemo.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "gpuClass": "standard",
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/w-okada/voice-changer/blob/master/MMVCTrainerFrontendDemo.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# このノートブックは管理されていません。\n",
        "# VCClientをColabで使用する場合は、次のノートブックをご使用ください。\n",
        "\n",
        "# This notebook is not being managed.\n",
        "# If you're using VCClient in Colab, please use the following notebook.\n",
        "\n",
        "https://github.com/w-okada/voice-changer/blob/master/Realtime_Voice_Changer_on_Colab.ipynb\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "_41LkcbiwUFK"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Voice Changer Simple (デモ版)\n",
        "---\n",
        "\n",
        "このノートはVoice ChangerをColab上で動かすデモ版です。\n",
        "\n",
        "正式版はローカルPCのDocker上で動かすアプリケーションです。\n",
        "\n",
        "正式版は、多くの場合より少ないタイムラグで滑らかに音声を変換できます。\n",
        "\n",
        "詳細な使用方法はこちらの[リポジトリ](https://github.com/w-okada/voice-changer)からご確認ください。\n"
      ],
      "metadata": {
        "id": "Lbbmx_Vjl0zo"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# GPUを確認\n",
        "GPUを用いたほうが高速に処理が行えます。\n",
        "\n",
        "下記のコマンドでGPUが確認できない場合は、上のメニューから\n",
        "\n",
        "「ランタイム」→「ランタイムの変更」→「ハードウェア アクセラレータ」\n",
        "\n",
        "でGPUを選択してください。"
      ],
      "metadata": {
        "id": "oUKi1NYMmXrr"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# (1) GPUの確認\n",
        "!nvidia-smi"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vV1t7PBRm-o6",
        "outputId": "4f159c80-8114-4732-f5af-0856f7b5c39a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Sat Dec 10 23:45:44 2022       \n",
            "+-----------------------------------------------------------------------------+\n",
            "| NVIDIA-SMI 460.32.03    Driver Version: 460.32.03    CUDA Version: 11.2     |\n",
            "|-------------------------------+----------------------+----------------------+\n",
            "| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |\n",
            "| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |\n",
            "|                               |                      |               MIG M. |\n",
            "|===============================+======================+======================|\n",
            "|   0  Tesla T4            Off  | 00000000:00:04.0 Off |                    0 |\n",
            "| N/A   70C    P0    31W /  70W |      0MiB / 15109MiB |      0%      Default |\n",
            "|                               |                      |                  N/A |\n",
            "+-------------------------------+----------------------+----------------------+\n",
            "                                                                               \n",
            "+-----------------------------------------------------------------------------+\n",
            "| Processes:                                                                  |\n",
            "|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |\n",
            "|        ID   ID                                                   Usage      |\n",
            "|=============================================================================|\n",
            "|  No running processes found                                                 |\n",
            "+-----------------------------------------------------------------------------+\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# リポジトリのクローン\n",
        "リポジトリをクローンします"
      ],
      "metadata": {
        "id": "sLBfykjBnjWc"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# (2) リポジトリのクローン\n",
        "!git clone --depth 1 https://github.com/w-okada/voice-changer.git -b dev\n",
        "%cd voice-changer/demo/\n",
        "\n",
        "!cp ../template/setting_mmvc_colab.json ../frontend/dist/assets/setting.json"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "86wTFmqsNMnD",
        "outputId": "3f84319c-0365-442a-fa3a-0a8aea701926"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Cloning into 'voice-changer'...\n",
            "remote: Enumerating objects: 1029, done.\u001b[K\n",
            "remote: Counting objects: 100% (1029/1029), done.\u001b[K\n",
            "remote: Compressing objects: 100% (919/919), done.\u001b[K\n",
            "remote: Total 1029 (delta 21), reused 979 (delta 10), pack-reused 0\u001b[K\n",
            "Receiving objects: 100% (1029/1029), 71.87 MiB | 26.18 MiB/s, done.\n",
            "Resolving deltas: 100% (21/21), done.\n",
            "/content/voice-changer/demo\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# モジュールのインストール\n",
        "\n",
        "必要なモジュールをインストールします。"
      ],
      "metadata": {
        "id": "8Na2PbLZSWgZ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# (3) 設定ファイルの確認\n",
        "!apt-get install -y espeak libsndfile1-dev &> /dev/null\n",
        "!pip install unidecode &> /dev/null\n",
        "!pip install phonemizer &> /dev/null\n",
        "!pip install retry &> /dev/null\n",
        "!pip install python-socketio &> /dev/null\n",
        "!pip install fastapi &> /dev/null\n",
        "!pip install python-multipart &> /dev/null\n",
        "!pip install uvicorn &> /dev/null\n",
        "!pip install websockets &> /dev/null\n",
        "!pip install pyOpenSSL &> /dev/null\n",
        "!pip install pyopenjtalk==0.2.0 &> /dev/null\n",
        "\n",
        "%cd MMVC_Trainer/monotonic_align/\n",
        "!python setup.py build_ext --inplace\n",
        "%cd ../../"
      ],
      "metadata": {
        "id": "LwZAAuqxX7yY",
        "outputId": "61526e29-97d9-4975-e921-4ca9ae5a153f",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/voice-changer/demo/MMVC_Trainer/monotonic_align\n",
            "running build_ext\n",
            "building 'monotonic_align.core' extension\n",
            "creating build\n",
            "creating build/temp.linux-x86_64-3.8\n",
            "x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -g -fwrapv -O2 -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/local/lib/python3.8/dist-packages/numpy/core/include -I/usr/include/python3.8 -c core.c -o build/temp.linux-x86_64-3.8/core.o\n",
            "x86_64-linux-gnu-gcc -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-Bsymbolic-functions -g -fwrapv -O2 -Wl,-Bsymbolic-functions -g -fwrapv -O2 -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-3.8/core.o -o /content/voice-changer/demo/MMVC_Trainer/monotonic_align/monotonic_align/core.cpython-38-x86_64-linux-gnu.so\n",
            "/content/voice-changer/demo\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# サーバの起動\n",
        "\n",
        "サーバを起動します。(4-1)\n",
        "\n",
        "サーバの起動状況を確認します。(4-2)\n",
        "\n",
        "このセルは繰り返し実行することになるのでCtrl+Retでセルを実行してください。\n",
        "\n",
        "下記のようなテキストが表示されたら起動完了です。\n",
        "\n",
        "**`DEBUG:asyncio:Using selector: EpollSelector`**\n",
        "\n",
        "```\n",
        "    Phase name:__main__\n",
        "    PHASE3:__main__\n",
        "    PHASE1:__main__\n",
        "Start MMVC SocketIO Server\n",
        "    CONFIG:None, MODEL:None\n",
        "DEBUG:asyncio:Using selector: EpollSelector\n",
        "```\n",
        "\n"
      ],
      "metadata": {
        "id": "-_2OcN9Borke"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# (4-1) サーバの起動\n",
        "import random\n",
        "PORT = 10000 + random.randint(1, 9999)\n",
        "LOG_FILE = f\"LOG_FILE_{PORT}\"\n",
        "\n",
        "get_ipython().system_raw(f'python3 MMVCServerSIO.py -p {PORT} --colab True >{LOG_FILE} 2>&1 &')\n",
        "#print(f\"PORT:{PORT}, LOG_FILE:{LOG_FILE}\")"
      ],
      "metadata": {
        "id": "G-nMdPxEW1rc"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# (4-2) サーバの起動確認\n",
        "!sleep 5\n",
        "!tail -20 {LOG_FILE}"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "chu06KpAjEK6",
        "outputId": "51b4979c-91b7-4c95-eb4b-40ea001042a9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[32m    Phase name:__main__\u001b[0m\n",
            "\u001b[32m    PHASE3:__main__\u001b[0m\n",
            "\u001b[32m    PHASE1:__main__\u001b[0m\n",
            "\u001b[17mStart MMVC SocketIO Server\u001b[0m\n",
            "\u001b[34m    CONFIG:None, MODEL:None\u001b[0m\n",
            "DEBUG:asyncio:Using selector: EpollSelector\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# プロキシを起動\n",
        "ウェブサーバへのアクセスをするためのプロキシを起動します。\n",
        "\n",
        "表示されたURLをクリックして開くと別タブでアプリが開きます。\n",
        "\n",
        "Colabなので、ロードにある程度時間がかかります(30秒くらい)。"
      ],
      "metadata": {
        "id": "WhxcFLQEpctq"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# (5) プロキシを起動\n",
        "from google.colab.output import eval_js\n",
        "proxy = eval_js( \"google.colab.kernel.proxyPort(\" + str(PORT) + \")\" )\n",
        "print(f\"{proxy}trainer/\")"
      ],
      "metadata": {
        "id": "nkRjZm95l87C",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "bcca9fae-642c-42f6-f3a5-a8bb0789090f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "https://vljlzcgk39q-496ff2e9c6d22116-17357-colab.googleusercontent.com/trainer/\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "s1aWiBg-cTle"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}