voice-changer/VoiceChangerDemo_Simple.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyMeMGMfscotyaoFPcXG8qRY",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU",
    "gpuClass": "standard"
  },
  "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/dev/VoiceChangerDemo_Simple.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "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": "8e212991-8ca0-45bc-c632-40a707e9668e"
      },
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Thu Nov  3 21:54:01 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   42C    P0    25W /  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/isletennos/MMVC_Trainer.git -b v1.3.1.3 /MMVC_Trainer\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": "a269932d-20e1-4fa0-ce86-00d231d169bd"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Cloning into '/MMVC_Trainer'...\n",
            "remote: Enumerating objects: 917, done.\u001b[K\n",
            "remote: Counting objects: 100% (917/917), done.\u001b[K\n",
            "remote: Compressing objects: 100% (828/828), done.\u001b[K\n",
            "remote: Total 917 (delta 3), reused 888 (delta 0), pack-reused 0\u001b[K\n",
            "Receiving objects: 100% (917/917), 53.02 MiB | 16.78 MiB/s, done.\n",
            "Resolving deltas: 100% (3/3), done.\n",
            "Note: checking out '39723b3243e0265b8802e020e4d4d90a4b8b65ee'.\n",
            "\n",
            "You are in 'detached HEAD' state. You can look around, make experimental\n",
            "changes and commit them, and you can discard any commits you make in this\n",
            "state without impacting any branches by performing another checkout.\n",
            "\n",
            "If you want to create a new branch to retain commits you create, you may\n",
            "do so (now or later) by using -b with the checkout command again. Example:\n",
            "\n",
            "  git checkout -b <new-branch-name>\n",
            "\n",
            "Cloning into 'voice-changer'...\n",
            "remote: Enumerating objects: 91, done.\u001b[K\n",
            "remote: Counting objects: 100% (91/91), done.\u001b[K\n",
            "remote: Compressing objects: 100% (79/79), done.\u001b[K\n",
            "remote: Total 91 (delta 12), reused 55 (delta 4), pack-reused 0\u001b[K\n",
            "Unpacking objects: 100% (91/91), 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"
      ],
      "metadata": {
        "id": "LwZAAuqxX7yY"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "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": 4,
      "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": "a1b039dc-8f47-44f4-fb02-be29f26468fd"
      },
      "execution_count": 7,
      "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}front/\")"
      ],
      "metadata": {
        "id": "nkRjZm95l87C",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "37531763-2abd-49e4-d2b7-0a301b9923de"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "https://s1ib44uhknk-496ff2e9c6d22116-19907-colab.googleusercontent.com/front/\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "axkt5BjhoiPV"
      },
      "execution_count": 6,
      "outputs": []
    }
  ]
}