mirror of
https://github.com/w-okada/voice-changer.git
synced 2025-01-23 13:35:12 +03:00
339 lines
13 KiB
Plaintext
339 lines
13 KiB
Plaintext
{
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"nbformat": 4,
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"nbformat_minor": 0,
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"metadata": {
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"colab": {
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"provenance": [],
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"authorship_tag": "ABX9TyP+LenGtlXFGimgObzNvgqS",
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"include_colab_link": true
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},
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"kernelspec": {
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"name": "python3",
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"display_name": "Python 3"
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},
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"language_info": {
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"name": "python"
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},
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"accelerator": "GPU",
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"gpuClass": "standard"
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},
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "view-in-github",
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"colab_type": "text"
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},
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"source": [
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"<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>"
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]
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},
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{
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"cell_type": "markdown",
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"source": [
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"MMVCプレイヤー（超簡単版）\n",
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"---\n",
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"\n",
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"このノートはColab上でMMVCのボイチェンを行うノートです。\n",
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"\n",
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"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",
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"\n",
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"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",
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"\n",
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"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"
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],
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"metadata": {
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"id": "Lbbmx_Vjl0zo"
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}
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},
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{
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"cell_type": "markdown",
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"source": [
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"# GPUを確認\n",
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"GPUを用いたほうが高速に処理が行えます。\n",
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"\n",
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"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",
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"\n",
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"「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",
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"\n",
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"でGPUを選択してください。"
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],
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"metadata": {
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"id": "oUKi1NYMmXrr"
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}
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},
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{
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"cell_type": "code",
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"source": [
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"# (1) GPUの確認\n",
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"!nvidia-smi"
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],
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "vV1t7PBRm-o6",
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"outputId": "85aaa5ec-0fc9-4433-96f3-5086c17e5ba1"
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},
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"execution_count": 1,
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"outputs": [
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{
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"output_type": "stream",
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"name": "stdout",
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"text": [
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"Thu Jan 12 14:48:08 2023 \n",
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"+-----------------------------------------------------------------------------+\n",
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"| NVIDIA-SMI 460.32.03 Driver Version: 460.32.03 CUDA Version: 11.2 |\n",
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"|-------------------------------+----------------------+----------------------+\n",
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"| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |\n",
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"| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |\n",
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"| | | MIG M. |\n",
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"|===============================+======================+======================|\n",
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"| 0 Tesla T4 Off | 00000000:00:04.0 Off | 0 |\n",
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"| N/A 58C P8 10W / 70W | 0MiB / 15109MiB | 0% Default |\n",
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"| | | N/A |\n",
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"+-------------------------------+----------------------+----------------------+\n",
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" \n",
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"+-----------------------------------------------------------------------------+\n",
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"| Processes: |\n",
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"| GPU GI CI PID Type Process name GPU Memory |\n",
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"| ID ID Usage |\n",
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"|=============================================================================|\n",
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"| No running processes found |\n",
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"+-----------------------------------------------------------------------------+\n"
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]
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}
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]
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},
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{
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"cell_type": "markdown",
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"source": [
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"# リポジトリのクローン\n",
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"リポジトリをクローンします"
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],
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"metadata": {
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"id": "sLBfykjBnjWc"
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}
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},
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{
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"cell_type": "code",
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"source": [
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"# (2) リポジトリのクローン\n",
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"!git clone --depth 1 https://github.com/w-okada/voice-changer.git -b v.1.3.3\n",
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"%cd voice-changer/server\n",
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"!git clone --depth 1 https://github.com/isletennos/MMVC_Trainer.git -b v1.3.2.2\n",
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"!cd MMVC_Trainer/monotonic_align/ && python setup.py build_ext --inplace && cd -\n"
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],
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "86wTFmqsNMnD",
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"outputId": "27ad5458-3aee-4a05-945a-5b66fd603a8d"
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},
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"execution_count": 2,
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"outputs": [
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{
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"output_type": "stream",
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"name": "stdout",
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"text": [
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"Cloning into 'voice-changer'...\n",
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"remote: Enumerating objects: 143, done.\u001b[K\n",
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"remote: Counting objects: 100% (143/143), done.\u001b[K\n",
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"remote: Compressing objects: 100% (128/128), done.\u001b[K\n",
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"remote: Total 143 (delta 20), reused 62 (delta 5), pack-reused 0\u001b[K\n",
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"Receiving objects: 100% (143/143), 1.52 MiB | 4.30 MiB/s, done.\n",
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"Resolving deltas: 100% (20/20), done.\n",
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"/content/voice-changer/server\n",
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"Cloning into 'MMVC_Trainer'...\n",
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"remote: Enumerating objects: 920, done.\u001b[K\n",
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"remote: Counting objects: 100% (920/920), done.\u001b[K\n",
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"remote: Compressing objects: 100% (830/830), done.\u001b[K\n",
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"remote: Total 920 (delta 4), reused 893 (delta 1), pack-reused 0\u001b[K\n",
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"Receiving objects: 100% (920/920), 53.04 MiB | 17.33 MiB/s, done.\n",
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"Resolving deltas: 100% (4/4), done.\n",
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"Note: checking out 'f17c8c57d1ab7512633e6c57521f1eef6851bd0e'.\n",
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"\n",
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"You are in 'detached HEAD' state. You can look around, make experimental\n",
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"changes and commit them, and you can discard any commits you make in this\n",
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"state without impacting any branches by performing another checkout.\n",
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"\n",
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"If you want to create a new branch to retain commits you create, you may\n",
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"do so (now or later) by using -b with the checkout command again. Example:\n",
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"\n",
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" git checkout -b <new-branch-name>\n",
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"\n",
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"Compiling core.pyx because it changed.\n",
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"[1/1] Cythonizing core.pyx\n",
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"/usr/local/lib/python3.8/dist-packages/Cython/Compiler/Main.py:369: FutureWarning: Cython directive 'language_level' not set, using 2 for now (Py2). This will change in a later release! File: /content/voice-changer/server/MMVC_Trainer/monotonic_align/core.pyx\n",
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" tree = Parsing.p_module(s, pxd, full_module_name)\n",
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"running build_ext\n",
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"building 'monotonic_align.core' extension\n",
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"creating build\n",
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"creating build/temp.linux-x86_64-3.8\n",
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"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",
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"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/server/MMVC_Trainer/monotonic_align/monotonic_align/core.cpython-38-x86_64-linux-gnu.so\n",
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"/content/voice-changer/server\n"
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]
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}
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]
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},
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{
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"cell_type": "markdown",
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"source": [
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"# モジュールのインストール\n",
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"\n",
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"必要なモジュールをインストールします。"
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],
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"metadata": {
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"id": "8Na2PbLZSWgZ"
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}
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},
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{
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"cell_type": "code",
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"source": [
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"# (3) 設定ファイルの確認\n",
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"!apt-get install -y libsndfile1-dev &> /dev/null\n",
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"!pip install unidecode &> /dev/null\n",
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"!pip install phonemizer &> /dev/null\n",
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"!pip install retry &> /dev/null\n",
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"!pip install python-socketio &> /dev/null\n",
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"!pip install fastapi &> /dev/null\n",
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"!pip install python-multipart &> /dev/null\n",
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"!pip install uvicorn &> /dev/null\n",
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"!pip install websockets &> /dev/null\n",
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"!pip install pyOpenSSL &> /dev/null\n",
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"!pip install onnxruntime-gpu &> /dev/null"
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],
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"metadata": {
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"id": "LwZAAuqxX7yY"
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},
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"execution_count": 3,
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"outputs": []
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},
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{
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"cell_type": "markdown",
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"source": [
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"# サーバの起動\n",
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"\n",
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"サーバを起動します。(4-1)\n",
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"\n",
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"サーバの起動状況を確認します。(4-2) \n",
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"\n",
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"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",
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"\n",
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"下記のようなテキストが表示されたら起動完了です。\n",
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"\n",
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"**`DEBUG:asyncio:Using selector: EpollSelector`**\n",
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"\n",
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"```\n",
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" Phase name:__main__\n",
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" PHASE3:__main__\n",
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" PHASE1:__main__\n",
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"Start MMVC SocketIO Server\n",
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" CONFIG:None, MODEL:None ONNX_MODEL:None\n",
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"```\n",
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"\n"
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],
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"metadata": {
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"id": "-_2OcN9Borke"
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}
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},
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{
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"cell_type": "code",
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"source": [
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"# (4-1) サーバの起動\n",
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"import random\n",
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"PORT = 10000 + random.randint(1, 9999)\n",
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"LOG_FILE = f\"LOG_FILE_{PORT}\"\n",
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"\n",
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"get_ipython().system_raw(f'python3 MMVCServerSIO.py -t MMVC -p {PORT} --colab True >{LOG_FILE} 2>&1 &')\n",
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"#print(f\"PORT:{PORT}, LOG_FILE:{LOG_FILE}\")"
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],
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"metadata": {
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"id": "G-nMdPxEW1rc"
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},
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"execution_count": 4,
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"outputs": []
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},
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{
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"cell_type": "code",
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"source": [
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"# (4-2) サーバの起動確認\n",
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"!sleep 30\n",
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"!tail -20 {LOG_FILE}"
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],
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "chu06KpAjEK6",
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"outputId": "a4c8aea1-4193-4bb2-c128-3ed6d55e0270"
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},
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"execution_count": 5,
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"outputs": [
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{
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"output_type": "stream",
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"name": "stdout",
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"text": [
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"\u001b[32m Phase name:__main__\u001b[0m\n",
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"\u001b[32m PHASE3:__main__\u001b[0m\n",
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"\u001b[32m PHASE1:__main__\u001b[0m\n",
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"\u001b[17mStart MMVC SocketIO Server\u001b[0m\n",
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"\u001b[34m CONFIG:None, MODEL:None ONNX_MODEL:None\u001b[0m\n"
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]
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}
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]
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},
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{
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"cell_type": "markdown",
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"source": [
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"# プロキシを起動\n",
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"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",
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"\n",
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"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",
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"\n",
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"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)。"
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],
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"metadata": {
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"id": "WhxcFLQEpctq"
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}
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},
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{
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"cell_type": "code",
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"source": [
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"# (5) プロキシを起動\n",
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"from google.colab.output import eval_js\n",
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"proxy = eval_js( \"google.colab.kernel.proxyPort(\" + str(PORT) + \")\" )\n",
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"print(f\"{proxy}front/?colab=true\")"
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],
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"metadata": {
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"id": "nkRjZm95l87C",
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"colab": {
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"base_uri": "https://localhost:8080/",
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"height": 34
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},
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"outputId": "349c76f5-c039-46e3-e73b-7582e21e2f23"
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},
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"execution_count": 6,
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"outputs": [
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{
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"output_type": "stream",
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"name": "stdout",
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"text": [
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"https://pedza0b09p-496ff2e9c6d22116-12113-colab.googleusercontent.com/front/?colab=true\n"
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]
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}
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]
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},
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{
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"cell_type": "code",
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"source": [],
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"metadata": {
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"id": "axkt5BjhoiPV"
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},
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"execution_count": 6,
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"outputs": []
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}
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]
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} |