colab_webui.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/liutiao4533/python-spider/blob/master/colab_webui.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "环境配置 environment"
      ],
      "metadata": {
        "id": "_o6a8GS2lWQM"
      }
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "83PAXN45bwOa"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tnW2gkdPcZM_",
        "outputId": "c108a55e-32b0-458b-e9d8-3c5f85740c81"
      },
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "e9b7iFV3dm1f",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "98f07c98-e64c-4bc1-e841-868cb8613e89"
      },
      "source": [
        "!pip install -q condacolab\n",
        "# Setting up condacolab and installing packages\n",
        "import condacolab\n",
        "condacolab.install_from_url(\"https://repo.anaconda.com/miniconda/Miniconda3-py39_23.11.0-2-Linux-x86_64.sh\")\n",
        "%cd -q /content\n",
        "!git clone https://github.com/RVC-Boss/GPT-SoVITS\n",
        "!conda install -y -q -c pytorch -c nvidia cudatoolkit\n",
        "%cd -q /content/GPT-SoVITS\n",
        "!conda install -y -q -c conda-forge gcc gxx ffmpeg cmake -c pytorch -c nvidia\n",
        "!/usr/local/bin/pip install -r requirements.txt"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "⏬ Downloading https://repo.anaconda.com/miniconda/Miniconda3-py39_23.11.0-2-Linux-x86_64.sh...\n",
            "📦 Installing...\n",
            "📌 Adjusting configuration...\n",
            "🩹 Patching environment...\n",
            "⏲ Done in 0:00:21\n",
            "🔁 Restarting kernel...\n",
            "Cloning into 'GPT-SoVITS'...\n",
            "remote: Enumerating objects: 1616, done.\u001b[K\n",
            "remote: Counting objects: 100% (624/624), done.\u001b[K\n",
            "remote: Compressing objects: 100% (241/241), done.\u001b[K\n",
            "remote: Total 1616 (delta 521), reused 399 (delta 383), pack-reused 992\u001b[K\n",
            "Receiving objects: 100% (1616/1616), 2.86 MiB | 6.37 MiB/s, done.\n",
            "Resolving deltas: 100% (857/857), done.\n",
            "Channels:\n",
            " - pytorch\n",
            " - nvidia\n",
            " - defaults\n",
            "Platform: linux-64\n",
            "Collecting package metadata (repodata.json): ...working... done\n",
            "Solving environment: ...working... done\n",
            "\n",
            "## Package Plan ##\n",
            "\n",
            "  environment location: /usr/local\n",
            "\n",
            "  added / updated specs:\n",
            "    - cudatoolkit\n",
            "\n",
            "\n",
            "The following packages will be downloaded:\n",
            "\n",
            "    package                    |            build\n",
            "    ---------------------------|-----------------\n",
            "    conda-24.1.0               |   py39h06a4308_0         960 KB\n",
            "    cudatoolkit-11.7.0         |      hd8887f6_10       831.6 MB  nvidia\n",
            "    openssl-3.0.13             |       h7f8727e_0         5.2 MB\n",
            "    ------------------------------------------------------------\n",
            "                                           Total:       837.7 MB\n",
            "\n",
            "The following NEW packages will be INSTALLED:\n",
            "\n",
            "  cudatoolkit        nvidia/linux-64::cudatoolkit-11.7.0-hd8887f6_10 \n",
            "\n",
            "The following packages will be UPDATED:\n",
            "\n",
            "  conda                              23.11.0-py39h06a4308_0 --> 24.1.0-py39h06a4308_0 \n",
            "  openssl                                 3.0.12-h7f8727e_0 --> 3.0.13-h7f8727e_0 \n",
            "\n",
            "\n",
            "Preparing transaction: ...working... done\n",
            "Verifying transaction: ...working... done\n",
            "Executing transaction: ...working... By downloading and using the CUDA Toolkit conda packages, you accept the terms and conditions of the CUDA End User License Agreement (EULA): https://docs.nvidia.com/cuda/eula/index.html\n",
            "\n",
            "done\n",
            "Channels:\n",
            " - conda-forge\n",
            " - pytorch\n",
            " - nvidia\n",
            " - defaults\n",
            "Platform: linux-64\n",
            "Collecting package metadata (repodata.json): ...working... done\n",
            "Solving environment: ...working... done\n",
            "\n",
            "## Package Plan ##\n",
            "\n",
            "  environment location: /usr/local\n",
            "\n",
            "  added / updated specs:\n",
            "    - cmake\n",
            "    - ffmpeg\n",
            "    - gcc\n",
            "    - gxx\n",
            "\n",
            "\n",
            "The following packages will be downloaded:\n",
            "\n",
            "    package                    |            build\n",
            "    ---------------------------|-----------------\n",
            "    _libgcc_mutex-0.1          |      conda_forge           3 KB  conda-forge\n",
            "    _openmp_mutex-4.5          |            2_gnu          23 KB  conda-forge\n",
            "    aom-3.8.1                  |       h59595ed_0         2.6 MB  conda-forge\n",
            "    binutils_impl_linux-64-2.40|       hf600244_0         5.2 MB  conda-forge\n",
            "    ca-certificates-2024.2.2   |       hbcca054_0         152 KB  conda-forge\n",
            "    cairo-1.18.0               |       h3faef2a_0         959 KB  conda-forge\n",
            "    certifi-2023.11.17         |     pyhd8ed1ab_1         155 KB  conda-forge\n",
            "    cmake-3.28.2               |       hcfe8598_0        17.9 MB  conda-forge\n",
            "    dav1d-1.2.1                |       hd590300_0         742 KB  conda-forge\n",
            "    expat-2.5.0                |       hcb278e6_1         134 KB  conda-forge\n",
            "    ffmpeg-6.1.1               | gpl_h8007c5b_104         9.3 MB  conda-forge\n",
            "    font-ttf-dejavu-sans-mono-2.37|       hab24e00_0         388 KB  conda-forge\n",
            "    font-ttf-inconsolata-3.000 |       h77eed37_0          94 KB  conda-forge\n",
            "    font-ttf-source-code-pro-2.038|       h77eed37_0         684 KB  conda-forge\n",
            "    font-ttf-ubuntu-0.83       |       h77eed37_1         1.5 MB  conda-forge\n",
            "    fontconfig-2.14.2          |       h14ed4e7_0         266 KB  conda-forge\n",
            "    fonts-conda-ecosystem-1    |                0           4 KB  conda-forge\n",
            "    fonts-conda-forge-1        |                0           4 KB  conda-forge\n",
            "    freetype-2.12.1            |       h267a509_2         620 KB  conda-forge\n",
            "    fribidi-1.0.10             |       h36c2ea0_0         112 KB  conda-forge\n",
            "    gcc-13.2.0                 |       h574f8da_2          26 KB  conda-forge\n",
            "    gcc_impl_linux-64-13.2.0   |       h338b0a0_5        50.8 MB  conda-forge\n",
            "    gettext-0.21.1             |       h27087fc_0         4.1 MB  conda-forge\n",
            "    gmp-6.3.0                  |       h59595ed_0         550 KB  conda-forge\n",
            "    gnutls-3.7.9               |       hb077bed_0         1.9 MB  conda-forge\n",
            "    graphite2-1.3.13           |    h58526e2_1001         102 KB  conda-forge\n",
            "    gxx-13.2.0                 |       h574f8da_2          26 KB  conda-forge\n",
            "    gxx_impl_linux-64-13.2.0   |       h338b0a0_5        13.0 MB  conda-forge\n",
            "    harfbuzz-8.3.0             |       h3d44ed6_0         1.5 MB  conda-forge\n",
            "    icu-73.2                   |       h59595ed_0        11.5 MB  conda-forge\n",
            "    kernel-headers_linux-64-2.6.32|      he073ed8_16         692 KB  conda-forge\n",
            "    lame-3.100                 |    h166bdaf_1003         496 KB  conda-forge\n",
            "    ld_impl_linux-64-2.40      |       h41732ed_0         688 KB  conda-forge\n",
            "    libabseil-20230802.1       | cxx17_h59595ed_0         1.2 MB  conda-forge\n",
            "    libarchive-3.6.2           |       h039dbb9_1         824 KB  conda-forge\n",
            "    libass-0.17.1              |       h8fe9dca_1         124 KB  conda-forge\n",
            "    libcurl-8.5.0              |       h251f7ec_0         416 KB\n",
            "    libdrm-2.4.114             |       h166bdaf_0         298 KB  conda-forge\n",
            "    libexpat-2.5.0             |       hcb278e6_1          76 KB  conda-forge\n",
            "    libgcc-devel_linux-64-13.2.0|     ha9c7c90_105         2.5 MB  conda-forge\n",
            "    libgcc-ng-13.2.0           |       h807b86a_5         752 KB  conda-forge\n",
            "    libglib-2.78.3             |       h783c2da_0         2.6 MB  conda-forge\n",
            "    libgomp-13.2.0             |       h807b86a_5         410 KB  conda-forge\n",
            "    libhwloc-2.9.3             |default_h554bfaf_1009         2.5 MB  conda-forge\n",
            "    libiconv-1.17              |       hd590300_2         689 KB  conda-forge\n",
            "    libidn2-2.3.7              |       hd590300_0         124 KB  conda-forge\n",
            "    libopenvino-2023.3.0       |       h2e90f83_0         5.7 MB  conda-forge\n",
            "    libopenvino-auto-batch-plugin-2023.3.0|       hd5fc58b_0         113 KB  conda-forge\n",
            "    libopenvino-auto-plugin-2023.3.0|       hd5fc58b_0         233 KB  conda-forge\n",
            "    libopenvino-hetero-plugin-2023.3.0|       h3ecfda7_0         178 KB  conda-forge\n",
            "    libopenvino-intel-cpu-plugin-2023.3.0|       h2e90f83_0         9.7 MB  conda-forge\n",
            "    libopenvino-intel-gpu-plugin-2023.3.0|       h2e90f83_0         7.8 MB  conda-forge\n",
            "    libopenvino-ir-frontend-2023.3.0|       h3ecfda7_0         194 KB  conda-forge\n",
            "    libopenvino-onnx-frontend-2023.3.0|       hfbc7f12_0         1.5 MB  conda-forge\n",
            "    libopenvino-paddle-frontend-2023.3.0|       hfbc7f12_0         644 KB  conda-forge\n",
            "    libopenvino-pytorch-frontend-2023.3.0|       h59595ed_0         938 KB  conda-forge\n",
            "    libopenvino-tensorflow-frontend-2023.3.0|       h0bff32c_0         1.1 MB  conda-forge\n",
            "    libopenvino-tensorflow-lite-frontend-2023.3.0|       h59595ed_0         446 KB  conda-forge\n",
            "    libopus-1.3.1              |       h7f98852_1         255 KB  conda-forge\n",
            "    libpciaccess-0.17          |       h166bdaf_0          39 KB  conda-forge\n",
            "    libpng-1.6.42              |       h2797004_0         282 KB  conda-forge\n",
            "    libprotobuf-4.25.1         |       hf27288f_1         2.6 MB  conda-forge\n",
            "    libsanitizer-13.2.0        |       h7e041cc_5         3.9 MB  conda-forge\n",
            "    libstdcxx-devel_linux-64-13.2.0|     ha9c7c90_105        12.4 MB  conda-forge\n",
            "    libstdcxx-ng-13.2.0        |       h7e041cc_5         3.7 MB  conda-forge\n",
            "    libtasn1-4.19.0            |       h166bdaf_0         114 KB  conda-forge\n",
            "    libunistring-0.9.10        |       h7f98852_0         1.4 MB  conda-forge\n",
            "    libuuid-2.38.1             |       h0b41bf4_0          33 KB  conda-forge\n",
            "    libuv-1.46.0               |       hd590300_0         872 KB  conda-forge\n",
            "    libva-2.20.0               |       hd590300_0         184 KB  conda-forge\n",
            "    libvpx-1.13.1              |       h59595ed_0         982 KB  conda-forge\n",
            "    libxcb-1.15                |       h0b41bf4_0         375 KB  conda-forge\n",
            "    libxml2-2.12.4             |       h232c23b_1         688 KB  conda-forge\n",
            "    libzlib-1.2.13             |       hd590300_5          60 KB  conda-forge\n",
            "    lzo-2.10                   |    h516909a_1000         314 KB  conda-forge\n",
            "    nettle-3.9.1               |       h7ab15ed_0         988 KB  conda-forge\n",
            "    ocl-icd-2.3.1              |       h7f98852_0         119 KB  conda-forge\n",
            "    ocl-icd-system-1.0.0       |                1           4 KB  conda-forge\n",
            "    openh264-2.4.1             |       h59595ed_0         718 KB  conda-forge\n",
            "    openssl-3.2.1              |       hd590300_0         2.7 MB  conda-forge\n",
            "    p11-kit-0.24.1             |       hc5aa10d_0         4.5 MB  conda-forge\n",
            "    pixman-0.43.2              |       h59595ed_0         378 KB  conda-forge\n",
            "    pthread-stubs-0.4          |    h36c2ea0_1001           5 KB  conda-forge\n",
            "    pugixml-1.14               |       h59595ed_0         112 KB  conda-forge\n",
            "    rhash-1.4.4                |       hd590300_0         181 KB  conda-forge\n",
            "    snappy-1.1.10              |       h9fff704_0          38 KB  conda-forge\n",
            "    svt-av1-1.8.0              |       h59595ed_0         2.5 MB  conda-forge\n",
            "    sysroot_linux-64-2.12      |      he073ed8_16        14.6 MB  conda-forge\n",
            "    tbb-2021.11.0              |       h00ab1b0_1         191 KB  conda-forge\n",
            "    x264-1!164.3095            |       h166bdaf_2         877 KB  conda-forge\n",
            "    x265-3.5                   |       h924138e_3         3.2 MB  conda-forge\n",
            "    xorg-fixesproto-5.0        |    h7f98852_1002           9 KB  conda-forge\n",
            "    xorg-kbproto-1.0.7         |    h7f98852_1002          27 KB  conda-forge\n",
            "    xorg-libice-1.1.1          |       hd590300_0          57 KB  conda-forge\n",
            "    xorg-libsm-1.2.4           |       h7391055_0          27 KB  conda-forge\n",
            "    xorg-libx11-1.8.7          |       h8ee46fc_0         809 KB  conda-forge\n",
            "    xorg-libxau-1.0.11         |       hd590300_0          14 KB  conda-forge\n",
            "    xorg-libxdmcp-1.1.3        |       h7f98852_0          19 KB  conda-forge\n",
            "    xorg-libxext-1.3.4         |       h0b41bf4_2          49 KB  conda-forge\n",
            "    xorg-libxfixes-5.0.3       |    h7f98852_1004          18 KB  conda-forge\n",
            "    xorg-libxrender-0.9.11     |       hd590300_0          37 KB  conda-forge\n",
            "    xorg-renderproto-0.11.1    |    h7f98852_1002           9 KB  conda-forge\n",
            "    xorg-xextproto-7.3.0       |    h0b41bf4_1003          30 KB  conda-forge\n",
            "    xorg-xproto-7.0.31         |    h7f98852_1007          73 KB  conda-forge\n",
            "    zlib-1.2.13                |       hd590300_5          91 KB  conda-forge\n",
            "    ------------------------------------------------------------\n",
            "                                           Total:       227.3 MB\n",
            "\n",
            "The following NEW packages will be INSTALLED:\n",
            "\n",
            "  aom                conda-forge/linux-64::aom-3.8.1-h59595ed_0 \n",
            "  binutils_impl_lin~ conda-forge/linux-64::binutils_impl_linux-64-2.40-hf600244_0 \n",
            "  cairo              conda-forge/linux-64::cairo-1.18.0-h3faef2a_0 \n",
            "  cmake              conda-forge/linux-64::cmake-3.28.2-hcfe8598_0 \n",
            "  dav1d              conda-forge/linux-64::dav1d-1.2.1-hd590300_0 \n",
            "  expat              conda-forge/linux-64::expat-2.5.0-hcb278e6_1 \n",
            "  ffmpeg             conda-forge/linux-64::ffmpeg-6.1.1-gpl_h8007c5b_104 \n",
            "  font-ttf-dejavu-s~ conda-forge/noarch::font-ttf-dejavu-sans-mono-2.37-hab24e00_0 \n",
            "  font-ttf-inconsol~ conda-forge/noarch::font-ttf-inconsolata-3.000-h77eed37_0 \n",
            "  font-ttf-source-c~ conda-forge/noarch::font-ttf-source-code-pro-2.038-h77eed37_0 \n",
            "  font-ttf-ubuntu    conda-forge/noarch::font-ttf-ubuntu-0.83-h77eed37_1 \n",
            "  fontconfig         conda-forge/linux-64::fontconfig-2.14.2-h14ed4e7_0 \n",
            "  fonts-conda-ecosy~ conda-forge/noarch::fonts-conda-ecosystem-1-0 \n",
            "  fonts-conda-forge  conda-forge/noarch::fonts-conda-forge-1-0 \n",
            "  freetype           conda-forge/linux-64::freetype-2.12.1-h267a509_2 \n",
            "  fribidi            conda-forge/linux-64::fribidi-1.0.10-h36c2ea0_0 \n",
            "  gcc                conda-forge/linux-64::gcc-13.2.0-h574f8da_2 \n",
            "  gcc_impl_linux-64  conda-forge/linux-64::gcc_impl_linux-64-13.2.0-h338b0a0_5 \n",
            "  gettext            conda-forge/linux-64::gettext-0.21.1-h27087fc_0 \n",
            "  gmp                conda-forge/linux-64::gmp-6.3.0-h59595ed_0 \n",
            "  gnutls             conda-forge/linux-64::gnutls-3.7.9-hb077bed_0 \n",
            "  graphite2          conda-forge/linux-64::graphite2-1.3.13-h58526e2_1001 \n",
            "  gxx                conda-forge/linux-64::gxx-13.2.0-h574f8da_2 \n",
            "  gxx_impl_linux-64  conda-forge/linux-64::gxx_impl_linux-64-13.2.0-h338b0a0_5 \n",
            "  harfbuzz           conda-forge/linux-64::harfbuzz-8.3.0-h3d44ed6_0 \n",
            "  kernel-headers_li~ conda-forge/noarch::kernel-headers_linux-64-2.6.32-he073ed8_16 \n",
            "  lame               conda-forge/linux-64::lame-3.100-h166bdaf_1003 \n",
            "  libabseil          conda-forge/linux-64::libabseil-20230802.1-cxx17_h59595ed_0 \n",
            "  libass             conda-forge/linux-64::libass-0.17.1-h8fe9dca_1 \n",
            "  libdrm             conda-forge/linux-64::libdrm-2.4.114-h166bdaf_0 \n",
            "  libexpat           conda-forge/linux-64::libexpat-2.5.0-hcb278e6_1 \n",
            "  libgcc-devel_linu~ conda-forge/noarch::libgcc-devel_linux-64-13.2.0-ha9c7c90_105 \n",
            "  libglib            conda-forge/linux-64::libglib-2.78.3-h783c2da_0 \n",
            "  libhwloc           conda-forge/linux-64::libhwloc-2.9.3-default_h554bfaf_1009 \n",
            "  libiconv           conda-forge/linux-64::libiconv-1.17-hd590300_2 \n",
            "  libidn2            conda-forge/linux-64::libidn2-2.3.7-hd590300_0 \n",
            "  libopenvino        conda-forge/linux-64::libopenvino-2023.3.0-h2e90f83_0 \n",
            "  libopenvino-auto-~ conda-forge/linux-64::libopenvino-auto-batch-plugin-2023.3.0-hd5fc58b_0 \n",
            "  libopenvino-auto-~ conda-forge/linux-64::libopenvino-auto-plugin-2023.3.0-hd5fc58b_0 \n",
            "  libopenvino-heter~ conda-forge/linux-64::libopenvino-hetero-plugin-2023.3.0-h3ecfda7_0 \n",
            "  libopenvino-intel~ conda-forge/linux-64::libopenvino-intel-cpu-plugin-2023.3.0-h2e90f83_0 \n",
            "  libopenvino-intel~ conda-forge/linux-64::libopenvino-intel-gpu-plugin-2023.3.0-h2e90f83_0 \n",
            "  libopenvino-ir-fr~ conda-forge/linux-64::libopenvino-ir-frontend-2023.3.0-h3ecfda7_0 \n",
            "  libopenvino-onnx-~ conda-forge/linux-64::libopenvino-onnx-frontend-2023.3.0-hfbc7f12_0 \n",
            "  libopenvino-paddl~ conda-forge/linux-64::libopenvino-paddle-frontend-2023.3.0-hfbc7f12_0 \n",
            "  libopenvino-pytor~ conda-forge/linux-64::libopenvino-pytorch-frontend-2023.3.0-h59595ed_0 \n",
            "  libopenvino-tenso~ conda-forge/linux-64::libopenvino-tensorflow-frontend-2023.3.0-h0bff32c_0 \n",
            "  libopenvino-tenso~ conda-forge/linux-64::libopenvino-tensorflow-lite-frontend-2023.3.0-h59595ed_0 \n",
            "  libopus            conda-forge/linux-64::libopus-1.3.1-h7f98852_1 \n",
            "  libpciaccess       conda-forge/linux-64::libpciaccess-0.17-h166bdaf_0 \n",
            "  libpng             conda-forge/linux-64::libpng-1.6.42-h2797004_0 \n",
            "  libprotobuf        conda-forge/linux-64::libprotobuf-4.25.1-hf27288f_1 \n",
            "  libsanitizer       conda-forge/linux-64::libsanitizer-13.2.0-h7e041cc_5 \n",
            "  libstdcxx-devel_l~ conda-forge/noarch::libstdcxx-devel_linux-64-13.2.0-ha9c7c90_105 \n",
            "  libtasn1           conda-forge/linux-64::libtasn1-4.19.0-h166bdaf_0 \n",
            "  libunistring       conda-forge/linux-64::libunistring-0.9.10-h7f98852_0 \n",
            "  libuuid            conda-forge/linux-64::libuuid-2.38.1-h0b41bf4_0 \n",
            "  libuv              conda-forge/linux-64::libuv-1.46.0-hd590300_0 \n",
            "  libva              conda-forge/linux-64::libva-2.20.0-hd590300_0 \n",
            "  libvpx             conda-forge/linux-64::libvpx-1.13.1-h59595ed_0 \n",
            "  libxcb             conda-forge/linux-64::libxcb-1.15-h0b41bf4_0 \n",
            "  libzlib            conda-forge/linux-64::libzlib-1.2.13-hd590300_5 \n",
            "  lzo                conda-forge/linux-64::lzo-2.10-h516909a_1000 \n",
            "  nettle             conda-forge/linux-64::nettle-3.9.1-h7ab15ed_0 \n",
            "  ocl-icd            conda-forge/linux-64::ocl-icd-2.3.1-h7f98852_0 \n",
            "  ocl-icd-system     conda-forge/linux-64::ocl-icd-system-1.0.0-1 \n",
            "  openh264           conda-forge/linux-64::openh264-2.4.1-h59595ed_0 \n",
            "  p11-kit            conda-forge/linux-64::p11-kit-0.24.1-hc5aa10d_0 \n",
            "  pixman             conda-forge/linux-64::pixman-0.43.2-h59595ed_0 \n",
            "  pthread-stubs      conda-forge/linux-64::pthread-stubs-0.4-h36c2ea0_1001 \n",
            "  pugixml            conda-forge/linux-64::pugixml-1.14-h59595ed_0 \n",
            "  rhash              conda-forge/linux-64::rhash-1.4.4-hd590300_0 \n",
            "  snappy             conda-forge/linux-64::snappy-1.1.10-h9fff704_0 \n",
            "  svt-av1            conda-forge/linux-64::svt-av1-1.8.0-h59595ed_0 \n",
            "  sysroot_linux-64   conda-forge/noarch::sysroot_linux-64-2.12-he073ed8_16 \n",
            "  tbb                conda-forge/linux-64::tbb-2021.11.0-h00ab1b0_1 \n",
            "  x264               conda-forge/linux-64::x264-1!164.3095-h166bdaf_2 \n",
            "  x265               conda-forge/linux-64::x265-3.5-h924138e_3 \n",
            "  xorg-fixesproto    conda-forge/linux-64::xorg-fixesproto-5.0-h7f98852_1002 \n",
            "  xorg-kbproto       conda-forge/linux-64::xorg-kbproto-1.0.7-h7f98852_1002 \n",
            "  xorg-libice        conda-forge/linux-64::xorg-libice-1.1.1-hd590300_0 \n",
            "  xorg-libsm         conda-forge/linux-64::xorg-libsm-1.2.4-h7391055_0 \n",
            "  xorg-libx11        conda-forge/linux-64::xorg-libx11-1.8.7-h8ee46fc_0 \n",
            "  xorg-libxau        conda-forge/linux-64::xorg-libxau-1.0.11-hd590300_0 \n",
            "  xorg-libxdmcp      conda-forge/linux-64::xorg-libxdmcp-1.1.3-h7f98852_0 \n",
            "  xorg-libxext       conda-forge/linux-64::xorg-libxext-1.3.4-h0b41bf4_2 \n",
            "  xorg-libxfixes     conda-forge/linux-64::xorg-libxfixes-5.0.3-h7f98852_1004 \n",
            "  xorg-libxrender    conda-forge/linux-64::xorg-libxrender-0.9.11-hd590300_0 \n",
            "  xorg-renderproto   conda-forge/linux-64::xorg-renderproto-0.11.1-h7f98852_1002 \n",
            "  xorg-xextproto     conda-forge/linux-64::xorg-xextproto-7.3.0-h0b41bf4_1003 \n",
            "  xorg-xproto        conda-forge/linux-64::xorg-xproto-7.0.31-h7f98852_1007 \n",
            "\n",
            "The following packages will be UPDATED:\n",
            "\n",
            "  ca-certificates    pkgs/main::ca-certificates-2023.12.12~ --> conda-forge::ca-certificates-2024.2.2-hbcca054_0 \n",
            "  certifi            pkgs/main/linux-64::certifi-2023.11.1~ --> conda-forge/noarch::certifi-2023.11.17-pyhd8ed1ab_1 \n",
            "  icu                        pkgs/main::icu-73.1-h6a678d5_0 --> conda-forge::icu-73.2-h59595ed_0 \n",
            "  ld_impl_linux-64   pkgs/main::ld_impl_linux-64-2.38-h118~ --> conda-forge::ld_impl_linux-64-2.40-h41732ed_0 \n",
            "  libcurl                                  8.4.0-h251f7ec_1 --> 8.5.0-h251f7ec_0 \n",
            "  libgcc-ng          pkgs/main::libgcc-ng-11.2.0-h1234567_1 --> conda-forge::libgcc-ng-13.2.0-h807b86a_5 \n",
            "  libgomp              pkgs/main::libgomp-11.2.0-h1234567_1 --> conda-forge::libgomp-13.2.0-h807b86a_5 \n",
            "  libstdcxx-ng       pkgs/main::libstdcxx-ng-11.2.0-h12345~ --> conda-forge::libstdcxx-ng-13.2.0-h7e041cc_5 \n",
            "  libxml2              pkgs/main::libxml2-2.10.4-hf1b16e4_1 --> conda-forge::libxml2-2.12.4-h232c23b_1 \n",
            "  openssl              pkgs/main::openssl-3.0.13-h7f8727e_0 --> conda-forge::openssl-3.2.1-hd590300_0 \n",
            "  zlib                    pkgs/main::zlib-1.2.13-h5eee18b_0 --> conda-forge::zlib-1.2.13-hd590300_5 \n",
            "\n",
            "The following packages will be SUPERSEDED by a higher-priority channel:\n",
            "\n",
            "  _libgcc_mutex           pkgs/main::_libgcc_mutex-0.1-main --> conda-forge::_libgcc_mutex-0.1-conda_forge \n",
            "  _openmp_mutex          pkgs/main::_openmp_mutex-5.1-1_gnu --> conda-forge::_openmp_mutex-4.5-2_gnu \n",
            "  libarchive         pkgs/main::libarchive-3.6.2-h6ac8c49_2 --> conda-forge::libarchive-3.6.2-h039dbb9_1 \n",
            "\n",
            "\n",
            "Preparing transaction: ...working... done\n",
            "Verifying transaction: ...working... done\n",
            "Executing transaction: ...working... done\n",
            "Collecting numpy (from -r requirements.txt (line 1))\n",
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            "\u001b[?25h  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
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            "  Downloading PyYAML-6.0.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (2.1 kB)\n",
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            "  Downloading psutil-5.9.8-cp36-abi3-manylinux_2_12_x86_64.manylinux2010_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (21 kB)\n",
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            "\u001b[?25h  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
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            "  Stored in directory: /root/.cache/pip/wheels/23/cf/80/f3efa822e6ab23277902ee9165fe772eeb1dfb8014f359020a\n",
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            "  Created wheel for ffmpy: filename=ffmpy-0.3.1-py3-none-any.whl size=5579 sha256=bb4b25735f0bdae62171022e978398da965fcc4f50efc44a384134287cd327a4\n",
            "  Stored in directory: /root/.cache/pip/wheels/1f/f1/8d/367922b023b526b7c2ced5db30932def7b18cf39d7ac6e8572\n",
            "  Building wheel for future (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for future: filename=future-0.18.3-py3-none-any.whl size=492024 sha256=8f8e10affc7a8ea022cfa9b3bbde0400f7b9b91b05d1f6d1adb47095b9a80500\n",
            "  Stored in directory: /root/.cache/pip/wheels/bf/5d/6a/2e53874f7ec4e2bede522385439531fafec8fafe005b5c3d1b\n",
            "  Building wheel for hdbscan (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for hdbscan: filename=hdbscan-0.8.33-cp39-cp39-linux_x86_64.whl size=737965 sha256=939e4e9dfd7292f58a29148604b0f4466db9e15b60368626372712308a04b138\n",
            "  Stored in directory: /root/.cache/pip/wheels/28/5e/ed/5989da4cc423a222a47cbb4fde5d6c0eff4590d922e45f233c\n",
            "  Building wheel for jaconv (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for jaconv: filename=jaconv-0.3.4-py3-none-any.whl size=16416 sha256=54f1364117b84ca80f3709ddbc186db1edd58a95830bea07654da57321dd27f5\n",
            "  Stored in directory: /root/.cache/pip/wheels/49/de/f1/55f605920db3666d30215331bc85f24686dde9b95b473ae41b\n",
            "  Building wheel for oss2 (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for oss2: filename=oss2-2.18.4-py3-none-any.whl size=115939 sha256=f87415cedd9f44bf4b4d63daa4a9c4f92611a746ef6dd46d3ec875f16ce0e3e0\n",
            "  Stored in directory: /root/.cache/pip/wheels/0f/65/8e/0417b076271c1d16cd41db00820b121cdc3fab91e2fbeb2aae\n",
            "  Building wheel for umap-learn (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for umap-learn: filename=umap_learn-0.5.5-py3-none-any.whl size=86832 sha256=2dcf066417195eaa00dfbc11a537f14a4acf24cb00c26f6c50ba254fca4f0d31\n",
            "  Stored in directory: /root/.cache/pip/wheels/0f/01/17/26951217a11fb724b7027c6dd5b620b6d368104f7e6d4171fc\n",
            "  Building wheel for aliyun-python-sdk-core (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for aliyun-python-sdk-core: filename=aliyun_python_sdk_core-2.14.0-py3-none-any.whl size=535290 sha256=1b8eba3ada5a17d6e0d4c0543d35b3c5365dc24c8d7184096cfe7b74b987ea55\n",
            "  Stored in directory: /root/.cache/pip/wheels/00/bd/a9/ef224c78c3aa426c4867927f46ebb6fd1fd705c6c4bafde111\n",
            "  Building wheel for crcmod (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for crcmod: filename=crcmod-1.7-cp39-cp39-linux_x86_64.whl size=23291 sha256=2e224acbbaa3abcb5eff4ee266ec394ed7bbba7a035ad608bdeae519ae47c64f\n",
            "  Stored in directory: /root/.cache/pip/wheels/4a/6c/a6/ffdd136310039bf226f2707a9a8e6857be7d70a3fc061f6b36\n",
            "Successfully built pyopenjtalk jieba_fast jieba distance antlr4-python3-runtime ffmpy future hdbscan jaconv oss2 umap-learn aliyun-python-sdk-core crcmod\n",
            "Installing collected packages: sortedcontainers, sentencepiece, pytz, pydub, mpmath, jieba_fast, jieba, jamo, jaconv, flatbuffers, ffmpy, distance, crcmod, antlr4-python3-runtime, addict, zipp, xxhash, websockets, uc-micro-py, tzdata, typing-extensions, toolz, tomli, threadpoolctl, tensorboard-data-server, sympy, sniffio, six, simplejson, semantic-version, safetensors, rpds-py, regex, PyYAML, python-multipart, pypinyin, pyparsing, pycryptodome, pyasn1, pyarrow-hotfix, psutil, protobuf, proces, pillow, orjson, oauthlib, nvidia-nvtx-cu12, nvidia-nvjitlink-cu12, nvidia-nccl-cu12, nvidia-curand-cu12, nvidia-cufft-cu12, nvidia-cuda-runtime-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-cupti-cu12, nvidia-cublas-cu12, numpy, networkx, multidict, mdurl, markupsafe, llvmlite, kiwisolver, joblib, jmespath, humanfriendly, h11, grpcio, gast, future, fsspec, frozenlist, fonttools, filelock, exceptiongroup, einops, editdistance, dill, decorator, cython, cycler, click, chardet, cachetools, audioread, attrs, async-timeout, annotated-types, aiofiles, absl-py, yarl, werkzeug, uvicorn, triton, torch-complex, soundfile, scipy, rsa, requests-oauthlib, referencing, pytorch-wpe, python-dateutil, pyopenjtalk, pydantic-core, pyasn1-modules, pyarrow, py3langid, pooch, omegaconf, nvidia-cusparse-cu12, nvidia-cudnn-cu12, numba, nltk, multiprocess, markdown-it-py, linkify-it-py, lightning-utilities, kaldiio, jinja2, importlib-resources, importlib-metadata, huggingface-hub, httpcore, ffmpeg-python, contourpy, coloredlogs, cn2an, anyio, aiosignal, yapf, tokenizers, starlette, scikit-learn, resampy, pydantic, pandas, onnxruntime, nvidia-cusolver-cu12, mdit-py-plugins, matplotlib, markdown, LangSegment, jsonschema-specifications, hydra-core, httpx, google-auth, aliyun-python-sdk-core, aiohttp, transformers, torch, pynndescent, librosa, jsonschema, inflect, hdbscan, gradio-client, google-auth-oauthlib, fastapi, aliyun-python-sdk-kms, umap-learn, torchmetrics, torchaudio, tensorboard, oss2, g2p_en, datasets, altair, pytorch-lightning, modelscope, gradio, funasr\n",
            "Successfully installed LangSegment-0.1.3 PyYAML-6.0.1 absl-py-2.1.0 addict-2.4.0 aiofiles-23.2.1 aiohttp-3.9.3 aiosignal-1.3.1 aliyun-python-sdk-core-2.14.0 aliyun-python-sdk-kms-2.16.2 altair-5.2.0 annotated-types-0.6.0 antlr4-python3-runtime-4.9.3 anyio-4.2.0 async-timeout-4.0.3 attrs-23.2.0 audioread-3.0.1 cachetools-5.3.2 chardet-5.2.0 click-8.1.7 cn2an-0.5.22 coloredlogs-15.0.1 contourpy-1.2.0 crcmod-1.7 cycler-0.12.1 cython-0.29.37 datasets-2.16.1 decorator-5.1.1 dill-0.3.7 distance-0.1.3 editdistance-0.6.2 einops-0.7.0 exceptiongroup-1.2.0 fastapi-0.109.1 ffmpeg-python-0.2.0 ffmpy-0.3.1 filelock-3.13.1 flatbuffers-23.5.26 fonttools-4.47.2 frozenlist-1.4.1 fsspec-2023.10.0 funasr-1.0.5 future-0.18.3 g2p_en-2.1.0 gast-0.5.4 google-auth-2.27.0 google-auth-oauthlib-1.2.0 gradio-3.38.0 gradio-client-0.8.1 grpcio-1.60.1 h11-0.14.0 hdbscan-0.8.33 httpcore-1.0.2 httpx-0.26.0 huggingface-hub-0.20.3 humanfriendly-10.0 hydra-core-1.3.2 importlib-metadata-7.0.1 importlib-resources-6.1.1 inflect-7.0.0 jaconv-0.3.4 jamo-0.4.1 jieba-0.42.1 jieba_fast-0.53 jinja2-3.1.3 jmespath-0.10.0 joblib-1.3.2 jsonschema-4.21.1 jsonschema-specifications-2023.12.1 kaldiio-2.18.0 kiwisolver-1.4.5 librosa-0.9.2 lightning-utilities-0.10.1 linkify-it-py-2.0.2 llvmlite-0.39.1 markdown-3.5.2 markdown-it-py-2.2.0 markupsafe-2.1.5 matplotlib-3.8.2 mdit-py-plugins-0.3.3 mdurl-0.1.2 modelscope-1.10.0 mpmath-1.3.0 multidict-6.0.5 multiprocess-0.70.15 networkx-3.2.1 nltk-3.8.1 numba-0.56.4 numpy-1.23.5 nvidia-cublas-cu12-12.1.3.1 nvidia-cuda-cupti-cu12-12.1.105 nvidia-cuda-nvrtc-cu12-12.1.105 nvidia-cuda-runtime-cu12-12.1.105 nvidia-cudnn-cu12-8.9.2.26 nvidia-cufft-cu12-11.0.2.54 nvidia-curand-cu12-10.3.2.106 nvidia-cusolver-cu12-11.4.5.107 nvidia-cusparse-cu12-12.1.0.106 nvidia-nccl-cu12-2.19.3 nvidia-nvjitlink-cu12-12.3.101 nvidia-nvtx-cu12-12.1.105 oauthlib-3.2.2 omegaconf-2.3.0 onnxruntime-1.17.0 orjson-3.9.12 oss2-2.18.4 pandas-2.2.0 pillow-10.2.0 pooch-1.8.0 proces-0.1.7 protobuf-4.23.4 psutil-5.9.8 py3langid-0.2.2 pyarrow-15.0.0 pyarrow-hotfix-0.6 pyasn1-0.5.1 pyasn1-modules-0.3.0 pycryptodome-3.20.0 pydantic-2.6.0 pydantic-core-2.16.1 pydub-0.25.1 pynndescent-0.5.11 pyopenjtalk-0.3.3 pyparsing-3.1.1 pypinyin-0.50.0 python-dateutil-2.8.2 python-multipart-0.0.7 pytorch-lightning-2.1.4 pytorch-wpe-0.0.1 pytz-2024.1 referencing-0.33.0 regex-2023.12.25 requests-oauthlib-1.3.1 resampy-0.4.2 rpds-py-0.17.1 rsa-4.9 safetensors-0.4.2 scikit-learn-1.4.0 scipy-1.12.0 semantic-version-2.10.0 sentencepiece-0.1.99 simplejson-3.19.2 six-1.16.0 sniffio-1.3.0 sortedcontainers-2.4.0 soundfile-0.12.1 starlette-0.35.1 sympy-1.12 tensorboard-2.15.1 tensorboard-data-server-0.7.2 threadpoolctl-3.2.0 tokenizers-0.15.1 tomli-2.0.1 toolz-0.12.1 torch-2.2.0 torch-complex-0.4.3 torchaudio-2.2.0 torchmetrics-1.3.0.post0 transformers-4.37.2 triton-2.2.0 typing-extensions-4.9.0 tzdata-2023.4 uc-micro-py-1.0.2 umap-learn-0.5.5 uvicorn-0.27.0.post1 websockets-11.0.3 werkzeug-3.0.1 xxhash-3.4.1 yapf-0.40.2 yarl-1.9.4 zipp-3.17.0\n",
            "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
            "\u001b[0m"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# @title Download pretrained models 下载预训练模型\n",
        "!mkdir -p /content/GPT-SoVITS/GPT_SoVITS/pretrained_models\n",
        "!mkdir -p /content/GPT-SoVITS/tools/damo_asr/models\n",
        "!mkdir -p /content/GPT-SoVITS/tools/uvr5\n",
        "%cd /content/GPT-SoVITS/GPT_SoVITS/pretrained_models\n",
        "!git clone https://huggingface.co/lj1995/GPT-SoVITS\n",
        "%cd /content/GPT-SoVITS/tools/damo_asr/models\n",
        "!git clone https://www.modelscope.cn/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch.git\n",
        "!git clone https://www.modelscope.cn/damo/speech_fsmn_vad_zh-cn-16k-common-pytorch.git\n",
        "!git clone https://www.modelscope.cn/damo/punc_ct-transformer_zh-cn-common-vocab272727-pytorch.git\n",
        "# @title UVR5 pretrains 安装uvr5模型\n",
        "%cd /content/GPT-SoVITS/tools/uvr5\n",
        "!git clone https://huggingface.co/Delik/uvr5_weights\n",
        "!git config core.sparseCheckout true\n",
        "!mv /content/GPT-SoVITS/GPT_SoVITS/pretrained_models/GPT-SoVITS/* /content/GPT-SoVITS/GPT_SoVITS/pretrained_models/"
      ],
      "metadata": {
        "id": "0NgxXg5sjv7z",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "4d90ba78-0110-4f2e-dd87-ebdc9c070db8"
      },
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/bin/bash: /usr/local/lib/libtinfo.so.6: no version information available (required by /bin/bash)\n",
            "/bin/bash: /usr/local/lib/libtinfo.so.6: no version information available (required by /bin/bash)\n",
            "/bin/bash: /usr/local/lib/libtinfo.so.6: no version information available (required by /bin/bash)\n",
            "/content/GPT-SoVITS/GPT_SoVITS/pretrained_models\n",
            "/bin/bash: /usr/local/lib/libtinfo.so.6: no version information available (required by /bin/bash)\n",
            "Cloning into 'GPT-SoVITS'...\n",
            "remote: Enumerating objects: 20, done.\u001b[K\n",
            "remote: Counting objects: 100% (16/16), done.\u001b[K\n",
            "remote: Compressing objects: 100% (16/16), done.\u001b[K\n",
            "remote: Total 20 (delta 1), reused 0 (delta 0), pack-reused 4\u001b[K\n",
            "Unpacking objects: 100% (20/20), 102.34 KiB | 7.31 MiB/s, done.\n",
            "Filtering content: 100% (5/5), 1.11 GiB | 63.43 MiB/s, done.\n",
            "/content/GPT-SoVITS/tools/damo_asr/models\n",
            "/bin/bash: /usr/local/lib/libtinfo.so.6: no version information available (required by /bin/bash)\n",
            "Cloning into 'speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch'...\n",
            "remote: Enumerating objects: 465, done.\u001b[K\n",
            "remote: Counting objects: 100% (57/57), done.\u001b[K\n",
            "remote: Compressing objects: 100% (33/33), done.\u001b[K\n",
            "remote: Total 465 (delta 32), reused 47 (delta 24), pack-reused 408\u001b[K\n",
            "Receiving objects: 100% (465/465), 1.12 GiB | 21.88 MiB/s, done.\n",
            "Resolving deltas: 100% (267/267), done.\n",
            "/bin/bash: /usr/local/lib/libtinfo.so.6: no version information available (required by /bin/bash)\n",
            "Cloning into 'speech_fsmn_vad_zh-cn-16k-common-pytorch'...\n",
            "remote: Enumerating objects: 180, done.\u001b[K\n",
            "remote: Counting objects: 100% (35/35), done.\u001b[K\n",
            "remote: Compressing objects: 100% (25/25), done.\u001b[K\n",
            "remote: Total 180 (delta 16), reused 23 (delta 10), pack-reused 145\u001b[K\n",
            "Receiving objects: 100% (180/180), 4.66 MiB | 19.15 MiB/s, done.\n",
            "Resolving deltas: 100% (89/89), done.\n",
            "/bin/bash: /usr/local/lib/libtinfo.so.6: no version information available (required by /bin/bash)\n",
            "Cloning into 'punc_ct-transformer_zh-cn-common-vocab272727-pytorch'...\n",
            "remote: Enumerating objects: 167, done.\u001b[K\n",
            "remote: Counting objects: 100% (47/47), done.\u001b[K\n",
            "remote: Compressing objects: 100% (33/33), done.\u001b[K\n",
            "remote: Total 167 (delta 23), reused 30 (delta 14), pack-reused 120\u001b[K\n",
            "Receiving objects: 100% (167/167), 257.56 MiB | 33.83 MiB/s, done.\n",
            "Resolving deltas: 100% (84/84), done.\n",
            "/content/GPT-SoVITS/tools/uvr5\n",
            "/bin/bash: /usr/local/lib/libtinfo.so.6: no version information available (required by /bin/bash)\n",
            "Cloning into 'uvr5_weights'...\n",
            "remote: Enumerating objects: 15, done.\u001b[K\n",
            "remote: Counting objects: 100% (12/12), done.\u001b[K\n",
            "remote: Compressing objects: 100% (11/11), done.\u001b[K\n",
            "remote: Total 15 (delta 1), reused 0 (delta 0), pack-reused 3\u001b[K\n",
            "Unpacking objects: 100% (15/15), 3.25 KiB | 1.08 MiB/s, done.\n",
            "Filtering content: 100% (9/9), 594.44 MiB | 59.61 MiB/s, done.\n",
            "/bin/bash: /usr/local/lib/libtinfo.so.6: no version information available (required by /bin/bash)\n",
            "/bin/bash: /usr/local/lib/libtinfo.so.6: no version information available (required by /bin/bash)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# @title launch WebUI 启动WebUI\n",
        "!/usr/local/bin/pip install ipykernel\n",
        "!sed -i '9s/False/True/' /content/GPT-SoVITS/config.py\n",
        "%cd /content/GPT-SoVITS/\n",
        "!/usr/local/bin/python  webui.py"
      ],
      "metadata": {
        "id": "4oRGUzkrk8C7",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "caa7fbfd-6ab8-4f27-ec05-99a631566c56"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "不存在:/content/GPT-SoVITS/output\n",
            "Backup is running in the background...\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "/bin/bash: /usr/local/lib/libtinfo.so.6: no version information available (required by /bin/bash)\n",
            "不存在:/content/GPT-SoVITS/output\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "Requirement already satisfied: ipykernel in /usr/local/lib/python3.9/site-packages (6.29.0)\n",
            "Requirement already satisfied: comm>=0.1.1 in /usr/local/lib/python3.9/site-packages (from ipykernel) (0.2.1)\n",
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            "Requirement already satisfied: ipython>=7.23.1 in /usr/local/lib/python3.9/site-packages (from ipykernel) (8.18.1)\n",
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            "Requirement already satisfied: packaging in /usr/local/lib/python3.9/site-packages (from ipykernel) (23.1)\n",
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            "Requirement already satisfied: ptyprocess>=0.5 in /usr/local/lib/python3.9/site-packages (from pexpect>4.3->ipython>=7.23.1->ipykernel) (0.7.0)\n",
            "Requirement already satisfied: wcwidth in /usr/local/lib/python3.9/site-packages (from prompt-toolkit<3.1.0,>=3.0.41->ipython>=7.23.1->ipykernel) (0.2.13)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.9/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.12->ipykernel) (1.16.0)\n",
            "Requirement already satisfied: executing>=1.2.0 in /usr/local/lib/python3.9/site-packages (from stack-data->ipython>=7.23.1->ipykernel) (2.0.1)\n",
            "Requirement already satisfied: asttokens>=2.1.0 in /usr/local/lib/python3.9/site-packages (from stack-data->ipython>=7.23.1->ipykernel) (2.4.1)\n",
            "Requirement already satisfied: pure-eval in /usr/local/lib/python3.9/site-packages (from stack-data->ipython>=7.23.1->ipykernel) (0.2.2)\n",
            "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
            "\u001b[0m/bin/bash: /usr/local/lib/libtinfo.so.6: no version information available (required by /bin/bash)\n",
            "/content/GPT-SoVITS\n",
            "/bin/bash: /usr/local/lib/libtinfo.so.6: no version information available (required by /bin/bash)\n",
            "不存在:/content/GPT-SoVITS/output\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "不存在:/content/GPT-SoVITS/output\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "Running on local URL:  http://0.0.0.0:9874\n",
            "不存在:/content/GPT-SoVITS/output\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "不存在:/content/GPT-SoVITS/output\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "Running on public URL: https://16f3dc1e85e36b92c5.gradio.live\n",
            "不存在:/content/GPT-SoVITS/output\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "不存在:/content/GPT-SoVITS/output\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "不存在:/content/GPT-SoVITS/output\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "不存在:/content/GPT-SoVITS/output\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "不存在:/content/GPT-SoVITS/output\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "不存在:/content/GPT-SoVITS/output\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "不存在:/content/GPT-SoVITS/output\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "不存在:/content/GPT-SoVITS/output\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "不存在:/content/GPT-SoVITS/output\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "不存在:/content/GPT-SoVITS/output\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "不存在:/content/GPT-SoVITS/output\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "不存在:/content/GPT-SoVITS/output\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "不存在:/content/GPT-SoVITS/output\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "不存在:/content/GPT-SoVITS/output\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "不存在:/content/GPT-SoVITS/output\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "不存在:/content/GPT-SoVITS/output\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "不存在:/content/GPT-SoVITS/output\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "不存在:/content/GPT-SoVITS/output\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "不存在:/content/GPT-SoVITS/output\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "不存在:/content/GPT-SoVITS/output\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "不存在:/content/GPT-SoVITS/output\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "不存在:/content/GPT-SoVITS/output\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "不存在:/content/GPT-SoVITS/output\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "不存在:/content/GPT-SoVITS/output\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "不存在:/content/GPT-SoVITS/output\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "不存在:/content/GPT-SoVITS/output\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "不存在:/content/GPT-SoVITS/output\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "不存在:/content/GPT-SoVITS/output\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "\"/usr/local/bin/python\" tools/slice_audio.py \"/content/drive/MyDrive/gpt-SoVITS/【音频】【同学你好，我能叉你一下吗】感觉自己好像脑袋不太好使… (1).wav\" \"output/slicer_opt\" -34 4000 300 10 500 0.9 0.25 0 1\n",
            "执行完毕，请检查输出文件\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "\"/usr/local/bin/python\" tools/damo_asr/cmd-asr.py \"/content/GPT-SoVITS/output/slicer_opt\"\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "Please install rotary_embedding_torch by: \n",
            " pip install -U rotary_embedding_torch\n",
            "Please install rotary_embedding_torch by: \n",
            " pip install -U rotary_embedding_torch\n",
            "Please install rotary_embedding_torch by: \n",
            " pip install -U rotary_embedding_torch\n",
            "Please install rotary_embedding_torch by: \n",
            " pip install -U rotary_embedding_torch\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "  0% 0/1 [00:00<?, ?it/s]output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "rtf_avg: 0.057: 100% 1/1 [00:00<00:00,  1.80it/s]\n",
            "time cost vad: 0.557\n",
            "  0% 0/1 [00:00<?, ?it/s]output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "rtf_avg: 0.173, time_speech:  9.710, time_escape: 1.680: 100% 1/1 [00:01<00:00,  1.70s/it]\n",
            "rtf_avg: 0.011: 100% 1/1 [00:00<00:00, 12.39it/s]\n",
            "time cost vad: 0.081\n",
            "rtf_avg: 0.017, time_speech:  7.290, time_escape: 0.125: 100% 1/1 [00:00<00:00,  7.24it/s]\n",
            "rtf_avg: 0.012: 100% 1/1 [00:00<00:00,  8.93it/s]\n",
            "time cost vad: 0.112\n",
            "rtf_avg: 0.014, time_speech:  9.350, time_escape: 0.130: 100% 1/1 [00:00<00:00,  6.79it/s]\n",
            "rtf_avg: 0.013: 100% 1/1 [00:00<00:00,  7.83it/s]\n",
            "time cost vad: 0.128\n",
            "rtf_avg: 0.018, time_speech:  9.900, time_escape: 0.176: 100% 1/1 [00:00<00:00,  4.95it/s]\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "\"/usr/local/bin/python\" GPT_SoVITS/prepare_datasets/1-get-text.py\n",
            "\"/usr/local/bin/python\" GPT_SoVITS/prepare_datasets/1-get-text.py\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Exception in thread Thread-11 (backup_files):\n",
            "Traceback (most recent call last):\n",
            "  File \"/usr/lib/python3.10/threading.py\", line 1016, in _bootstrap_inner\n",
            "    self.run()\n",
            "  File \"/usr/lib/python3.10/threading.py\", line 953, in run\n",
            "    self._target(*self._args, **self._kwargs)\n",
            "  File \"<ipython-input-3-967f5acab284>\", line 20, in backup_files\n",
            "  File \"/usr/lib/python3.10/shutil.py\", line 559, in copytree\n",
            "    return _copytree(entries=entries, src=src, dst=dst, symlinks=symlinks,\n",
            "  File \"/usr/lib/python3.10/shutil.py\", line 513, in _copytree\n",
            "    raise Error(errors)\n",
            "shutil.Error: [('/content/GPT-SoVITS/output/slicer_opt/【音频】【同学你好，我能叉你一下吗】感觉自己好像脑袋不太好使… (1).wav_0000844800_0001161600.wav', '/content/drive/MyDrive/gpt-SoVITS/b站某up/output/slicer_opt/【音频】【同学你好，我能叉你一下吗】感觉自己好像脑袋不太好使… (1).wav_0000844800_0001161600.wav', '[Errno 2] No such file or directory'), (<DirEntry 'slicer_opt'>, '/content/drive/MyDrive/gpt-SoVITS/b站某up/output/slicer_opt', '[Errno 2] No such file or directory'), ('/content/GPT-SoVITS/output', '/content/drive/MyDrive/gpt-SoVITS/b站某up/output', '[Errno 2] No such file or directory')]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "[nltk_data] Downloading package averaged_perceptron_tagger to\n",
            "[nltk_data]     /root/nltk_data...\n",
            "[nltk_data] Downloading package averaged_perceptron_tagger to\n",
            "[nltk_data]     /root/nltk_data...\n",
            "[nltk_data]   Unzipping taggers/averaged_perceptron_tagger.zip.\n",
            "[nltk_data]   Unzipping taggers/averaged_perceptron_tagger.zip.\n",
            "[nltk_data] Downloading package cmudict to /root/nltk_data...\n",
            "[nltk_data] Downloading package cmudict to /root/nltk_data...\n",
            "[nltk_data]   Unzipping corpora/cmudict.zip.\n",
            "[nltk_data]   Unzipping corpora/cmudict.zip.\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "Building prefix dict from the default dictionary ...\n",
            "Building prefix dict from the default dictionary ...\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "Dumping model to file cache /content/GPT-SoVITS/TEMP/jieba.cache\n",
            "Dumping model to file cache /content/GPT-SoVITS/TEMP/jieba.cache\n",
            "Loading model cost 2.182 seconds.\n",
            "Prefix dict has been built succesfully.\n",
            "Loading model cost 2.341 seconds.\n",
            "Prefix dict has been built succesfully.\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "\"/usr/local/bin/python\" GPT_SoVITS/prepare_datasets/2-get-hubert-wav32k.py\n",
            "\"/usr/local/bin/python\" GPT_SoVITS/prepare_datasets/2-get-hubert-wav32k.py\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "Some weights of the model checkpoint at GPT_SoVITS/pretrained_models/chinese-hubert-base were not used when initializing HubertModel: ['encoder.pos_conv_embed.conv.weight_g', 'encoder.pos_conv_embed.conv.weight_v']\n",
            "- This IS expected if you are initializing HubertModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n",
            "- This IS NOT expected if you are initializing HubertModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n",
            "Some weights of the model checkpoint at GPT_SoVITS/pretrained_models/chinese-hubert-base were not used when initializing HubertModel: ['encoder.pos_conv_embed.conv.weight_g', 'encoder.pos_conv_embed.conv.weight_v']\n",
            "- This IS expected if you are initializing HubertModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n",
            "- This IS NOT expected if you are initializing HubertModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n",
            "Some weights of HubertModel were not initialized from the model checkpoint at GPT_SoVITS/pretrained_models/chinese-hubert-base and are newly initialized: ['encoder.pos_conv_embed.conv.parametrizations.weight.original0', 'encoder.pos_conv_embed.conv.parametrizations.weight.original1']\n",
            "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n",
            "Some weights of HubertModel were not initialized from the model checkpoint at GPT_SoVITS/pretrained_models/chinese-hubert-base and are newly initialized: ['encoder.pos_conv_embed.conv.parametrizations.weight.original0', 'encoder.pos_conv_embed.conv.parametrizations.weight.original1']\n",
            "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "\"/usr/local/bin/python\" GPT_SoVITS/prepare_datasets/3-get-semantic.py\n",
            "\"/usr/local/bin/python\" GPT_SoVITS/prepare_datasets/3-get-semantic.py\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "/usr/local/lib/python3.9/site-packages/torch/nn/utils/weight_norm.py:28: UserWarning: torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.\n",
            "  warnings.warn(\"torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.\")\n",
            "/usr/local/lib/python3.9/site-packages/torch/nn/utils/weight_norm.py:28: UserWarning: torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.\n",
            "  warnings.warn(\"torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.\")\n",
            "<All keys matched successfully>\n",
            "<All keys matched successfully>\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "\"/usr/local/bin/python\" GPT_SoVITS/s2_train.py --config \"/content/GPT-SoVITS/TEMP/tmp_s2.json\"\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "INFO:xxx:{'train': {'log_interval': 100, 'eval_interval': 500, 'seed': 1234, 'epochs': 8, 'learning_rate': 0.0001, 'betas': [0.8, 0.99], 'eps': 1e-09, 'batch_size': 12, 'fp16_run': True, 'lr_decay': 0.999875, 'segment_size': 20480, 'init_lr_ratio': 1, 'warmup_epochs': 0, 'c_mel': 45, 'c_kl': 1.0, 'text_low_lr_rate': 0.4, 'pretrained_s2G': 'GPT_SoVITS/pretrained_models/s2G488k.pth', 'pretrained_s2D': 'GPT_SoVITS/pretrained_models/s2D488k.pth', 'if_save_latest': True, 'if_save_every_weights': True, 'save_every_epoch': 4, 'gpu_numbers': '0'}, 'data': {'max_wav_value': 32768.0, 'sampling_rate': 32000, 'filter_length': 2048, 'hop_length': 640, 'win_length': 2048, 'n_mel_channels': 128, 'mel_fmin': 0.0, 'mel_fmax': None, 'add_blank': True, 'n_speakers': 300, 'cleaned_text': True, 'exp_dir': 'logs/xxx'}, 'model': {'inter_channels': 192, 'hidden_channels': 192, 'filter_channels': 768, 'n_heads': 2, 'n_layers': 6, 'kernel_size': 3, 'p_dropout': 0.1, 'resblock': '1', 'resblock_kernel_sizes': [3, 7, 11], 'resblock_dilation_sizes': [[1, 3, 5], [1, 3, 5], [1, 3, 5]], 'upsample_rates': [10, 8, 2, 2, 2], 'upsample_initial_channel': 512, 'upsample_kernel_sizes': [16, 16, 8, 2, 2], 'n_layers_q': 3, 'use_spectral_norm': False, 'gin_channels': 512, 'semantic_frame_rate': '25hz', 'freeze_quantizer': True}, 's2_ckpt_dir': 'logs/xxx', 'content_module': 'cnhubert', 'save_weight_dir': 'SoVITS_weights', 'name': 'xxx', 'pretrain': None, 'resume_step': None}\n",
            "phoneme_data_len: 4\n",
            "wav_data_len: 100\n",
            "100% 100/100 [00:00<00:00, 70433.32it/s]\n",
            "skipped_phone:  0 , skipped_dur:  0\n",
            "total left:  100\n",
            "/usr/local/lib/python3.9/site-packages/torch/utils/data/dataloader.py:558: UserWarning: This DataLoader will create 6 worker processes in total. Our suggested max number of worker in current system is 2, which is smaller than what this DataLoader is going to create. Please be aware that excessive worker creation might get DataLoader running slow or even freeze, lower the worker number to avoid potential slowness/freeze if necessary.\n",
            "  warnings.warn(_create_warning_msg(\n",
            "/usr/local/lib/python3.9/site-packages/torch/nn/utils/weight_norm.py:28: UserWarning: torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.\n",
            "  warnings.warn(\"torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.\")\n",
            "ssl_proj.weight not requires_grad\n",
            "ssl_proj.bias not requires_grad\n",
            "INFO:xxx:loaded pretrained GPT_SoVITS/pretrained_models/s2G488k.pth\n",
            "<All keys matched successfully>\n",
            "INFO:xxx:loaded pretrained GPT_SoVITS/pretrained_models/s2D488k.pth\n",
            "<All keys matched successfully>\n",
            "/usr/local/lib/python3.9/site-packages/torch/optim/lr_scheduler.py:143: UserWarning: Detected call of `lr_scheduler.step()` before `optimizer.step()`. In PyTorch 1.1.0 and later, you should call them in the opposite order: `optimizer.step()` before `lr_scheduler.step()`.  Failure to do this will result in PyTorch skipping the first value of the learning rate schedule. See more details at https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate\n",
            "  warnings.warn(\"Detected call of `lr_scheduler.step()` before `optimizer.step()`. \"\n",
            "/usr/local/lib/python3.9/site-packages/torch/utils/data/dataloader.py:558: UserWarning: This DataLoader will create 6 worker processes in total. Our suggested max number of worker in current system is 2, which is smaller than what this DataLoader is going to create. Please be aware that excessive worker creation might get DataLoader running slow or even freeze, lower the worker number to avoid potential slowness/freeze if necessary.\n",
            "  warnings.warn(_create_warning_msg(\n",
            "0it [00:00, ?it/s]output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "/usr/local/lib/python3.9/site-packages/torch/functional.py:660: UserWarning: stft with return_complex=False is deprecated. In a future pytorch release, stft will return complex tensors for all inputs, and return_complex=False will raise an error.\n",
            "Note: you can still call torch.view_as_real on the complex output to recover the old return format. (Triggered internally at ../aten/src/ATen/native/SpectralOps.cpp:874.)\n",
            "  return _VF.stft(input, n_fft, hop_length, win_length, window,  # type: ignore[attr-defined]\n",
            "/usr/local/lib/python3.9/site-packages/torch/functional.py:660: UserWarning: stft with return_complex=False is deprecated. In a future pytorch release, stft will return complex tensors for all inputs, and return_complex=False will raise an error.\n",
            "Note: you can still call torch.view_as_real on the complex output to recover the old return format. (Triggered internally at ../aten/src/ATen/native/SpectralOps.cpp:874.)\n",
            "  return _VF.stft(input, n_fft, hop_length, win_length, window,  # type: ignore[attr-defined]\n",
            "/usr/local/lib/python3.9/site-packages/torch/functional.py:660: UserWarning: stft with return_complex=False is deprecated. In a future pytorch release, stft will return complex tensors for all inputs, and return_complex=False will raise an error.\n",
            "Note: you can still call torch.view_as_real on the complex output to recover the old return format. (Triggered internally at ../aten/src/ATen/native/SpectralOps.cpp:874.)\n",
            "  return _VF.stft(input, n_fft, hop_length, win_length, window,  # type: ignore[attr-defined]\n",
            "/usr/local/lib/python3.9/site-packages/torch/functional.py:660: UserWarning: stft with return_complex=False is deprecated. In a future pytorch release, stft will return complex tensors for all inputs, and return_complex=False will raise an error.\n",
            "Note: you can still call torch.view_as_real on the complex output to recover the old return format. (Triggered internally at ../aten/src/ATen/native/SpectralOps.cpp:874.)\n",
            "  return _VF.stft(input, n_fft, hop_length, win_length, window,  # type: ignore[attr-defined]\n",
            "/usr/local/lib/python3.9/site-packages/torch/functional.py:660: UserWarning: stft with return_complex=False is deprecated. In a future pytorch release, stft will return complex tensors for all inputs, and return_complex=False will raise an error.\n",
            "Note: you can still call torch.view_as_real on the complex output to recover the old return format. (Triggered internally at ../aten/src/ATen/native/SpectralOps.cpp:874.)\n",
            "  return _VF.stft(input, n_fft, hop_length, win_length, window,  # type: ignore[attr-defined]\n",
            "/usr/local/lib/python3.9/site-packages/torch/functional.py:660: UserWarning: stft with return_complex=False is deprecated. In a future pytorch release, stft will return complex tensors for all inputs, and return_complex=False will raise an error.\n",
            "Note: you can still call torch.view_as_real on the complex output to recover the old return format. (Triggered internally at ../aten/src/ATen/native/SpectralOps.cpp:874.)\n",
            "  return _VF.stft(input, n_fft, hop_length, win_length, window,  # type: ignore[attr-defined]\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "[rank0]:[W reducer.cpp:1360] Warning: find_unused_parameters=True was specified in DDP constructor, but did not find any unused parameters in the forward pass. This flag results in an extra traversal of the autograd graph every iteration,  which can adversely affect performance. If your model indeed never has any unused parameters in the forward pass, consider turning this flag off. Note that this warning may be a false positive if your model has flow control causing later iterations to have unused parameters. (function operator())\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "/usr/local/lib/python3.9/site-packages/torch/functional.py:660: UserWarning: stft with return_complex=False is deprecated. In a future pytorch release, stft will return complex tensors for all inputs, and return_complex=False will raise an error.\n",
            "Note: you can still call torch.view_as_real on the complex output to recover the old return format. (Triggered internally at ../aten/src/ATen/native/SpectralOps.cpp:874.)\n",
            "  return _VF.stft(input, n_fft, hop_length, win_length, window,  # type: ignore[attr-defined]\n",
            "/usr/local/lib/python3.9/site-packages/torch/functional.py:660: UserWarning: ComplexHalf support is experimental and many operators don't support it yet. (Triggered internally at ../aten/src/ATen/EmptyTensor.cpp:30.)\n",
            "  return _VF.stft(input, n_fft, hop_length, win_length, window,  # type: ignore[attr-defined]\n",
            "/usr/local/lib/python3.9/site-packages/torch/autograd/__init__.py:266: UserWarning: Grad strides do not match bucket view strides. This may indicate grad was not created according to the gradient layout contract, or that the param's strides changed since DDP was constructed.  This is not an error, but may impair performance.\n",
            "grad.sizes() = [1, 9, 96], strides() = [70176, 96, 1]\n",
            "bucket_view.sizes() = [1, 9, 96], strides() = [864, 96, 1] (Triggered internally at ../torch/csrc/distributed/c10d/reducer.cpp:322.)\n",
            "  Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass\n",
            "INFO:xxx:Train Epoch: 1 [0%]\n",
            "INFO:xxx:[3.030667781829834, 1.7712655067443848, 8.140056610107422, 27.30544090270996, 0.8134536743164062, 1.5707759857177734, 0, 9.99875e-05]\n",
            "1it [00:36, 36.87s/it]output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "6it [00:42,  3.01s/it]output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "10it [00:46,  4.62s/it]\n",
            "INFO:xxx:====> Epoch: 1\n",
            "0it [00:00, ?it/s]output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "2it [00:11,  5.51s/it]output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "8it [00:17,  1.14s/it]output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "10it [00:18,  1.90s/it]\n",
            "INFO:xxx:====> Epoch: 2\n",
            "0it [00:00, ?it/s]output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "4it [00:14,  2.36s/it]output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "10it [00:19,  1.90s/it]\n",
            "INFO:xxx:====> Epoch: 3\n",
            "0it [00:00, ?it/s]output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "1it [00:10, 10.61s/it]output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "6it [00:15,  1.50s/it]output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "10it [00:19,  1.93s/it]\n",
            "INFO:xxx:Saving model and optimizer state at iteration 4 to logs/xxx/logs_s2/G_233333333333.pth\n",
            "INFO:xxx:Saving model and optimizer state at iteration 4 to logs/xxx/logs_s2/D_233333333333.pth\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "INFO:xxx:saving ckpt xxx_e4:Success.\n",
            "INFO:xxx:====> Epoch: 4\n",
            "0it [00:00, ?it/s]output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "1it [00:07,  7.58s/it]output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "2it [00:09,  4.20s/it]SoVITS_weights:Backup completed!\n",
            "7it [00:14,  1.25s/it]output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "10it [00:17,  1.78s/it]\n",
            "INFO:xxx:====> Epoch: 5\n",
            "0it [00:00, ?it/s]output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "2it [00:09,  4.30s/it]output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "7it [00:15,  1.33s/it]output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "10it [00:18,  1.82s/it]\n",
            "INFO:xxx:====> Epoch: 6\n",
            "0it [00:00, ?it/s]output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "1it [00:08,  8.55s/it]output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "5it [00:15,  1.96s/it]output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "10it [00:19,  1.95s/it]\n",
            "INFO:xxx:====> Epoch: 7\n",
            "0it [00:00, ?it/s]output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "2it [00:13,  6.38s/it]output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "8it [00:19,  1.24s/it]output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "10it [00:21,  2.11s/it]\n",
            "INFO:xxx:Saving model and optimizer state at iteration 8 to logs/xxx/logs_s2/G_233333333333.pth\n",
            "INFO:xxx:Saving model and optimizer state at iteration 8 to logs/xxx/logs_s2/D_233333333333.pth\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "INFO:xxx:saving ckpt xxx_e8:Success.\n",
            "INFO:xxx:====> Epoch: 8\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "\"/usr/local/bin/python\" GPT_SoVITS/s1_train.py --config_file \"/content/GPT-SoVITS/TEMP/tmp_s1.yaml\" \n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "Seed set to 1234\n",
            "Using 16bit Automatic Mixed Precision (AMP)\n",
            "GPU available: True (cuda), used: True\n",
            "TPU available: False, using: 0 TPU cores\n",
            "IPU available: False, using: 0 IPUs\n",
            "HPU available: False, using: 0 HPUs\n",
            "<All keys matched successfully>\n",
            "ckpt_path: None\n",
            "[rank: 0] Seed set to 1234\n",
            "Initializing distributed: GLOBAL_RANK: 0, MEMBER: 1/1\n",
            "----------------------------------------------------------------------------------------------------\n",
            "distributed_backend=nccl\n",
            "All distributed processes registered. Starting with 1 processes\n",
            "----------------------------------------------------------------------------------------------------\n",
            "\n",
            "Missing logger folder: logs/xxx/logs_s1/logs_s1\n",
            "semantic_data_len: 4\n",
            "phoneme_data_len: 4\n",
            "                                           item_name                                     semantic_audio\n",
            "0  【音频】【同学你好，我能叉你一下吗】感觉自己好像脑袋不太好使… (1).wav_000000...  536 536 334 334 103 844 944 847 476 728 641 45...\n",
            "1  【音频】【同学你好，我能叉你一下吗】感觉自己好像脑袋不太好使… (1).wav_000054...  774 936 581 582 581 638 638 263 1005 263 263 3...\n",
            "2  【音频】【同学你好，我能叉你一下吗】感觉自己好像脑袋不太好使… (1).wav_000031...  634 696 565 338 565 334 185 27 134 634 634 738...\n",
            "3  【音频】【同学你好，我能叉你一下吗】感觉自己好像脑袋不太好使… (1).wav_000084...  175 844 248 203 1005 565 631 680 313 711 97 71...\n",
            "dataset.__len__(): 100\n",
            "LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]\n",
            "\n",
            "  | Name  | Type                 | Params\n",
            "-----------------------------------------------\n",
            "0 | model | Text2SemanticDecoder | 77.5 M\n",
            "-----------------------------------------------\n",
            "77.5 M    Trainable params\n",
            "0         Non-trainable params\n",
            "77.5 M    Total params\n",
            "309.975   Total estimated model params size (MB)\n",
            "/usr/local/lib/python3.9/site-packages/torch/utils/data/dataloader.py:558: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, which is smaller than what this DataLoader is going to create. Please be aware that excessive worker creation might get DataLoader running slow or even freeze, lower the worker number to avoid potential slowness/freeze if necessary.\n",
            "  warnings.warn(_create_warning_msg(\n",
            "/usr/local/lib/python3.9/site-packages/pytorch_lightning/loops/fit_loop.py:293: The number of training batches (9) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.\n",
            "Epoch 0:   0% 0/9 [00:00<?, ?it/s] output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "Epoch 1:   0% 0/9 [00:00<?, ?it/s, v_num=0, total_loss_step=4.99e+3, lr_step=0.002, top_3_acc_step=0.117, total_loss_epoch=1.37e+4, lr_epoch=0.00488, top_3_acc_epoch=0.123]output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "Epoch 3:   0% 0/9 [00:00<?, ?it/s, v_num=0, total_loss_step=4.71e+3, lr_step=0.002, top_3_acc_step=0.122, total_loss_epoch=1.37e+4, lr_epoch=0.002, top_3_acc_epoch=0.124]output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "Epoch 4:   0% 0/9 [00:00<?, ?it/s, v_num=0, total_loss_step=4.71e+3, lr_step=0.002, top_3_acc_step=0.110, total_loss_epoch=1.37e+4, lr_epoch=0.002, top_3_acc_epoch=0.123]SoVITS_weights:Backup completed!\n",
            "Epoch 4: 100% 9/9 [00:02<00:00,  3.14it/s, v_num=0, total_loss_step=4.39e+3, lr_step=0.002, top_3_acc_step=0.125, total_loss_epoch=1.37e+4, lr_epoch=0.002, top_3_acc_epoch=0.123]output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "Epoch 6:   0% 0/9 [00:00<?, ?it/s, v_num=0, total_loss_step=5.02e+3, lr_step=0.002, top_3_acc_step=0.121, total_loss_epoch=1.36e+4, lr_epoch=0.002, top_3_acc_epoch=0.128]output:Backup completed!\n",
            "Epoch 7:   0% 0/9 [00:00<?, ?it/s, v_num=0, total_loss_step=4.64e+3, lr_step=0.002, top_3_acc_step=0.140, total_loss_epoch=1.3e+4, lr_epoch=0.002, top_3_acc_epoch=0.152]GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "Epoch 9:   0% 0/9 [00:00<?, ?it/s, v_num=0, total_loss_step=3.66e+3, lr_step=0.002, top_3_acc_step=0.284, total_loss_epoch=1.12e+4, lr_epoch=0.002, top_3_acc_epoch=0.250]output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "Epoch 9: 100% 9/9 [00:03<00:00,  2.60it/s, v_num=0, total_loss_step=3.42e+3, lr_step=0.002, top_3_acc_step=0.341, total_loss_epoch=1.01e+4, lr_epoch=0.002, top_3_acc_epoch=0.328]output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "Epoch 10:   0% 0/9 [00:00<?, ?it/s, v_num=0, total_loss_step=3.42e+3, lr_step=0.002, top_3_acc_step=0.341, total_loss_epoch=1.01e+4, lr_epoch=0.002, top_3_acc_epoch=0.328]SoVITS_weights:Backup completed!\n",
            "Epoch 12:   0% 0/9 [00:00<?, ?it/s, v_num=0, total_loss_step=2.35e+3, lr_step=0.002, top_3_acc_step=0.618, total_loss_epoch=7.59e+3, lr_epoch=0.002, top_3_acc_epoch=0.542]output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "Epoch 14:   0% 0/9 [00:00<?, ?it/s, v_num=0, total_loss_step=1.52e+3, lr_step=0.002, top_3_acc_step=0.822, total_loss_epoch=4.83e+3, lr_epoch=0.002, top_3_acc_epoch=0.787]SoVITS_weights:Backup completed!\n",
            "Epoch 14: 100% 9/9 [00:02<00:00,  3.14it/s, v_num=0, total_loss_step=1.16e+3, lr_step=0.002, top_3_acc_step=0.917, total_loss_epoch=3.67e+3, lr_epoch=0.002, top_3_acc_epoch=0.879]output:Backup completed!\n",
            "`Trainer.fit` stopped: `max_epochs=15` reached.\n",
            "Epoch 14: 100% 9/9 [00:16<00:00,  1.83s/it, v_num=0, total_loss_step=1.16e+3, lr_step=0.002, top_3_acc_step=0.917, total_loss_epoch=3.67e+3, lr_epoch=0.002, top_3_acc_epoch=0.879]\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "\"/usr/local/bin/python\" GPT_SoVITS/inference_webui.py\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "DEBUG:torio._extension.utils:Loading FFmpeg6\n",
            "DEBUG:torio._extension.utils:Successfully loaded FFmpeg6\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "Some weights of the model checkpoint at GPT_SoVITS/pretrained_models/chinese-hubert-base were not used when initializing HubertModel: ['encoder.pos_conv_embed.conv.weight_g', 'encoder.pos_conv_embed.conv.weight_v']\n",
            "- This IS expected if you are initializing HubertModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n",
            "- This IS NOT expected if you are initializing HubertModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n",
            "Some weights of HubertModel were not initialized from the model checkpoint at GPT_SoVITS/pretrained_models/chinese-hubert-base and are newly initialized: ['encoder.pos_conv_embed.conv.parametrizations.weight.original0', 'encoder.pos_conv_embed.conv.parametrizations.weight.original1']\n",
            "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n",
            "GPT_weights:Backup completed!\n",
            "/usr/local/lib/python3.9/site-packages/torch/nn/utils/weight_norm.py:28: UserWarning: torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.\n",
            "  warnings.warn(\"torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.\")\n",
            "SoVITS_weights:Backup completed!\n",
            "<All keys matched successfully>\n",
            "Number of parameter: 77.49M\n",
            "Running on local URL:  http://0.0.0.0:9872\n",
            "Running on public URL: https://dc3821667d70272efc.gradio.live\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "Keyboard interruption in main thread... closing server.\n",
            "Keyboard interruption in main thread... closing server.\n",
            "Killing tunnel 0.0.0.0:9872 <> https://dc3821667d70272efc.gradio.live\n",
            "Error in atexit._run_exitfuncs:\n",
            "Traceback (most recent call last):\n",
            "  File \"/usr/local/lib/python3.9/site-packages/matplotlib/_pylab_helpers.py\", line 77, in destroy_all\n",
            "    @classmethod\n",
            "KeyboardInterrupt\n",
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "^C\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [],
      "metadata": {
        "id": "UFZGr1ZVUrJb"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import threading\n",
        "import os\n",
        "import time\n",
        "import shutil\n",
        "source_directory = \"/content/GPT-SoVITS/output,/content/GPT-SoVITS/GPT_weights,/content/GPT-SoVITS/SoVITS_weights\"#@param {type:\"string\"}\n",
        "destination_directory = \"/content/drive/MyDrive/gpt-SoVITS/b\\u7AD9\\u67D0up\"#@param {type:\"string\"}\n",
        "def backup_files(source, destination):\n",
        "    \"\"\"\n",
        "    Function to backup files from source to destination.\n",
        "    \"\"\"\n",
        "    for filepath in source:\n",
        "        name = os.path.basename(filepath)\n",
        "        des_path = os.path.join(destination,name)\n",
        "        if os.path.exists(des_path):\n",
        "            shutil.rmtree(des_path)\n",
        "        if not os.path.exists(filepath):\n",
        "            print(f\"不存在:{filepath}\")\n",
        "            continue\n",
        "        shutil.copytree(filepath, des_path)\n",
        "        print(f\"{name}:Backup completed!\")\n",
        "\n",
        "# 创建并启动备份文件的线程\n",
        "source_file = []\n",
        "if source_directory.split(\",\") == None:\n",
        "    source_file.append(source_directory)\n",
        "else:\n",
        "    source_file = source_directory.split(\",\")\n",
        "\n",
        "backup_files(source_file, destination_directory)\n",
        "print(\"Backup is running in the background...\")\n",
        "\n"
      ],
      "metadata": {
        "id": "VrfF2WorUs6U",
        "outputId": "3798f5ec-d653-40c0-ab2b-e9ff06fd1b26",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "output:Backup completed!\n",
            "GPT_weights:Backup completed!\n",
            "SoVITS_weights:Backup completed!\n",
            "Backup is running in the background...\n"
          ]
        }
      ]
    }
  ]
}