Google_Colab_Notebook_Updated.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "private_outputs": true,
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU",
    "gpuClass": "standard"
  },
  "cells": [
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "GmFP6bN9dvOq"
      },
      "outputs": [],
      "source": [
        "#@title Check if the graphics card is present\n",
        "!nvidia-smi"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Install dependencies (you might need to restart the runtime after running the cell)\n",
        "!apt-get -y install build-essential python3-dev ffmpeg\n",
        "!pip3 install --upgrade setuptools wheel\n",
        "!pip3 install --upgrade pip\n",
        "!pip3 install faiss-gpu fairseq gradio ffmpeg ffmpeg-python praat-parselmouth pyworld numpy==1.23.5 numba==0.56.4 librosa==0.9.2 onnxruntime torchcrepe tensorboardX cloud-tpu-client tensorrt"
      ],
      "metadata": {
        "id": "wjddIFr1oS3W"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Clone the main branch of the repository and copy to colab drive\n",
        "\n",
        "!git clone https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI.git\n",
        "%cd /content/Retrieval-based-Voice-Conversion-WebUI\n",
        "!mkdir -p pretrained uvr5_weights"
      ],
      "metadata": {
        "id": "ge_97mfpgqTm"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title You can manually update the repo by pulling it\n",
        "#You don't have to do this unless your files are outdated\n",
        "!git pull"
      ],
      "metadata": {
        "id": "BLDEZADkvlw1"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Install aria2\n",
        "!apt -y install -qq aria2"
      ],
      "metadata": {
        "id": "pqE0PrnuRqI2"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Download the required weights (v1 model)\n",
        "!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/D32k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o D32k.pth\n",
        "!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/D40k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o D40k.pth\n",
        "!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/D48k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o D48k.pth\n",
        "!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/G32k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o G32k.pth\n",
        "!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/G40k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o G40k.pth\n",
        "!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/G48k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o G48k.pth\n",
        "!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0D32k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o f0D32k.pth\n",
        "!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0D40k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o f0D40k.pth\n",
        "!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0D48k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o f0D48k.pth\n",
        "!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0G32k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o f0G32k.pth\n",
        "!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0G40k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o f0G40k.pth\n",
        "!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0G48k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o f0G48k.pth"
      ],
      "metadata": {
        "id": "UG3XpUwEomUz"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Download the V2 pretrained weights (required if you want to use the v2 model)\n",
        "\n",
        "!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/D40k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained_v2 -o D40k.pth\n",
        "!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/G40k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained_v2 -o G40k.pth\n",
        "!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/f0D40k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained_v2 -o f0D40k.pth\n",
        "!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/f0G40k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained_v2 -o f0G40k.pth"
      ],
      "metadata": {
        "id": "hpf9tWVkBlI-"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Download the voice separation module\n",
        "!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/uvr5_weights/HP2-人声vocals+非人声instrumentals.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/uvr5_weights -o HP2-人声vocals+非人声instrumentals.pth\n",
        "!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/uvr5_weights/HP5-主旋律人声vocals+其他instrumentals.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/uvr5_weights -o HP5-主旋律人声vocals+其他instrumentals.pth"
      ],
      "metadata": {
        "id": "HugjmZqZRuiF"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Download hubert_base\n",
        "!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/hubert_base.pt -d /content/Retrieval-based-Voice-Conversion-WebUI -o hubert_base.pt"
      ],
      "metadata": {
        "id": "2RCaT9FTR0ej"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Mount your local google drive\n",
        "\n",
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "id": "jwu07JgqoFON"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Load your training dataset(.zip archive of .wav files) from /content/dataset (modify accordingly)\n",
        "\n",
        "#@markdown Dataset location\n",
        "DATASET = \"/content/drive/MyDrive/dataset/trainsongs.zip\"  #@param {type:\"string\"}\n",
        "\n",
        "!mkdir -p /content/dataset\n",
        "!unzip -d /content/dataset -B {DATASET}"
      ],
      "metadata": {
        "id": "Mwk7Q0Loqzjx"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Remove duplicates and clean-up file names\n",
        "!ls -a /content/dataset/\n",
        "!rename 's/(\\w+)\\.(\\w+)~(\\d*)/$1_$3.$2/' /content/dataset/*.*~*"
      ],
      "metadata": {
        "id": "PDlFxWHWEynD"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Start the web instance (click on the non-localhost url)\n",
        "%cd /content/Retrieval-based-Voice-Conversion-WebUI\n",
        "# %load_ext tensorboard\n",
        "# %tensorboard --logdir /content/Retrieval-based-Voice-Conversion-WebUI/logs\n",
        "!python3 infer-web.py --colab --pycmd python3"
      ],
      "metadata": {
        "id": "7vh6vphDwO0b"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Manually back-up the trained model\n",
        "#@markdown You need to check the file name of the model under the logs folder by yourself, and manually modify the file name and epoch below\n",
        "\n",
        "#@markdown Model name\n",
        "MODELNAME = \"lulu\"  #@param {type:\"string\"}\n",
        "#@markdown Model epoch\n",
        "MODELEPOCH = 7500  #@param {type:\"integer\"}\n",
        "\n",
        "!cp /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/G_{MODELEPOCH}.pth /content/drive/MyDrive/{MODELNAME}_D_{MODELEPOCH}.pth\n",
        "!cp /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/D_{MODELEPOCH}.pth /content/drive/MyDrive/{MODELNAME}_G_{MODELEPOCH}.pth\n",
        "!cp /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/added_*.index /content/drive/MyDrive/\n",
        "!cp /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/total_*.npy /content/drive/MyDrive/\n",
        "\n",
        "!cp /content/Retrieval-based-Voice-Conversion-WebUI/weights/{MODELNAME}.pth /content/drive/MyDrive/{MODELNAME}{MODELEPOCH}.pth"
      ],
      "metadata": {
        "id": "FgJuNeAwx5Y_"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Restore trained model from back-up\n",
        "#@markdown You need to check the file name of the model under the logs folder by yourself, and manually modify the file name and epoch below\n",
        "\n",
        "#@markdown Model name\n",
        "MODELNAME = \"lulu\"  #@param {type:\"string\"}\n",
        "#@markdown Model epoch\n",
        "MODELEPOCH = 7500  #@param {type:\"integer\"}\n",
        "\n",
        "!mkdir -p /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}\n",
        "\n",
        "!cp /content/drive/MyDrive/{MODELNAME}_D_{MODELEPOCH}.pth /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/G_{MODELEPOCH}.pth\n",
        "!cp /content/drive/MyDrive/{MODELNAME}_G_{MODELEPOCH}.pth /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/D_{MODELEPOCH}.pth\n",
        "!cp /content/drive/MyDrive/*.index /content/\n",
        "!cp /content/drive/MyDrive/*.npy /content/\n",
        "!cp /content/drive/MyDrive/{MODELNAME}{MODELEPOCH}.pth /content/Retrieval-based-Voice-Conversion-WebUI/weights/{MODELNAME}.pth"
      ],
      "metadata": {
        "id": "OVQoLQJXS7WX"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Use the cells below only if needed**"
      ],
      "metadata": {
        "id": "GKLXEUQA9QJ0"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Manual preprocessing (not recommended)\n",
        "#@markdown Model Name\n",
        "MODELNAME = \"lulu\"  #@param {type:\"string\"}\n",
        "#@markdown Sampling rate\n",
        "BITRATE = 48000  #@param {type:\"integer\"}\n",
        "#@markdown Thread count\n",
        "THREADCOUNT = 8  #@param {type:\"integer\"}\n",
        "\n",
        "!python3 trainset_preprocess_pipeline_print.py /content/dataset {BITRATE} {THREADCOUNT} logs/{MODELNAME} True\n"
      ],
      "metadata": {
        "id": "ZKAyuKb9J6dz"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Extract features manually\n",
        "#@markdown Model Name\n",
        "MODELNAME = \"lulu\"  #@param {type:\"string\"}\n",
        "#@markdown Thread coun\n",
        "THREADCOUNT = 8  #@param {type:\"integer\"}\n",
        "#@markdown Pitch extraction algorithm\n",
        "ALGO = \"harvest\"  #@param {type:\"string\"}\n",
        "\n",
        "!python3 extract_f0_print.py logs/{MODELNAME} {THREADCOUNT} {ALGO}\n",
        "\n",
        "!python3 extract_feature_print.py cpu 1 0 0 logs/{MODELNAME}\n"
      ],
      "metadata": {
        "id": "CrxJqzAUKmPJ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Manual training (not recommended)\n",
        "#@markdown Model name\n",
        "MODELNAME = \"lulu\"  #@param {type:\"string\"}\n",
        "#@markdown GPU Used\n",
        "USEGPU = \"0\"  #@param {type:\"string\"}\n",
        "#@markdown Batch size\n",
        "BATCHSIZE = 32  #@param {type:\"integer\"}\n",
        "#@markdown Stop epoch\n",
        "MODELEPOCH = 3200  #@param {type:\"integer\"}\n",
        "#@markdown Save epoch interval\n",
        "EPOCHSAVE = 100  #@param {type:\"integer\"}\n",
        "#@markdown Sampling rate\n",
        "MODELSAMPLE = \"48k\"  #@param {type:\"string\"}\n",
        "#@markdown Whether to cache the training set\n",
        "CACHEDATA = 1  #@param {type:\"integer\"}\n",
        "#@markdown Whether to save only the latest ckpt file\n",
        "ONLYLATEST = 0  #@param {type:\"integer\"}\n",
        "\n",
        "!python3 train_nsf_sim_cache_sid_load_pretrain.py -e lulu -sr {MODELSAMPLE} -f0 1 -bs {BATCHSIZE} -g {USEGPU} -te {MODELEPOCH} -se {EPOCHSAVE} -pg pretrained/f0G{MODELSAMPLE}.pth -pd pretrained/f0D{MODELSAMPLE}.pth -l {ONLYLATEST} -c {CACHEDATA}\n"
      ],
      "metadata": {
        "id": "IMLPLKOaKj58"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Delete other .pths, leaving only the selected ones (be careful, read the code)\n",
        "#@markdown Model name\n",
        "MODELNAME = \"lulu\"  #@param {type:\"string\"}\n",
        "#@markdown Selected model epoch\n",
        "MODELEPOCH = 9600  #@param {type:\"integer\"}\n",
        "\n",
        "!echo \"Backing up the selected models...\"\n",
        "!cp /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/G_{MODELEPOCH}.pth /content/{MODELNAME}_D_{MODELEPOCH}.pth\n",
        "!cp /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/D_{MODELEPOCH}.pth /content/{MODELNAME}_G_{MODELEPOCH}.pth\n",
        "\n",
        "!echo \"Deleting...\"\n",
        "!ls /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}\n",
        "!rm /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/*.pth\n",
        "\n",
        "!echo \"Restoring the selected models...\"\n",
        "!mv /content/{MODELNAME}_D_{MODELEPOCH}.pth /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/G_{MODELEPOCH}.pth \n",
        "!mv /content/{MODELNAME}_G_{MODELEPOCH}.pth /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/D_{MODELEPOCH}.pth\n",
        "\n",
        "!echo \"Delete completed\"\n",
        "!ls /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}"
      ],
      "metadata": {
        "id": "haYA81hySuDl"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Clear all files under the project, leaving only the selected model (be careful, read the code)\n",
        "#@markdown Model name\n",
        "MODELNAME = \"lulu\"  #@param {type:\"string\"}\n",
        "#@markdown Selected model epoch\n",
        "MODELEPOCH = 9600  #@param {type:\"integer\"}\n",
        "\n",
        "!echo \"Backing up the selected models...\"\n",
        "!cp /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/G_{MODELEPOCH}.pth /content/{MODELNAME}_D_{MODELEPOCH}.pth\n",
        "!cp /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/D_{MODELEPOCH}.pth /content/{MODELNAME}_G_{MODELEPOCH}.pth\n",
        "\n",
        "!echo \"Deleting...\"\n",
        "!ls /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}\n",
        "!rm -rf /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/*\n",
        "\n",
        "!echo \"Restoring the selected model...\"\n",
        "!mv /content/{MODELNAME}_D_{MODELEPOCH}.pth /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/G_{MODELEPOCH}.pth \n",
        "!mv /content/{MODELNAME}_G_{MODELEPOCH}.pth /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/D_{MODELEPOCH}.pth\n",
        "\n",
        "!echo \"Delete completed\"\n",
        "!ls /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}"
      ],
      "metadata": {
        "id": "QhSiPTVPoIRh"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}