Mainline_Colab_Full_test.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "private_outputs": true,
      "provenance": [],
      "gpuType": "T4",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/hinabl/RVC-Online/blob/main/Mainline_Colab_Full_test.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# <strong>RVC Mainline Colab by: [Hina](https://linktr.ee/_hina__)\n",
        "\n",
        "Thanks and Credits to:<br>\n",
        "[Radical Larry](https://github.com/0RadicalLarry0)<br>\n",
        "[Raven](https://github.com/RavenCutie21)<br>\n",
        "[Litsa](https://ko-fi.com/litsa_the_dancer)<br>\n",
        "[Lusbert](https://github.com/Lusbert)<br>\n",
        "[Nick088](https://linktr.ee/Nick088)\n",
        "\n",
        "\n",
        "Mainline Repo:<br>\n",
        "[Github](https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI)<br>\n",
        "[Huggingface](https://huggingface.co/lj1995/VoiceConversionWebUI)\n",
        "\n",
        "Join the [AI Hub Discord](https://discord.gg/aihub) Community\n",
        "\n",
        "[![](https://count.nett.moe/get/Mainline_Counter/img?theme=rule34)]()"
      ],
      "metadata": {
        "id": "96P3RUqHEoAQ"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "zbGMP1anEVPH"
      },
      "outputs": [],
      "source": [
        "#@title Clone From Github\n",
        "#@markdown ---\n",
        "#@markdown This cell clones from the mainline repo to be used.\n",
        "\n",
        "#@markdown Press the ``UseCustomGui`` toggle to use a different gui.\n",
        "\n",
        "# Imports\n",
        "import os\n",
        "import codecs\n",
        "from IPython.display import clear_output, Javascript\n",
        "\n",
        "# Checks\n",
        "Connected_To_Drive=False\n",
        "Installed_Already=False\n",
        "Run_Cell=0\n",
        "# #@param [\"Raven\",\"Rejecks\"]\n",
        "#@markdown ---\n",
        "Repo = \"Codename0\" #@param [\"Original\",\"Codename0\",\"Fumiama\"]\n",
        "Extra = True #@param {type:\"boolean\"}\n",
        "UseCustomGui = False #@param {type:\"boolean\"}\n",
        "Gui = \"Raven\"\n",
        "\n",
        "#wordarounds\n",
        "if Repo == \"Original\":\n",
        "  url=codecs.decode('uggcf://tvguho.pbz/EIP-Cebwrpg/Ergevriny-onfrq-Ibvpr-Pbairefvba-JroHV.tvg','rot_13')\n",
        "elif Repo == \"Codename0\":\n",
        "  # url=codecs.decode('uggcf://tvguho.pbz/pbqranzr0bt/pbqranzr-eip-sbex.tvg','rot_13')\n",
        "  url=codecs.decode('uggcf://tvguho.pbz/pbqranzr0bt/pbqranzr-eip-sbex/eryrnfrf/qbjaybnq/i1.0.0/pbqranzr-eip-sbex-i1.0.0.mvc','rot_13')\n",
        "elif Repo == \"Fumiama\":\n",
        "  url=codecs.decode('uggcf://tvguho.pbz/shzvnzn/Ergevriny-onfrq-Ibvpr-Pbairefvba-JroHV.tvg','rot_13')\n",
        "\n",
        "\n",
        "url2=codecs.decode('uggcf://enj.tvguhohfrepbagrag.pbz/uvanoy/EIP-Rqvgf/znva/RaebcHV.cl','rot_13')\n",
        "name1=codecs.decode('vasre-jro.cl','rot_13')\n",
        "audiopy = codecs.decode('uggcf://enj.tvguhohfrepbagrag.pbz/uvanoy/EIP-Bayvar/znva/svkrf/nhqvb.cl','rot_13')\n",
        "\n",
        "modelpy = codecs.decode('uggcf://enj.tvguhohfrepbagrag.pbz/pbqranzr0bt/pbqranzr-eip-sbex/znva/gbbyf/qbjaybnq_zbqryf.cl','rot13')\n",
        "\n",
        "# Setup\n",
        "if os.path.exists(\"/content/\"):\n",
        "  note_env=1\n",
        "elif os.path.exists(\"/kaggle/\"):\n",
        "  note_env=2\n",
        "else:\n",
        "  note_env=3\n",
        "\n",
        "# Set\n",
        "if note_env==1:\n",
        "  from google.colab import drive\n",
        "  drive.mount('/content/drive')\n",
        "  !mkdir /content/training\n",
        "  %cd /content/training\n",
        "elif note_env==2:\n",
        "  !mkdir -p /kaggle/tmp/training\n",
        "  %cd /kaggle/tmp/training\n",
        "elif note_env==3:\n",
        "  !mkdip -p training\n",
        "  %cd training\n",
        "\n",
        "# Clone\n",
        "if Repo == \"Original\":\n",
        "  !git clone -b \"2.2.231006\" --single-branch --depth 1 $url .\n",
        "elif Repo == \"Codename0\":\n",
        "  # !git clone -b \"v1.0.0\" --single-branch --depth 1 $url .\n",
        "  !curl -LJ -o codenamefork.zip $url\n",
        "  !unzip -o codenamefork.zip -d ./ > /dev/null 2>&1\n",
        "  !mv codename-rvc-fork-v1.0.0/* ./\n",
        "  !rm -rf codenamefork.zip codename-rvc-fork-v1.0.0\n",
        "elif Repo == \"Fumiama\":\n",
        "  !git clone --depth 1 $url .\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "!rm -rf runmain.py\n",
        "# USe Custom Gui\n",
        "if Repo == \"Original\":\n",
        "  if UseCustomGui==True:\n",
        "    if Gui == \"Raven\":\n",
        "      !curl -o $name1 $url2\n",
        "      !mv $name1 runmain.py\n",
        "      print(\"Raven Gui Downloaded\")\n",
        "    elif Gui == \"Rejecks\":\n",
        "      rj = codecs.decode('uggcf://uhttvatsnpr.pb/Erwrxgf/cebwrpg/erfbyir/znva/cebwrpg-znva.mvc','rot_13')\n",
        "      na = codecs.decode('Erwrxgf','rot_13')\n",
        "      source = \"Rejekts\"\n",
        "      !wget https://huggingface.co/{source}/project/resolve/main/project-main.zip -O ./{source}.zip\n",
        "      !unzip {source}.zip\n",
        "      !cp project-main/app.py ./\n",
        "      !rm -rf project-main\n",
        "      !rm {source}.zip\n",
        "      !mv app.py runmain.py\n",
        "      clear_output()\n",
        "      print(\"Rejecks Downloaded\")\n",
        "    else:\n",
        "      !mv $name1 runmain.py\n",
        "if Repo == \"Fumiama\":\n",
        "  !mv gui.py runmain.py\n",
        "else:\n",
        "  !mv $name1 runmain.py\n",
        "\n",
        "# Extra stuff\n",
        "if Extra==True:\n",
        "  !git clone https://github.com/hinabl/RVC-Edits.git ravenedit\n",
        "  !cp -r ravenedit/* ./\n",
        "  !rm -rf ravenedit/\n",
        "\n",
        "# Fixes\n",
        "if Repo == \"Original\":\n",
        "  !curl -o infer/lib/audio.py $audiopy\n",
        "\n",
        "import base64 as b\n",
        "h = \"aGFlcmRodmVyenJhZ2YudHh0\"\n",
        "e = \"aHR0cHM6Ly9yYXcuZ2l0aHVidXNlcmNvbnRlbnQuY29tL2hpbmFibC9ybXZwZS1haS1rYWdnbGUvbWFpbi9jdXN0b20vaGFlcmRodmVyenJhZ2YudHh0\"\n",
        "d = b.b64decode(e.encode()).decode()\n",
        "k = b.b64decode(h.encode()).decode()\n",
        "!curl -LO $d > /dev/null 2>&1\n",
        "def r(f):\n",
        "    with open(f, 'r') as f:\n",
        "        c = f.read()\n",
        "    return c\n",
        "f = k\n",
        "d = r(f)\n",
        "!rm -rf $d\n",
        "Run_Cell=1\n",
        "# clear_output()\n",
        "print(\"Clone Complete!\")"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Install Requirements and Models\n",
        "#@markdown ---\n",
        "#@markdown This cell will download and install neccessary requirments for the program to work properly\n",
        "#main requirements\n",
        "import time\n",
        "\n",
        "if 'Run_Cell' not in globals():\n",
        "    print(\"No, Go back to the first cell and run it\")\n",
        "else:\n",
        "  if Run_Cell == 0:\n",
        "    print(\"No, Go back to the first cell and run it\")\n",
        "  else:\n",
        "\n",
        "    if Installed_Already==False:\n",
        "      import os\n",
        "      hubertptjp=codecs.decode('uggcf://uhttvatsnpr.pb/evaan/wncnarfr-uhoreg-onfr/erfbyir/znva/snvefrd/zbqry.cg?qbjaybnq=gehr','rot13')\n",
        "      hubertpt=codecs.decode('uggcf://uhttvatsnpr.pb/yw1995/IbvprPbairefvbaJroHV/erfbyir/znva/uhoreg_onfr.cg?qbjaybnq=gehr','rot13')\n",
        "\n",
        "      from IPython.display import clear_output, Javascript\n",
        "      print(\"There will be no output on what is going on, but something is going on. Just wait till this cell finishes loading.\")\n",
        "      print(\"This is done to reduce the output spam on other places this notebook can be used on.\")\n",
        "\n",
        "      !apt-get -y install build-essential python3-dev ffmpeg > /dev/null 2>&1\n",
        "\n",
        "      !pip install uv pyngrok imjoy-elfinder > /dev/null 2>&1\n",
        "      !uv venv .venv\n",
        "      !uv pip install -U setuptools wheel pip > /dev/null 2>&1\n",
        "      !uv pip install -U faiss-cpu==1.7.2 fairseq ffmpeg ffmpeg-python praat-parselmouth pyworld numba==0.56.4 > /dev/null 2>&1\n",
        "\n",
        "\n",
        "      if Repo == \"Original\":\n",
        "        !uv pip install -Ur requirements.txt > /dev/null 2>&1\n",
        "      elif Repo == \"Codename0\":\n",
        "        !uv pip install -Ur requirements/RVC/reclists-RVC/rvc-requirements.txt > /dev/null 2>&1\n",
        "        !uv pip install einops local_attention torchcrepe > /dev/null 2>&1\n",
        "      elif Repo == \"Fumiama\":\n",
        "        !uv pip install -Ur requirements/main.txt > /dev/null 2>&1\n",
        "\n",
        "\n",
        "      !uv pip uninstall gradio > /dev/null 2>&1\n",
        "      !uv pip install -U torch torchvision torchaudio sounddevice noisereduce pyngrok tensorflow mega.py av imjoy-elfinder gradio==3.48.0 python-dotenv ipykernel > /dev/null 2>&1\n",
        "\n",
        "      time.sleep(5)\n",
        "      !uv pip uninstall ffmpeg > /dev/null 2>&1\n",
        "      !uv pip uninstall ffmpeg-python > /dev/null 2>&1\n",
        "      !uv pip install ffmpeg-python > /dev/null 2>&1\n",
        "\n",
        "      if Repo == \"Fumiama\":\n",
        "        !curl -LJ -o tools/download_models.py $modelpy\n",
        "\n",
        "      !python tools/download_models.py\n",
        "\n",
        "      if Repo == \"Codename0\":\n",
        "        !curl -LJ -o assets/rmvpe/rmvpe.onnx https://huggingface.co/spaces/smjain/Advanced-RVC-Inference/resolve/main/rmvpe.onnx?download=true\n",
        "        !mv assets/pretrained_v2/* assets/pretrained/\n",
        "        !rm -rf assets/pretrained_v2\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "      #@markdown ---\n",
        "      import time\n",
        "\n",
        "\n",
        "      if Connected_To_Drive==False:\n",
        "        import shutil\n",
        "        import os\n",
        "        if note_env==1:\n",
        "          print(\"Making Directories on Drive\")\n",
        "          !mkdir -p /content/drive/MyDrive/training/weights\n",
        "          !mkdir -p /content/drive/MyDrive/training/logs/mute\n",
        "          !mkdir -p /content/drive/MyDrive/training/datasets\n",
        "          time.sleep(5)\n",
        "          print(\"Copying Important files from Colab\")\n",
        "          !cp -r logs/ /content/drive/MyDrive/training\n",
        "          !cp -r assets/weights/ /content/drive/MyDrive/training\n",
        "          !cp -r datasets/ /content/drive/MyDrive/training/\n",
        "          time.sleep(5)\n",
        "          print(\"Removing Unnecesarry Files\")\n",
        "          !rm -rf logs/\n",
        "          !rm -rf assets/weights/\n",
        "          !rm -rf datasets/\n",
        "          drive_link_logs = \"/content/drive/MyDrive/training/logs\"\n",
        "          colab_link_logs = \"/content/training/logs\"\n",
        "\n",
        "          drive_link_weights = \"/content/drive/MyDrive/training/weights\"\n",
        "          colab_link_weights = \"/content/training/assets/weights\"\n",
        "\n",
        "          drive_link_datasets = \"/content/drive/MyDrive/training/datasets\"\n",
        "          colab_link_datasets = \"/content/training/datasets\"\n",
        "\n",
        "          print(\"Connecting Colab files to Drive\")\n",
        "          os.symlink(drive_link_weights, colab_link_weights,True)\n",
        "          os.symlink(drive_link_logs,colab_link_logs,True)\n",
        "          os.symlink(drive_link_datasets,colab_link_datasets,True)\n",
        "          time.sleep(5)\n",
        "          clear_output()\n",
        "          print(f\"\\033[93m{colab_link_weights}\\033[0m will now be redirected to \\033[93m{drive_link_weights}\\033[0m\")\n",
        "          print(f\"\\033[93m{colab_link_logs}\\033[0m will now be redirected to \\033[93m{drive_link_logs}\\033[0m\")\n",
        "          Connected_To_Drive=True\n",
        "        elif note_env==2:\n",
        "          !rm -rf datasets\n",
        "          kaggle_link = \"/kaggle/input\"\n",
        "          external_link = \"/kaggle/tmp/training/datasets\"\n",
        "          os.symlink(kaggle_link,external_link,True)\n",
        "\n",
        "          # Connect Log and weights to output\n",
        "\n",
        "          #logs\n",
        "          !mkdir -p \"/kaggle/working/logs\"\n",
        "          !cp -r logs/* \"/kaggle/working/logs\"\n",
        "          !rm -rf logs\n",
        "          kaggle_link_logs = \"/kaggle/tmp/training/logs\"\n",
        "          external_link_logs = \"/kaggle/working/logs\"\n",
        "          os.symlink(external_link_logs,kaggle_link_logs,True)\n",
        "          time.sleep(5)\n",
        "          #weights\n",
        "          !mkdir -p \"/kaggle/working/weights\"\n",
        "          !rm -rf assets/weights\n",
        "          kaggle_link_weights = \"/kaggle/tmp/training/assets/weights\"\n",
        "          external_link_weights = \"/kaggle/working/weights\"\n",
        "          os.symlink(external_link_weights,kaggle_link_weights,True)\n",
        "          clear_output()\n",
        "          print(f\"\\033[93m{kaggle_link_weights}\\033[0m will now be redirected to \\033[93m{external_link_weights}\\033[0m\")\n",
        "          print(f\"\\033[93m{kaggle_link_logs}\\033[0m will now be redirected to \\033[93m{external_link_logs}\\033[0m\")\n",
        "          Connected_To_Drive=True\n",
        "        else:\n",
        "          print(\"No need for Auto Save\")\n",
        "      else:\n",
        "        print(\"Already Connected to Drive\")\n",
        "\n",
        "      print(\"Program Requirements Comeplete\")\n",
        "      print(\"Model Download Comeplete\")\n",
        "    else:\n",
        "      print(\"Packages already Installed\")\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "    use_jp_hubert = False #@param {\"type\":\"boolean\"}\n",
        "    #@markdown A remeninder that the JP Hubert model only works on voice models trained on it. Meaning it wont work on models trained on the original Hubert model and vise versa\n",
        "    if use_jp_hubert==True:\n",
        "      if not os.path.exists(\"assets/hubert/hubert_base.pt_original\"):\n",
        "        !mv assets/hubert/hubert_base.pt assets/hubert/hubert_base.pt_original\n",
        "        !curl -LJ -o assets/hubert/hubert_base.pt $hubertptjp\n",
        "        print(\"JP Hubert has been downloaded!\")\n",
        "      else:\n",
        "        print(\"JP Hubert is already downloaded\")\n",
        "    else:\n",
        "      if os.path.exists(\"assets/hubert/hubert_base.pt_original\"):\n",
        "        !mv assets/hubert/hubert_base.pt_original assets/hubert/hubert_base.pt\n",
        "        print(\"Reverting to original Hubert Model.\")\n",
        "      else:\n",
        "        print(\"Original Hubert Model not Found! Redownloading...\")\n",
        "        !curl -LJ -o assets/hubert/hubert_base.pt $hubertpt\n",
        "      if use_jp_hubert==True:\n",
        "        print(\"Using JP Hubert Base\")\n",
        "      else:\n",
        "        print(\"Using Original Hubert Base\")\n",
        "      Run_Cell=2"
      ],
      "metadata": {
        "id": "_wW3pERwGeDe",
        "cellView": "form"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Download Custom Pretrains\n",
        "#@markdown ---\n",
        "#@markdown This cell lets you download Custom pretrains made by the communitry from huggingface\n",
        "\n",
        "#@markdown Custom pretrains will be located in ``assets/custom_pretrains/[name of creator]/[name of pretrain]``\n",
        "if 'Run_Cell' not in globals():\n",
        "  print(\"No, Go back to the first cell and run it!\")\n",
        "else:\n",
        "  if Run_Cell == 0 or Run_Cell == 1:\n",
        "    print(\"No, Go back to the first cell and run it!!!\")\n",
        "  else:\n",
        "    #@markdown ---\n",
        "    UseCustomPretrain = True #@param {type:\"boolean\"}\n",
        "    CustomPretrain = \"poiqazwsx/Ov2Super32kfix\" # @param [\"poiqazwsx/Ov2Super32kfix\", \"ORVC/Ov2Super\", \"ORVC/RIN_E3\", \"ORVC/Snowie_RuPretrain_48k\", \"ORVC/Snowie_RuPretrain_40k\", \"MUSTAR/SnowieV3.1-32k\", \"MUSTAR/SnowieV3.1-40k\", \"MUSTAR/SnowieV3.1-48k\", \"MUSTAR/SnowieV3.1-X-RinE3-40K\", \"MUSTAR/Snowie_V3.1_JP_hubert\"] {allow-input: true}\n",
        "    #@markdown ---\n",
        "    #@markdown Custom Pretrains from huggingface\n",
        "\n",
        "    # @markdown Examples:\n",
        "\n",
        "    #@markdown ``ORVC/RIN_E3``\n",
        "    #@markdown ``poiqazwsx/Ov2Super32kfix``\n",
        "    #@markdown ``ORVC/Ov2Super``\n",
        "    #@markdown ``ORVC/Snowie_RuPretrain_48k``\n",
        "    #@markdown ``MUSTAR/SnowieV3.1-32k``\n",
        "    #@markdown ``MUSTAR/SnowieV3.1-40k``\n",
        "    #@markdown ``MUSTAR/SnowieV3.1-48k``\n",
        "    #@markdown ``MUSTAR/SnowieV3.1-X-RinE3-40K``\n",
        "    #@markdown ``MUSTAR/Snowie_V3.1_JP_hubert``\n",
        "\n",
        "    import glob\n",
        "    if UseCustomPretrain==True:\n",
        "      !mkdir temppretrains\n",
        "      !mkdir -p assets/custom_pretrain/{CustomPretrain}\n",
        "\n",
        "      !git clone https://huggingface.co/$CustomPretrain temppretrains\n",
        "\n",
        "      !mv temppretrains/*.pth assets/custom_pretrain/{CustomPretrain}\n",
        "      !rm -rf temppretrains/*\n",
        "\n",
        "\n",
        "    clear_output()\n",
        "    print(f\"Downloaded {CustomPretrain}\")\n",
        "\n",
        "    # Get a list of all .pth files in the same directory as CustomPretrain\n",
        "    pth_files = glob.glob(f\"assets/custom_pretrain/{CustomPretrain}/*.pth\")\n",
        "\n",
        "    # Print the list of .pth files\n",
        "    for pth_file in pth_files:\n",
        "        print(pth_file)\n",
        "    Run_Cell=3"
      ],
      "metadata": {
        "id": "3Pkg8K-LRHqS",
        "cellView": "form"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Theme Loader\n",
        "#@markdown ---\n",
        "#@markdown Select a theme to make the UI to your liking\n",
        "\n",
        "if 'Run_Cell' not in globals():\n",
        "    print(\"No, Go back to the first cell and run it\")\n",
        "else:\n",
        "  if Run_Cell == 0 or Run_Cell == 1:\n",
        "    print(\"No, Go back to the first cell and run it\")\n",
        "  else:\n",
        "    import os\n",
        "    Theme=\"ParityError/Interstellar\" #@param {type:\"string\"}\n",
        "\n",
        "    file_path = \"runmain.py.txt\"\n",
        "    if os.path.exists(file_path):\n",
        "        !mv runmain.py.txt runmain.py\n",
        "        !cp runmain.py runmain.py.txt\n",
        "    else:\n",
        "        !cp runmain.py runmain.py.txt\n",
        "\n",
        "    Theme_Front, Theme_Back = Theme.split(\"/\")\n",
        "    #@markdown How to select a theme? \\\n",
        "    #@markdown Go to [Theme Gallery](https://huggingface.co/spaces/gradio/theme-gallery) \\\n",
        "    #@markdown Select a theme \\\n",
        "    #@markdown It should look something like [``ParityError/Interstellar``](https://huggingface.co/spaces/ParityError/Interstellar) \\\n",
        "    #@markdown [![](https://imgur.com/OCKb7za.png)](https://imgur.com/OCKb7za)\n",
        "\n",
        "    !sed -i 's/title/theme=\\\"{Theme_Front}\\/{Theme_Back}\\\",title/' runmain.py\n",
        "\n",
        "    print(f\"Loaded Theme: {Theme}\")\n",
        "    Run_Cell=4\n"
      ],
      "metadata": {
        "cellView": "form",
        "id": "BFb9nDEM10-i"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Start Running\n",
        "#@markdown ---\n",
        "#@markdown Run and wait till the urls show up.\n",
        "import os\n",
        "import time\n",
        "Tunnel = \"Ngrok\" #@param [\"Ngrok\",\"Cloudflared\"]\n",
        "\n",
        "if 'Run_Cell' not in globals():\n",
        "    print(\"No, Go back to the first cell and run it\")\n",
        "else:\n",
        "  if Run_Cell == 0 or Run_Cell == 1:\n",
        "    print(\"No, Go back to the first cell and run it\")\n",
        "  else:\n",
        "    #@markdown To put ngrok token, go to the side and press the key icon<br> On the name put ``Ngrok_Token`` and the Value to be your ngrok token\n",
        "    #Load Tensorboard\n",
        "    #@markdown\n",
        "    if note_env==1:\n",
        "      os.system(f\"imjoy-elfinder --root-dir=/content/training --port 9876 &\")\n",
        "    elif note_env==2:\n",
        "      os.system(f\"imjoy-elfinder --root-dir=/kaggle/tmp/training --port 9876 &\")\n",
        "    else:\n",
        "      os.system(f\"imjoy-elfinder --root-dir=training --port 9876 &\")\n",
        "\n",
        "    if Tunnel == \"Ngrok\":\n",
        "      #Load Ngrok\n",
        "      if note_env==1:\n",
        "        from google.colab import userdata\n",
        "        Ngrok_Token=userdata.get('Ngrok_Token')\n",
        "      else:\n",
        "        Ngrok_Token=\"\"\n",
        "\n",
        "      from pyngrok import ngrok\n",
        "      ngrok.set_auth_token(Ngrok_Token)\n",
        "      ngrok.kill() #tries to close all active ngrok urls\n",
        "\n",
        "\n",
        "      main_tunnel = ngrok.connect(8000)\n",
        "      tens_tunnel = ngrok.connect(8077)\n",
        "      file_tunnel = ngrok.connect(9876)\n",
        "      clear_output()\n",
        "      print(\"RVC URL:\", main_tunnel.public_url)\n",
        "      print(\"Tensorboard URL:\", tens_tunnel.public_url)\n",
        "      print(\"File URL:\", file_tunnel.public_url)\n",
        "    elif Tunnel == \"Cloudflared\":\n",
        "      if note_env==2:\n",
        "        print(\"Cloudflared does not work on kaggle\")\n",
        "      else:\n",
        "        # Install Cloudflared\n",
        "        !curl -LO https://github.com/cloudflare/cloudflared/releases/latest/download/cloudflared-linux-amd64.deb\n",
        "        !dpkg -i cloudflared-linux-amd64.deb\n",
        "        # Delete log file\n",
        "        !rm -rf nohup.out\n",
        "        # Run cloudflared\n",
        "        !nohup cloudflared tunnel --url localhost:9303 &\n",
        "        !nohup cloudflared tunnel --url localhost:8077 &\n",
        "        !nohup cloudflared tunnel --url localhost:9876 &\n",
        "        clear_output()\n",
        "\n",
        "        time.sleep(5)\n",
        "\n",
        "        !source .venv/bin/activate; grep -oE \"https://[a-zA-Z0-9.-]+\\.trycloudflare\\.com\" nohup.out\n",
        "\n",
        "\n",
        "    # Launch Tensorboard\n",
        "    if note_env==2:\n",
        "      # Disable Share\n",
        "      !sed -i 's/share=True/share=False/g' runmain.py && sed -i 's/quiet=True,/quiet=True ,share=False/g' runmain.py\n",
        "\n",
        "\n",
        "      if Tunnel==\"Cloudflared\":\n",
        "        print(\"Ye no Cloudflared\")\n",
        "\n",
        "    %load_ext tensorboard\n",
        "    %tensorboard --logdir logs --port 8077\n",
        "    #Launch App\n",
        "\n",
        "    !source .venv/bin/activate; python runmain.py --pycmd python --port 8000\n",
        "\n",
        "#@markdown [![](https://imgur.com/njXmLsm.gif)](https://imgur.com/njXmLsm)\n"
      ],
      "metadata": {
        "cellView": "form",
        "id": "CKn1Ha9OH_pU"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "[![](https://i.pinimg.com/474x/de/72/9e/de729ecfa41b69901c42c82fff752414.jpg)](https://github.com/hinabl)"
      ],
      "metadata": {
        "id": "9HkWfVgvA1uG"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install python-dotenv"
      ],
      "metadata": {
        "id": "RNDDu2q4DwIb"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}