colab_webui.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "gpuType": "T4"
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "# Build environment 环境配置"
      ],
      "metadata": {
        "id": "kGzjw-j308Ec"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 查看当前使用GPU的CUDA版本\n",
        "!nvidia-smi"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JD7qLbdAu4Rq",
        "outputId": "9f20723c-cf99-45b8-cbd1-c217305163eb"
      },
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mon Mar 11 06:09:53 2024       \n",
            "+---------------------------------------------------------------------------------------+\n",
            "| NVIDIA-SMI 535.104.05             Driver Version: 535.104.05   CUDA Version: 12.2     |\n",
            "|-----------------------------------------+----------------------+----------------------+\n",
            "| GPU  Name                 Persistence-M | Bus-Id        Disp.A | Volatile Uncorr. ECC |\n",
            "| Fan  Temp   Perf          Pwr:Usage/Cap |         Memory-Usage | GPU-Util  Compute M. |\n",
            "|                                         |                      |               MIG M. |\n",
            "|=========================================+======================+======================|\n",
            "|   0  Tesla T4                       Off | 00000000:00:04.0 Off |                    0 |\n",
            "| N/A   46C    P8              10W /  70W |      0MiB / 15360MiB |      0%      Default |\n",
            "|                                         |                      |                  N/A |\n",
            "+-----------------------------------------+----------------------+----------------------+\n",
            "                                                                                         \n",
            "+---------------------------------------------------------------------------------------+\n",
            "| Processes:                                                                            |\n",
            "|  GPU   GI   CI        PID   Type   Process name                            GPU Memory |\n",
            "|        ID   ID                                                             Usage      |\n",
            "|=======================================================================================|\n",
            "|  No running processes found                                                           |\n",
            "+---------------------------------------------------------------------------------------+\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Git Clone 克隆代码"
      ],
      "metadata": {
        "id": "449w7IYaAJiu"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "OtztAfrnuxi_",
        "outputId": "60e21559-bc99-4a2e-f211-9158af94f82c"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content\n",
            "Cloning into 'Linly-Talker'...\n",
            "remote: Enumerating objects: 833, done.\u001b[K\n",
            "remote: Counting objects: 100% (115/115), done.\u001b[K\n",
            "remote: Compressing objects: 100% (90/90), done.\u001b[K\n",
            "remote: Total 833 (delta 50), reused 76 (delta 25), pack-reused 718\u001b[K\n",
            "Receiving objects: 100% (833/833), 58.54 MiB | 38.80 MiB/s, done.\n",
            "Resolving deltas: 100% (300/300), done.\n",
            "/content/Linly-Talker\n",
            "Looking in indexes: https://download.pytorch.org/whl/cu118\n",
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            "\u001b[?25hCollecting pydub==0.25.1 (from -r requirements_app.txt (line 9))\n",
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            "\u001b[?25h  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
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            "Building wheels for collected packages: transformers_stream_generator, zhconv, openai-whisper, ffmpy, filterpy\n",
            "  Building wheel for transformers_stream_generator (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
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            "  Stored in directory: /root/.cache/pip/wheels/47/1d/3c/92d88493ed40c0d9be60a391eb76c9a56e9f9b7542cb789401\n",
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            "  Stored in directory: /root/.cache/pip/wheels/d0/85/e1/9361b4cbea7dd4b7f6702fa4c3afc94877952eeb2b62f45f56\n",
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            "  Created wheel for ffmpy: filename=ffmpy-0.3.2-py3-none-any.whl size=5584 sha256=2c7ee9d29b352c79962c486a8f57dc7428be63200a2d56d0d45dfced8153c351\n",
            "  Stored in directory: /root/.cache/pip/wheels/bd/65/9a/671fc6dcde07d4418df0c592f8df512b26d7a0029c2a23dd81\n",
            "  Building wheel for filterpy (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for filterpy: filename=filterpy-1.4.5-py3-none-any.whl size=110458 sha256=95f3fedae48e74143c95bad15e1dbf4a3945425071b982d4af2caf03bd723aa2\n",
            "  Stored in directory: /root/.cache/pip/wheels/0f/0c/ea/218f266af4ad626897562199fbbcba521b8497303200186102\n",
            "Successfully built transformers_stream_generator zhconv openai-whisper ffmpy filterpy\n",
            "Installing collected packages: zhconv, tokenizers, pydub, ffmpy, yacs, websockets, tomlkit, shellingham, semantic-version, ruff, python-multipart, protobuf, orjson, numpy, joblib, imageio-ffmpeg, h11, einops, colorama, aiofiles, uvicorn, tiktoken, starlette, scipy, imageio, httpcore, transformers, scikit-learn, resampy, openai-whisper, kornia, httpx, fastapi, edge-tts, accelerate, transformers_stream_generator, librosa, gradio-client, filterpy, face_alignment, gradio, facexlib\n",
            "  Attempting uninstall: tokenizers\n",
            "    Found existing installation: tokenizers 0.15.2\n",
            "    Uninstalling tokenizers-0.15.2:\n",
            "      Successfully uninstalled tokenizers-0.15.2\n",
            "  Attempting uninstall: protobuf\n",
            "    Found existing installation: protobuf 3.20.3\n",
            "    Uninstalling protobuf-3.20.3:\n",
            "      Successfully uninstalled protobuf-3.20.3\n",
            "  Attempting uninstall: numpy\n",
            "    Found existing installation: numpy 1.25.2\n",
            "    Uninstalling numpy-1.25.2:\n",
            "      Successfully uninstalled numpy-1.25.2\n",
            "  Attempting uninstall: joblib\n",
            "    Found existing installation: joblib 1.3.2\n",
            "    Uninstalling joblib-1.3.2:\n",
            "      Successfully uninstalled joblib-1.3.2\n",
            "  Attempting uninstall: imageio-ffmpeg\n",
            "    Found existing installation: imageio-ffmpeg 0.4.9\n",
            "    Uninstalling imageio-ffmpeg-0.4.9:\n",
            "      Successfully uninstalled imageio-ffmpeg-0.4.9\n",
            "  Attempting uninstall: scipy\n",
            "    Found existing installation: scipy 1.11.4\n",
            "    Uninstalling scipy-1.11.4:\n",
            "      Successfully uninstalled scipy-1.11.4\n",
            "  Attempting uninstall: imageio\n",
            "    Found existing installation: imageio 2.31.6\n",
            "    Uninstalling imageio-2.31.6:\n",
            "      Successfully uninstalled imageio-2.31.6\n",
            "  Attempting uninstall: transformers\n",
            "    Found existing installation: transformers 4.38.2\n",
            "    Uninstalling transformers-4.38.2:\n",
            "      Successfully uninstalled transformers-4.38.2\n",
            "  Attempting uninstall: scikit-learn\n",
            "    Found existing installation: scikit-learn 1.2.2\n",
            "    Uninstalling scikit-learn-1.2.2:\n",
            "      Successfully uninstalled scikit-learn-1.2.2\n",
            "  Attempting uninstall: librosa\n",
            "    Found existing installation: librosa 0.10.1\n",
            "    Uninstalling librosa-0.10.1:\n",
            "      Successfully uninstalled librosa-0.10.1\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "bigframes 0.22.0 requires scikit-learn>=1.2.2, but you have scikit-learn 1.1.3 which is incompatible.\n",
            "chex 0.1.85 requires numpy>=1.24.1, but you have numpy 1.23.4 which is incompatible.\n",
            "imbalanced-learn 0.10.1 requires joblib>=1.1.1, but you have joblib 1.1.0 which is incompatible.\n",
            "tensorflow 2.15.0 requires numpy<2.0.0,>=1.23.5, but you have numpy 1.23.4 which is incompatible.\n",
            "tensorflow 2.15.0 requires protobuf!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.20.3, but you have protobuf 3.19.6 which is incompatible.\n",
            "tensorflow-datasets 4.9.4 requires protobuf>=3.20, but you have protobuf 3.19.6 which is incompatible.\n",
            "tensorflow-metadata 1.14.0 requires protobuf<4.21,>=3.20.3, but you have protobuf 3.19.6 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[0mSuccessfully installed accelerate-0.27.2 aiofiles-23.2.1 colorama-0.4.6 edge-tts-6.1.10 einops-0.7.0 face_alignment-1.3.5 facexlib-0.3.0 fastapi-0.110.0 ffmpy-0.3.2 filterpy-1.4.5 gradio-4.16.0 gradio-client-0.8.1 h11-0.14.0 httpcore-1.0.4 httpx-0.27.0 imageio-2.19.3 imageio-ffmpeg-0.4.7 joblib-1.1.0 kornia-0.6.8 librosa-0.9.2 numpy-1.23.4 openai-whisper-20231117 orjson-3.9.15 protobuf-3.19.6 pydub-0.25.1 python-multipart-0.0.9 resampy-0.3.1 ruff-0.3.2 scikit-learn-1.1.3 scipy-1.10.1 semantic-version-2.10.0 shellingham-1.5.4 starlette-0.36.3 tiktoken-0.6.0 tokenizers-0.13.3 tomlkit-0.12.0 transformers-4.32.0 transformers_stream_generator-0.0.4 uvicorn-0.28.0 websockets-11.0.3 yacs-0.1.8 zhconv-1.4.3\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.colab-display-data+json": {
              "pip_warning": {
                "packages": [
                  "google",
                  "numpy"
                ]
              },
              "id": "a0a7d836e6c3477e9312d38885af0505"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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            "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch>=1.10.0->accelerate) (1.3.0)\n",
            "Building wheels for collected packages: deepspeed\n",
            "  Building wheel for deepspeed (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for deepspeed: filename=deepspeed-0.14.0-py3-none-any.whl size=1400399 sha256=97f7a16598318b5967032c9b8c578c8a4168cff7b0e542c4c28135301e05486b\n",
            "  Stored in directory: /root/.cache/pip/wheels/23/96/24/bab20c3b4e2af15e195b339afaec373eca7072cf90620432e5\n",
            "Successfully built deepspeed\n",
            "Installing collected packages: ninja, hjson, pynvml, deepspeed, peft\n",
            "Successfully installed deepspeed-0.14.0 hjson-3.1.0 ninja-1.11.1.1 peft-0.9.0 pynvml-11.5.0\n",
            "Collecting protobuf==3.19.4\n",
            "  Downloading protobuf-3.19.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.1 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.1/1.1 MB\u001b[0m \u001b[31m12.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting openai\n",
            "  Downloading openai-1.13.3-py3-none-any.whl (227 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m227.4/227.4 kB\u001b[0m \u001b[31m15.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: anyio<5,>=3.5.0 in /usr/local/lib/python3.10/dist-packages (from openai) (3.7.1)\n",
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            "Requirement already satisfied: typing-extensions<5,>=4.7 in /usr/local/lib/python3.10/dist-packages (from openai) (4.10.0)\n",
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            "Requirement already satisfied: exceptiongroup in /usr/local/lib/python3.10/dist-packages (from anyio<5,>=3.5.0->openai) (1.2.0)\n",
            "Requirement already satisfied: certifi in /usr/local/lib/python3.10/dist-packages (from httpx<1,>=0.23.0->openai) (2024.2.2)\n",
            "Requirement already satisfied: httpcore==1.* in /usr/local/lib/python3.10/dist-packages (from httpx<1,>=0.23.0->openai) (1.0.4)\n",
            "Requirement already satisfied: h11<0.15,>=0.13 in /usr/local/lib/python3.10/dist-packages (from httpcore==1.*->httpx<1,>=0.23.0->openai) (0.14.0)\n",
            "Requirement already satisfied: annotated-types>=0.4.0 in /usr/local/lib/python3.10/dist-packages (from pydantic<3,>=1.9.0->openai) (0.6.0)\n",
            "Requirement already satisfied: pydantic-core==2.16.3 in /usr/local/lib/python3.10/dist-packages (from pydantic<3,>=1.9.0->openai) (2.16.3)\n",
            "Installing collected packages: protobuf, openai\n",
            "  Attempting uninstall: protobuf\n",
            "    Found existing installation: protobuf 3.19.6\n",
            "    Uninstalling protobuf-3.19.6:\n",
            "      Successfully uninstalled protobuf-3.19.6\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "google-ai-generativelanguage 0.4.0 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.19.4 which is incompatible.\n",
            "google-api-core 2.11.1 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0.dev0,>=3.19.5, but you have protobuf 3.19.4 which is incompatible.\n",
            "google-cloud-aiplatform 1.43.0 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.19.4 which is incompatible.\n",
            "google-cloud-bigquery 3.12.0 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.19.4 which is incompatible.\n",
            "google-cloud-bigquery-connection 1.12.1 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.19.4 which is incompatible.\n",
            "google-cloud-bigquery-storage 2.24.0 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.19.4 which is incompatible.\n",
            "google-cloud-datastore 2.15.2 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.19.4 which is incompatible.\n",
            "google-cloud-firestore 2.11.1 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.19.4 which is incompatible.\n",
            "google-cloud-functions 1.13.3 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.19.4 which is incompatible.\n",
            "google-cloud-iam 2.14.3 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.19.4 which is incompatible.\n",
            "google-cloud-language 2.13.3 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.19.4 which is incompatible.\n",
            "google-cloud-resource-manager 1.12.3 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.19.4 which is incompatible.\n",
            "google-cloud-translate 3.11.3 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.19.4 which is incompatible.\n",
            "googleapis-common-protos 1.62.0 requires protobuf!=3.20.0,!=3.20.1,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0.dev0,>=3.19.5, but you have protobuf 3.19.4 which is incompatible.\n",
            "grpc-google-iam-v1 0.13.0 requires protobuf!=3.20.0,!=3.20.1,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.19.4 which is incompatible.\n",
            "tensorboard 2.15.2 requires protobuf!=4.24.0,>=3.19.6, but you have protobuf 3.19.4 which is incompatible.\n",
            "tensorflow 2.15.0 requires numpy<2.0.0,>=1.23.5, but you have numpy 1.23.4 which is incompatible.\n",
            "tensorflow 2.15.0 requires protobuf!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.20.3, but you have protobuf 3.19.4 which is incompatible.\n",
            "tensorflow-datasets 4.9.4 requires protobuf>=3.20, but you have protobuf 3.19.4 which is incompatible.\n",
            "tensorflow-hub 0.16.1 requires protobuf>=3.19.6, but you have protobuf 3.19.4 which is incompatible.\n",
            "tensorflow-metadata 1.14.0 requires protobuf<4.21,>=3.20.3, but you have protobuf 3.19.4 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[0mSuccessfully installed openai-1.13.3 protobuf-3.19.4\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.colab-display-data+json": {
              "pip_warning": {
                "packages": [
                  "google"
                ]
              },
              "id": "83e58bd49d2e4a529353c353a870b888"
            }
          },
          "metadata": {}
        }
      ],
      "source": [
        "%cd /content/\n",
        "!git clone https://github.com/Kedreamix/Linly-Talker\n",
        "%cd /content/Linly-Talker/\n",
        "\n",
        "\n",
        "# 安装torch\n",
        "!pip install torch==2.1.0 torchvision==0.16.0 torchaudio==2.1.0 --index-url https://download.pytorch.org/whl/cu118\n",
        "\n",
        "# 默认存在ffmpeg\n",
        "# conda install -q ffmpeg # ffmpeg==4.2.2\n",
        "\n",
        "# 安装依赖\n",
        "!pip install -r requirements_app.txt\n",
        "\n",
        "# QWen安装\n",
        "!pip install transformers==4.32.0 accelerate tiktoken einops scipy transformers_stream_generator==0.0.4 peft deepspeed\n",
        "\n",
        "!pip install --upgrade protobuf"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 若想使用语音克隆请，安装语音克隆对应的依赖\n",
        "# !pip install -r VITS/requirements_gptsovits.txt"
      ],
      "metadata": {
        "id": "5ghozl_z20rI"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "安装可以后重启一下，才能使用新安装的库"
      ],
      "metadata": {
        "id": "dAaPl8kkAsP2"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Download pretrained models 下载预训练模型"
      ],
      "metadata": {
        "id": "0LqH8VZt1D6W"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%cd /content/Linly-Talker/\n",
        "!rm -rf Linly-Talker/\n",
        "\n",
        "# 从huggingface下载预训练模型，需要一段时间，因为比较大\n",
        "!git lfs install\n",
        "!git clone https://huggingface.co./Kedreamix/Linly-Talker"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LkFCAh4x1P4U",
        "outputId": "6716f95a-ba5f-4798-a35e-c3f0e5be3963"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/Linly-Talker\n",
            "Updated git hooks.\n",
            "Git LFS initialized.\n",
            "Cloning into 'Linly-Talker'...\n",
            "remote: Enumerating objects: 67, done.\u001b[K\n",
            "remote: Counting objects: 100% (63/63), done.\u001b[K\n",
            "remote: Compressing objects: 100% (54/54), done.\u001b[K\n",
            "remote: Total 67 (delta 1), reused 0 (delta 0), pack-reused 4\u001b[K\n",
            "Unpacking objects: 100% (67/67), 2.29 MiB | 7.27 MiB/s, done.\n",
            "Filtering content: 100% (17/17), 7.01 GiB | 55.22 MiB/s, done.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 移动所有模型到当前目录\n",
        "%cd /content/Linly-Talker/\n",
        "\n",
        "# checkpoint中含有SadTalker和Wav2Lip\n",
        "!mkdir checkpoints\n",
        "%mv Linly-Talker/checkpoints/* ./checkpoints/\n",
        "\n",
        "# SadTalker的增强GFPGAN\n",
        "# pip install gfpgan\n",
        "# %mv Linly-Talker/gfpan ./\n",
        "\n",
        "# 语音克隆模型\n",
        "%mv Linly-Talker/GPT_SoVITS/pretrained_models/* ./GPT_SoVITS/pretrained_models/\n",
        "\n",
        "# Qwen大模型\n",
        "%mv Linly-Talker/Qwen ./"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BHTSiSwF3tLG",
        "outputId": "f77ef304-fe79-44fa-9c6e-5d455eefd9cd"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/Linly-Talker\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# launch WebUI 启动WebUI"
      ],
      "metadata": {
        "id": "pVmRVq191Jmb"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "需要修改一下webui.py 设置share = True，这样就能在网页上进行体验\n",
        "\n",
        "\n",
        "\n",
        "```\n",
        "    demo.launch(server_name=\"127.0.0.1\", # 本地端口localhost:127.0.0.1 全局端口转发:\"0.0.0.0\"\n",
        "                server_port=port,\n",
        "                debug=True,\n",
        "                share=True,\n",
        "                )\n",
        "```\n",
        "\n"
      ],
      "metadata": {
        "id": "HNqzuahYFpHS"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%cd /content/Linly-Talker/\n",
        "\n",
        "!python  app.py"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "auS02lwhHdvB",
        "outputId": "407d46dd-b278-41e6-c432-6844d45becf4"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/Linly-Talker\n",
            "如果想使用FunASR，请先安装funasr，若使用Whisper，请忽略此条信息\n",
            "The model is automatically converting to fp16 for faster inference. If you want to disable the automatic precision, please manually add bf16/fp16/fp32=True to \"AutoModelForCausalLM.from_pretrained\".\n",
            "Try importing flash-attention for faster inference...\n",
            "Warning: import flash_attn rotary fail, please install FlashAttention rotary to get higher efficiency https://github.com/Dao-AILab/flash-attention/tree/main/csrc/rotary\n",
            "Warning: import flash_attn rms_norm fail, please install FlashAttention layer_norm to get higher efficiency https://github.com/Dao-AILab/flash-attention/tree/main/csrc/layer_norm\n",
            "Warning: import flash_attn fail, please install FlashAttention to get higher efficiency https://github.com/Dao-AILab/flash-attention\n",
            "Loading checkpoint shards: 100% 2/2 [00:04<00:00,  2.38s/it]\n",
            "using safetensor as default\n",
            "Running on local URL:  http://127.0.0.1:7860\n",
            "Running on public URL: https://d65872c8dbf61ef25e.gradio.live\n",
            "\n",
            "This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co./spaces)\n",
            "2024-03-11 06:29:13.417924: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n",
            "2024-03-11 06:29:13.417993: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n",
            "2024-03-11 06:29:13.425185: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n",
            "2024-03-11 06:29:15.324126: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n",
            "根据任务优先级安排，分配学习时间、休息时间及娱乐时间。建立目标清单，制定实现步骤并按时完成。\n",
            "函数 predict 运行时间： 1.6354515552520752 秒\n",
            "函数 LLM_response 运行时间： 8.379758834838867 秒\n",
            "audio2exp:: 100% 22/22 [00:00<00:00, 27.63it/s]\n",
            "Face Renderer:: 100% 106/106 [01:05<00:00,  1.63it/s]\n",
            "fps:  20 212\n",
            "./results/temp_girl_answer.mp4\n",
            "Numba: Attempted to fork from a non-main thread, the TBB library may be in an invalid state in the child process.\n",
            "函数 Talker_response 运行时间： 81.35897588729858 秒\n",
            "Keyboard interruption in main thread... closing server.\n",
            "Traceback (most recent call last):\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/gradio/blocks.py\", line 2233, in block_thread\n",
            "    time.sleep(0.1)\n",
            "KeyboardInterrupt\n",
            "\n",
            "During handling of the above exception, another exception occurred:\n",
            "\n",
            "Traceback (most recent call last):\n",
            "  File \"/content/Linly-Talker/app.py\", line 187, in <module>\n",
            "    demo.launch(server_name=\"127.0.0.1\", # 本地端口localhost:127.0.0.1 全局端口转发:\"0.0.0.0\"\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/gradio/blocks.py\", line 2129, in launch\n",
            "    self.block_thread()\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/gradio/blocks.py\", line 2237, in block_thread\n",
            "    self.server.close()\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/gradio/networking.py\", line 76, in close\n",
            "    self.thread.join()\n",
            "  File \"/usr/lib/python3.10/threading.py\", line 1096, in join\n",
            "    self._wait_for_tstate_lock()\n",
            "  File \"/usr/lib/python3.10/threading.py\", line 1116, in _wait_for_tstate_lock\n",
            "    if lock.acquire(block, timeout):\n",
            "KeyboardInterrupt\n",
            "Killing tunnel 127.0.0.1:7860 <> https://d65872c8dbf61ef25e.gradio.live\n",
            "\u001b[0m"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%cd /content/Linly-Talker/\n",
        "\n",
        "!python  webui.py"
      ],
      "metadata": {
        "id": "LdUowoDW2HDI",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "f18d71b4-c6be-4bb6-e219-c0b93b5cea78"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/Linly-Talker\n",
            "如果想使用FunASR，请先安装funasr，若使用Whisper，请忽略此条信息\n",
            "The model is automatically converting to fp16 for faster inference. If you want to disable the automatic precision, please manually add bf16/fp16/fp32=True to \"AutoModelForCausalLM.from_pretrained\".\n",
            "Try importing flash-attention for faster inference...\n",
            "Warning: import flash_attn rotary fail, please install FlashAttention rotary to get higher efficiency https://github.com/Dao-AILab/flash-attention/tree/main/csrc/rotary\n",
            "Warning: import flash_attn rms_norm fail, please install FlashAttention layer_norm to get higher efficiency https://github.com/Dao-AILab/flash-attention/tree/main/csrc/layer_norm\n",
            "Warning: import flash_attn fail, please install FlashAttention to get higher efficiency https://github.com/Dao-AILab/flash-attention\n",
            "Loading checkpoint shards: 100% 2/2 [00:08<00:00,  4.04s/it]\n",
            "using safetensor as default\n",
            "Load checkpoint from: checkpoints/wav2lip_gan.pth\n",
            "GPT_SoVITS导入失败，原因： No module named 'LangSegment'\n",
            "使用GPT-SoVITS语音克隆前需要安装对应的环境，请执行 pip install -r VITS/requirements_vits.txt\n",
            "XTTS导入失败，原因： No module named 'langid'\n",
            "使用XTTS语音克隆前需要安装对应的环境，请执行 pip install -r VITS/requirements_xtts.txt\n",
            "GPT-SoVITS Error:  No module named 'LangSegment'\n",
            "如果使用VITS，请先下载GPT-SoVITS模型和安装环境\n",
            "ASR Error:  name 'AutoModel' is not defined\n",
            "如果使用FunASR，请先下载FunASR模型和安装环境\n",
            "Running on local URL:  http://127.0.0.1:7860\n",
            "Running on public URL: https://38fcd792ddeac8706e.gradio.live\n",
            "\n",
            "This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co./spaces)\n",
            "2024-03-11 06:32:27.085932: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n",
            "2024-03-11 06:32:27.085986: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n",
            "2024-03-11 06:32:27.087492: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n",
            "2024-03-11 06:32:28.932933: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n",
            "[('如何进行时间管理？', '制定计划，列出任务，分配时间，按时完成。')]\n",
            "函数 predict 运行时间： 1.4457018375396729 秒\n",
            "audio2exp:: 100% 9/9 [00:00<00:00, 10.08it/s]\n",
            "Face Renderer:: 100% 42/42 [00:25<00:00,  1.63it/s]\n",
            "fps:  20 83\n",
            "./results/temp_boy_answer.mp4\n",
            "IMAGEIO FFMPEG_WRITER WARNING: input image is not divisible by macro_block_size=16, resizing from (256, 218) to (256, 224) to ensure video compatibility with most codecs and players. To prevent resizing, make your input image divisible by the macro_block_size or set the macro_block_size to 1 (risking incompatibility).\n",
            "Numba: Attempted to fork from a non-main thread, the TBB library may be in an invalid state in the child process.\n"
          ]
        }
      ]
    }
  ]
}