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{
"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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"Collecting numpy==1.23.4 (from -r requirements_app.txt (line 1))\n",
" Downloading numpy-1.23.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (17.1 MB)\n",
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"Building wheels for collected packages: transformers_stream_generator, zhconv, openai-whisper, ffmpy, filterpy\n",
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"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",
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" Attempting uninstall: imageio-ffmpeg\n",
" Found existing installation: imageio-ffmpeg 0.4.9\n",
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" Attempting uninstall: scipy\n",
" Found existing installation: scipy 1.11.4\n",
" Uninstalling scipy-1.11.4:\n",
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" Attempting uninstall: imageio\n",
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" Attempting uninstall: transformers\n",
" Found existing installation: transformers 4.38.2\n",
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" Attempting uninstall: librosa\n",
" Found existing installation: librosa 0.10.1\n",
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"\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",
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"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",
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"\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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"\u001b[?25hRequirement already satisfied: fsspec>=2023.5.0 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.15.1->transformers==4.32.0) (2023.6.0)\n",
"Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.15.1->transformers==4.32.0) (4.10.0)\n",
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"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: idna>=2.8 in /usr/local/lib/python3.10/dist-packages (from anyio<5,>=3.5.0->openai) (3.6)\n",
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"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"
]
}
]
}
]
} |