### 更换Ubuntu镜像源教程





#### 概述

本教程将介绍如何在不同版本的Ubuntu中更换为国内镜像源，以提高软件更新和安装速度。以下示例将涵盖Ubuntu 16.04、18.04、20.04、22.04、24.04五个版本。

#### 备份现有镜像源列表

在更改镜像源之前，建议先备份当前的镜像源列表文件`/etc/apt/sources.list`。

```bash
sudo cp /etc/apt/sources.list /etc/apt/sources.list.bak
```

#### 修改镜像源列表

使用文本编辑器打开`/etc/apt/sources.list`文件：

```bash
sudo nano /etc/apt/sources.list
```

将文件内容替换为所需的镜像源列表。以下提供了常用的国内镜像源对应不同版本的配置。

##### Ubuntu 16.04 (代号：xenial)

```plaintext
deb http://mirrors.aliyun.com/ubuntu/ xenial main restricted universe multiverse
deb http://mirrors.aliyun.com/ubuntu/ xenial-security main restricted universe multiverse
deb http://mirrors.aliyun.com/ubuntu/ xenial-updates main restricted universe multiverse
deb http://mirrors.aliyun.com/ubuntu/ xenial-backports main restricted universe multiverse
# deb-src http://mirrors.aliyun.com/ubuntu/ xenial main restricted universe multiverse
# deb-src http://mirrors.aliyun.com/ubuntu/ xenial-security main restricted universe multiverse
# deb-src http://mirrors.aliyun.com/ubuntu/ xenial-updates main restricted universe multiverse
# deb-src http://mirrors.aliyun.com/ubuntu/ xenial-backports main restricted universe multiverse
## 预发布源，不建议启用
# deb http://mirrors.aliyun.com/ubuntu/ xenial-proposed main restricted universe multiverse
# deb-src http://mirrors.aliyun.com/ubuntu/ xenial-proposed main restricted universe multiverse
```

##### Ubuntu 18.04 (代号：bionic)

```plaintext
deb http://mirrors.aliyun.com/ubuntu/ bionic main restricted universe multiverse
deb http://mirrors.aliyun.com/ubuntu/ bionic-security main restricted universe multiverse
deb http://mirrors.aliyun.com/ubuntu/ bionic-updates main restricted universe multiverse
deb http://mirrors.aliyun.com/ubuntu/ bionic-backports main restricted universe multiverse
# deb-src http://mirrors.aliyun.com/ubuntu/ bionic main restricted universe multiverse
# deb-src http://mirrors.aliyun.com/ubuntu/ bionic-security main restricted universe multiverse
# deb-src http://mirrors.aliyun.com/ubuntu/ bionic-updates main restricted universe multiverse
# deb-src http://mirrors.aliyun.com/ubuntu/ bionic-backports main restricted universe multiverse
## 预发布源，不建议启用
# deb http://mirrors.aliyun.com/ubuntu/ bionic-proposed main restricted universe multiverse
# deb-src http://mirrors.aliyun.com/ubuntu/ bionic-proposed main restricted universe multiverse
```

##### Ubuntu 20.04 (代号：focal)

```plaintext
deb http://mirrors.aliyun.com/ubuntu/ focal main restricted universe multiverse
deb http://mirrors.aliyun.com/ubuntu/ focal-security main restricted universe multiverse
deb http://mirrors.aliyun.com/ubuntu/ focal-updates main restricted universe multiverse
deb http://mirrors.aliyun.com/ubuntu/ focal-backports main restricted universe multiverse
# deb-src http://mirrors.aliyun.com/ubuntu/ focal main restricted universe multiverse
# deb-src http://mirrors.aliyun.com/ubuntu/ focal-security main restricted universe multiverse
# deb-src http://mirrors.aliyun.com/ubuntu/ focal-updates main restricted universe multiverse
# deb-src http://mirrors.aliyun.com/ubuntu/ focal-backports main restricted universe multiverse
## 预发布源，不建议启用
# deb http://mirrors.aliyun.com/ubuntu/ focal-proposed main restricted universe multiverse
# deb-src http://mirrors.aliyun.com/ubuntu/ focal-proposed main restricted universe multiverse
```

##### Ubuntu 22.04 (代号：jammy)

```plaintext
deb http://mirrors.aliyun.com/ubuntu/ jammy main restricted universe multiverse
deb http://mirrors.aliyun.com/ubuntu/ jammy-security main restricted universe multiverse
deb http://mirrors.aliyun.com/ubuntu/ jammy-updates main restricted universe multiverse
deb http://mirrors.aliyun.com/ubuntu/ jammy-backports main restricted universe multiverse
# deb-src http://mirrors.aliyun.com/ubuntu/ jammy main restricted universe multiverse
# deb-src http://mirrors.aliyun.com/ubuntu/ jammy-security main restricted universe multiverse
# deb-src http://mirrors.aliyun.com/ubuntu/ jammy-updates main restricted universe multiverse
# deb-src http://mirrors.aliyun.com/ubuntu/ jammy-backports main restricted universe multiverse
## 预发布源，不建议启用
# deb http://mirrors.aliyun.com/ubuntu/ jammy-proposed main restricted universe multiverse
# deb-src http://mirrors.aliyun.com/ubuntu/ jammy-proposed main restricted universe multiverse
```

##### Ubuntu 24.04 (代号：lunar)

```plaintext
deb http://mirrors.aliyun.com/ubuntu/ lunar main restricted universe multiverse
deb http://mirrors.aliyun.com/ubuntu/ lunar-security main restricted universe multiverse
deb http://mirrors.aliyun.com/ubuntu/ lunar-updates main restricted universe multiverse
deb http://mirrors.aliyun.com/ubuntu/ lunar-backports main restricted universe multiverse
# deb-src http://mirrors.aliyun.com/ubuntu/ lunar main restricted universe multiverse
# deb-src http://mirrors.aliyun.com/ubuntu/ lunar-security main restricted universe multiverse
# deb-src http://mirrors.aliyun.com/ubuntu/ lunar-updates main restricted universe multiverse
# deb-src http://mirrors.aliyun.com/ubuntu/ lunar-backports main restricted universe multiverse
## 预发布源，不建议启用
# deb http://mirrors.aliyun.com/ubuntu/ lunar-proposed main restricted universe multiverse
# deb-src http://mirrors.aliyun.com/ubuntu/ lunar-proposed main restricted universe multiverse
```

#### 更新软件包列表

保存并关闭`/etc/apt/sources.list`文件后，执行以下命令更新软件包列表：

```bash
sudo apt update
```

等待更新完成即可。

#### 常见问题及解决方法

1. **更新失败或速度较慢**：

   - 尝试更换其他镜像源，如中科大或清华大学的镜像源。

   - 检查网络连接是否正常。

   

2. **权限问题**：

   - 确保使用`sudo`命令进行操作。

   - 检查`/etc/apt/sources.list`文件的权限是否正确。

通过上述步骤，您可以在不同版本的Ubuntu中轻松更换为国内的镜像源，从而提升软件更新和安装的速度。

Ubuntu apt更换国内镜像源，apt 更新源，apt 国内镜像

如何断点续传：





curl "xxxxurl" -o RealisticPhotography_v10.safetensors

要实现断点续传，您可以使用`curl`工具并添加一些参数，以便在下载中断后恢复下载。下面是如何使用`curl`进行断点续传的方法：

1. 首先，确保您已经安装了`curl`命令行工具。

2. 使用`curl`的`-C -`参数来启用断点续传。这将告诉`curl`在文件已经存在的情况下继续下载。

```bash
curl -C - -o RealisticPhotography_v10.safetensors "xxxxurl"
```

这个命令会尝试从指定的URL继续下载文件，并且如果文件已经存在，它将从上次中断的地方继续下载。

注意：要使用这个方法，确保您的服务器支持HTTP断点续传。如果服务器不支持，那么此方法可能不起作用。

curl 断点续传

[https://github.com/AUTOMATIC1111/stable-diffusion-webui/discussions/5303#discussioncomment-4303079](https://github.com/AUTOMATIC1111/stable-diffusion-webui/discussions/5303#discussioncomment-4303079)





Just follow the guide here,do exact same installations, and your xformers should work.

go to the webui directory

source ./venv/bin/activate

cd repositories

git clone https://github.com/facebookresearch/xformers.git

cd xformers

git submodule update --init --recursive

pip install -r requirements.txt

pip install -e .

The last step will take more time, so be patient.

特别是最后一句，要很久很久，真的很久。

![在这里插入图片描述](/static/img/images/03812.png)

No module ‘xformers‘. Proceeding without it.

这里罗列一些打包的镜像，方便直接使用。





# cu11.6ubuntu18.04

docker push kevinchina/deeplearning:cu11.6ubuntu18.04
```bash
FROM nvidia/cuda:11.6.2-cudnn8-devel-ubuntu18.04
RUN apt-get update && apt-get install -y wget git vim curl
RUN wget http://mirrors.tuna.tsinghua.edu.cn/anaconda/miniconda/Miniconda3-latest-Linux-x86_64.sh -O /tmp/conda.sh && \
    bash /tmp/conda.sh -b && rm /tmp/conda.sh
ENV DEBIAN_FRONTEND=noninteractive
# 安装 tzdata 包并设置时区为上海（无交互）
RUN apt-get update && \
    apt-get install -y tzdata && \
    ln -sf /usr/share/zoneinfo/Asia/Shanghai /etc/localtime && \
    echo "Asia/Shanghai" > /etc/timezone
RUN ~/miniconda3/bin/conda init bash && . ~/.bashrc
RUN . ~/.bashrc && curl -s https://packagecloud.io/install/repositories/github/git-lfs/script.deb.sh |  bash && \
    apt-get install -y git-lfs && git-lfs install
RUN apt-get install -y python3-pip
# 打印~/.bashrc
RUN . ~/.bashrc && pip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple
RUN . ~/.bashrc && conda create -n py3_10_c2 python=3.10 -y
# RUN . ~/.bashrc && conda activate py3_10_c2 && conda install pytorch==1.13.1 torchvision==0.14.1 torchaudio==0.13.1 pytorch-cuda=11.6 -c pytorch -c nvidia -y
```


# cu11.8ubuntu22.04

docker push kevinchina/deeplearning:cu11.8ubuntu22.04

```bash
FROM nvidia/cuda:11.8.0-devel-ubuntu22.04
RUN apt-get update && apt-get install -y wget git vim curl
RUN wget http://mirrors.tuna.tsinghua.edu.cn/anaconda/miniconda/Miniconda3-latest-Linux-x86_64.sh -O /tmp/conda.sh && \
    bash /tmp/conda.sh -b && rm /tmp/conda.sh
ENV DEBIAN_FRONTEND=noninteractive
# 安装 tzdata 包并设置时区为上海（无交互）
RUN apt-get update && \
    apt-get install -y tzdata && \
    ln -sf /usr/share/zoneinfo/Asia/Shanghai /etc/localtime && \
    echo "Asia/Shanghai" > /etc/timezone
RUN ~/miniconda3/bin/conda init bash && . ~/.bashrc
RUN . ~/.bashrc && curl -s https://packagecloud.io/install/repositories/github/git-lfs/script.deb.sh |  bash && \
    apt-get install -y git-lfs && git-lfs install
RUN apt-get install -y python3-pip
# 打印~/.bashrc
RUN . ~/.bashrc && pip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple
RUN . ~/.bashrc && conda create -n py3_10_c2 python=3.10 -y
#RUN . ~/.bashrc && conda activate py3_10_c2 && conda install pytorch==1.13.1 torchvision==0.14.1 torchaudio==0.13.1 pytorch-cuda=11.6 -c pytorch -c nvidia -y
```

# cuda:11.8.0-cudnn8-runtime-ubuntu22.04 + 纯python


```clike
FROM nvidia/cuda:11.8.0-cudnn8-runtime-ubuntu22.04
ENV DEBIAN_FRONTEND=noninteractive
# 安装基本软件包
RUN apt-get update && \
    apt-get upgrade -y && \
    apt-get -y --no-install-recommends install vim wget curl build-essential python3.10 python3-pip sudo && \
    update-alternatives --install /usr/bin/python python /usr/bin/python3.10 1 && \
    apt-get install -y libgl1 libglib2.0-0 ffmpeg tzdata && \
    ln -sf /usr/share/zoneinfo/Asia/Shanghai /etc/localtime && \
    echo "Asia/Shanghai" > /etc/timezone
# 创建用户xd
RUN useradd -m -s /bin/bash xd
# 设置用户xd的密码为qwer1234..
RUN echo 'xd:qwer1234..' | chpasswd
# 将用户xd添加到sudo组并配置sudo无密码
RUN usermod -aG sudo xd && echo 'xd ALL=(ALL) NOPASSWD:ALL' > /etc/sudoers.d/xd
# 切换到xd用户
USER xd
# 设置工作目录
WORKDIR /home/xd
```



```clike
FROM nvidia/cuda:11.8.0-cudnn8-devel-ubuntu22.04
ENV DEBIAN_FRONTEND=noninteractive
# 安装基本软件包
RUN apt-get update && \
    apt-get upgrade -y && \
    apt-get -y --no-install-recommends install vim wget curl git build-essential python3.10 python3-pip python3.10-venv sudo && \
    update-alternatives --install /usr/bin/python python /usr/bin/python3.10 1 && \
    apt-get install -y libgl1 libglib2.0-0
# 安装 tzdata 包并设置时区为上海（无交互）
RUN apt-get update && \
    apt-get install -y tzdata && \
    ln -sf /usr/share/zoneinfo/Asia/Shanghai /etc/localtime && \
    echo "Asia/Shanghai" > /etc/timezone
```

# nvidia/cuda:12.1.1-cudnn8-devel-ubuntu22.04

nvidia/cuda:12.1.1-cudnn8-devel-ubuntu22.04 + 纯python+cuda12.1  pytorch 2.1

已推：docker push kevinchina/deeplearning:cuda12.1torch2.1.1

```bash
FROM nvidia/cuda:12.1.1-cudnn8-devel-ubuntu22.04
ENV DEBIAN_FRONTEND=noninteractive
# 安装基本软件包
RUN apt-get update && \
    apt-get upgrade -y && \
    apt-get -y --no-install-recommends install vim wget curl git build-essential python3.10 python3-pip python3.10-venv sudo && \
    update-alternatives --install /usr/bin/python python /usr/bin/python3.10 1 && \
    apt-get install -y libgl1 libglib2.0-0
# 安装 tzdata 包并设置时区为上海（无交互）
RUN apt-get update && \
    apt-get install -y tzdata && \
    ln -sf /usr/share/zoneinfo/Asia/Shanghai /etc/localtime && \
    echo "Asia/Shanghai" > /etc/timezone
RUN pip install torch==2.1.1 torchvision==0.16.1 torchaudio==2.1.1 --index-url https://download.pytorch.org/whl/cu121
```



# cuda11.8+python

docker push kevinchina/deeplearning:cuda118python

```python
FROM nvidia/cuda:11.8.0-cudnn8-runtime-ubuntu22.04
ENV DEBIAN_FRONTEND=noninteractive
# 安装基本软件包
RUN apt-get update && \
    apt-get upgrade -y && \
    apt-get -y --no-install-recommends install vim wget curl build-essential python3.10-dev python3.10 python3-pip sudo && \
    update-alternatives --install /usr/bin/python python /usr/bin/python3.10 1 && \
    apt-get install -y libgl1 libglib2.0-0 ffmpeg tzdata && \
    ln -sf /usr/share/zoneinfo/Asia/Shanghai /etc/localtime && \
    echo "Asia/Shanghai" > /etc/timezone
RUN apt-get -y --no-install-recommends install vim wget curl git build-essential python3.10 python3-pip python3.10-venv sudo
RUN apt-get install -y libgl1 libglib2.0-0
```


# cuda11.8+python+torch2.1.2

docker push kevinchina/deeplearning:cuda118torch2.1.2

```python
# CUDA 11.8
FROM nvidia/cuda:11.8.0-cudnn8-runtime-ubuntu22.04
ENV DEBIAN_FRONTEND=noninteractive
# 安装基本软件包
RUN apt-get update && \
    apt-get upgrade -y && \
    apt-get -y --no-install-recommends install vim wget curl build-essential python3.10-dev python3.10 python3-pip sudo && \
    update-alternatives --install /usr/bin/python python /usr/bin/python3.10 1 && \
    apt-get install -y libgl1 libglib2.0-0 ffmpeg tzdata && \
    ln -sf /usr/share/zoneinfo/Asia/Shanghai /etc/localtime && \
    echo "Asia/Shanghai" > /etc/timezone
RUN apt-get -y --no-install-recommends install vim wget curl git build-essential python3.10 python3-pip python3.10-venv sudo
RUN apt-get install -y libgl1 libglib2.0-0
RUN pip install torch==2.1.2 torchvision==0.16.2 torchaudio==2.1.2 --index-url https://download.pytorch.org/whl/cu118
```

【Docker】一些可以直接用的Docker环境

# 安装docker







安装docker（这东西一次就够了）：

```clike
sudo apt-get update
sudo apt-get install -y docker.io  或者snap install docker     # version 19.03.11, or apt  install docker.io
systemctl start docker
systemctl enable docker
docker version
```

对于安装新的显卡驱动后，最好重装一下docker nvidia。

安装docker nvidia：

```clike
# 1、添加源
distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
sudo curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add -
# 这个命令抽风，即使去下载https://nvidia.github.io/nvidia-docker/ubuntu22.04/nvidia-docker.list，得到的如果是18.04的，这个时候就自己修改文件/etc/apt/sources.list.d/nvidia-docker.list 
sudo curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list 
# 2、安装并重启
sudo apt-get update && sudo apt-get install -y nvidia-container-toolkit
sudo systemctl restart docker
# 3、测试
docker run --name test1 -it --gpus all或者写"device=0"或者'"device=0,1,2,3"'  nvidia/cuda:10.0-base 
docker run -it --gpus all  nvidia/cuda:11.8.0-base-centos7 bash
```


卸载docker：

```clike
sudo apt-get remove docker  
sudo apt-get remove --auto-remove docker  
sudo apt remove docker-ce
```

# 卸载显卡驱动



删除旧版本Nvidia驱动通常需要执行一些步骤，下面是一般情况下的做法：

1. **卸载Nvidia驱动**：使用以下命令可以卸载Nvidia驱动：

   ```clike
   sudo apt-get purge nvidia-*
   ```

   如果你的系统不是基于Debian的发行版（如Ubuntu），可以使用相应发行版的包管理器命令来卸载Nvidia驱动。

2. **删除残留文件**：执行以上命令后，还需要确认删除Nvidia相关的残留文件。你可以使用以下命令来删除Nvidia残留文件：

   ```clike
   sudo rm /etc/X11/xorg.conf
   sudo apt-get autoremove
   sudo apt-get autoclean
   ```

   这些命令可以删除Nvidia驱动卸载后留下的配置文件和不再需要的依赖包。

3. **重启系统**：最后，重启系统以确保所有的更改生效。

需要注意的是，卸载Nvidia驱动会导致你的系统使用开源的Nouveau驱动或者没有驱动，这可能会影响显示性能和相关功能。因此，在卸载旧版本驱动之后，确保准备好安装新的、兼容的Nvidia驱动。

希望这些信息对你有所帮助！如有其他问题，欢迎随时提问。🙂

# 安装新的显卡驱动

wget下载合适的驱动后，sudo -i后直接：

```clike
./NVIDIA-Linux-x86_64-535.129.03.run
```

装的时候提示装不上的话你可以先重启一下。

【安装docker】ubuntu安装docker nvidia，如何安装nvidia-docker

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