conda镜像源配置 • Atri Website

镜像源#

华为云

# 1. 添加华为云的 Anaconda 仓库
conda config --add channels https://repo.huaweicloud.com/anaconda/pkgs/free/
conda config --add channels https://repo.huaweicloud.com/anaconda/pkgs/main/
# 2. 添加华为云的 PyTorch 仓库
conda config --add channels https://repo.huaweicloud.com/anaconda/cloud/pytorch/
conda config --add channels https://repo.huaweicloud.com/anaconda/cloud/conda-forge/
conda config --add channels https://repo.huaweicloud.com/anaconda/cloud/msys2/

bash

清华源

conda config --set show_channel_urls yes
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/pytorch/
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge/

bash

实践示例#

下载 miniconda#

使用华为镜像源下载 x86 版本

wget https://repo.huaweicloud.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
bash Miniconda3-latest-Linux-x86_64.sh

bash

配置 pip 全局镜像#

使用华为云作为全局的 pip 镜像

# 全局配置
pip config set global.index-url https://mirrors.huaweicloud.com/repository/pypi/simple/

bash

激活环境#

# 激活环境
source ~/.bashrc

bash

创建 conda 环境#

conda create -n dl python=3.10 -y

bash

设置搜索时显示通道地址#

conda config --set show_channel_urls yes

bash

配置 conda 镜像#

conda config --add channels https://repo.huaweicloud.com/anaconda/pkgs/free/
conda config --add channels https://repo.huaweicloud.com/anaconda/pkgs/main/
conda config --add channels https://repo.huaweicloud.com/anaconda/cloud/pytorch/
conda config --add channels https://repo.huaweicloud.com/anaconda/cloud/conda-forge/
conda config --add channels https://repo.huaweicloud.com/anaconda/cloud/msys2/

bash

删除镜像配置（可选）#

conda config --remove-key channels
conda config --remove-key show_channel_urls
conda config --show channels # 如果成功恢复默认，你会看到输出里只有 defaults，或者什么都不显示

bash

激活环境#

conda activate dl

bash

安装环境依赖#

conda install pytorch torchvision torchaudio pytorch-cuda=11.8 -c pytorch -c nvidia
uv pip install matplotlib tensorboard scikit-learn numpy pandas seaborn kagglehub

bash