配置docker记录
Published:
TL;DR: This post documents the process of setting up a Docker container with Miniconda, troubleshooting common issues like network errors during image pulling, and configuring Docker to use image accelerators. It also covers creating a new container with GPU support, shared memory, and volume mounting, along with steps to activate the environment and run code within the container.
配置环境
先拉取镜像
docker pull continuumio/miniconda3:latest
报错
(base) root@ubuntu20:~/ASM# docker pull continuumio/miniconda3:latest
Error response from daemon: Get "https://registry-1.docker.io/v2/": net/http: request canceled while waiting for connection (Client.Timeout exceeded while awaiting headers)
使用image 加速器
参考 docker镜像源配置
# 创建目录
sudo mkdir -p /etc/docker
# 写入配置文件
sudo tee /etc/docker/daemon.json <<-'EOF'
{
"registry-mirrors": [
"https://docker.unsee.tech",
"https://dockerpull.org",
"https://docker.1panel.live",
"https://dockerhub.icu"
]
}
EOF
# 重启docker服务
sudo systemctl daemon-reload
sudo systemctl restart docker
报错
docker exec -it asm_test2 bash # 10g
重新新建一个容器
docker run -itd --network=host --gpus all --shm-size=10g -v /root/ASM:/home --name asm_test2 continuumio/miniconda3 /bin/bash
文件挂载成功了，现在开始跑一下代码看看
- 添加进度条
bash generate_imdb_model.sh
重新激活环境
docker start asm_test2