配置docker记录

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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