docker.io/pytorch/pytorch:2.1.2-cuda12.1-cudnn8-runtime linux/amd64

docker.io/pytorch/pytorch:2.1.2-cuda12.1-cudnn8-runtime - 国内下载镜像源 浏览次数:23 安全受验证的发布者-Pytorch

PyTorch是一个深度学习框架,旨在简化机器学习算法的实现和部署。该镜像提供了一个基于Python 3.x的环境,可以用于快速启动和测试PyTorch项目。

源镜像 docker.io/pytorch/pytorch:2.1.2-cuda12.1-cudnn8-runtime
国内镜像 swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:2.1.2-cuda12.1-cudnn8-runtime
镜像ID sha256:96d3e8fcea30561fe213e97aa46543d0daf78d2c59f981ba972964fd9db2539a
镜像TAG 2.1.2-cuda12.1-cudnn8-runtime
大小 7.22GB
镜像源 docker.io
项目信息 Docker-Hub主页 🚀项目TAG 🚀
CMD /bin/bash
启动入口
工作目录 /workspace
OS/平台 linux/amd64
浏览量 23 次
贡献者
镜像创建 2023-12-14T22:53:46.435893129Z
同步时间 2025-01-10 00:32
更新时间 2025-01-14 02:18
环境变量
PATH=/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin NVIDIA_VISIBLE_DEVICES=all NVIDIA_DRIVER_CAPABILITIES=compute,utility LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64 PYTORCH_VERSION=2.1.2
镜像标签
nvidia_driver: com.nvidia.volumes.needed ubuntu: org.opencontainers.image.ref.name 20.04: org.opencontainers.image.version
镜像安全扫描 查看Trivy扫描报告

系统OS: ubuntu 20.04 扫描引擎: Trivy 扫描时间: 2025-01-10 00:35

低危漏洞:110 中危漏洞:1724 高危漏洞:41 严重漏洞:1

Docker拉取命令 无权限下载?点我修复

docker pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:2.1.2-cuda12.1-cudnn8-runtime
docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:2.1.2-cuda12.1-cudnn8-runtime  docker.io/pytorch/pytorch:2.1.2-cuda12.1-cudnn8-runtime

Containerd拉取命令

ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:2.1.2-cuda12.1-cudnn8-runtime
ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:2.1.2-cuda12.1-cudnn8-runtime  docker.io/pytorch/pytorch:2.1.2-cuda12.1-cudnn8-runtime

Shell快速替换命令

sed -i 's#pytorch/pytorch:2.1.2-cuda12.1-cudnn8-runtime#swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:2.1.2-cuda12.1-cudnn8-runtime#' deployment.yaml

Ansible快速分发-Docker

#ansible k8s -m shell -a 'docker pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:2.1.2-cuda12.1-cudnn8-runtime && docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:2.1.2-cuda12.1-cudnn8-runtime  docker.io/pytorch/pytorch:2.1.2-cuda12.1-cudnn8-runtime'

Ansible快速分发-Containerd

#ansible k8s -m shell -a 'ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:2.1.2-cuda12.1-cudnn8-runtime && ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:2.1.2-cuda12.1-cudnn8-runtime  docker.io/pytorch/pytorch:2.1.2-cuda12.1-cudnn8-runtime'

镜像构建历史


# 2023-12-15 06:53:46  0.00B 设置工作目录为/workspace
WORKDIR /workspace
                        
# 2023-12-15 06:53:46  0.00B 设置环境变量 PYTORCH_VERSION
ENV PYTORCH_VERSION=2.1.2
                        
# 2023-12-15 06:53:46  0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64
                        
# 2023-12-15 06:53:46  0.00B 设置环境变量 NVIDIA_DRIVER_CAPABILITIES
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
                        
# 2023-12-15 06:53:46  0.00B 设置环境变量 NVIDIA_VISIBLE_DEVICES
ENV NVIDIA_VISIBLE_DEVICES=all
                        
# 2023-12-15 06:53:46  0.00B 设置环境变量 PATH
ENV PATH=/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
                        
# 2023-12-15 06:53:46  0.00B 执行命令并创建新的镜像层
RUN |4 PYTORCH_VERSION=2.1.2 TRITON_VERSION=2.1.0+e6216047b8 TARGETPLATFORM=linux/amd64 CUDA_VERSION=12.1.1 /bin/sh -c if test -n "${TRITON_VERSION}" -a "${TARGETPLATFORM}" != "linux/arm64"; then         DEBIAN_FRONTEND=noninteractive apt install -y --no-install-recommends gcc;         rm -rf /var/lib/apt/lists/*;     fi # buildkit
                        
# 2023-12-15 06:53:44  7.10GB 复制新文件或目录到容器中
COPY /opt/conda /opt/conda # buildkit
                        
# 2023-12-15 06:46:03  46.87MB 执行命令并创建新的镜像层
RUN |4 PYTORCH_VERSION=2.1.2 TRITON_VERSION=2.1.0+e6216047b8 TARGETPLATFORM=linux/amd64 CUDA_VERSION=12.1.1 /bin/sh -c apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends         ca-certificates         libjpeg-dev         libpng-dev         && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2023-12-15 06:46:03  0.00B 添加元数据标签
LABEL com.nvidia.volumes.needed=nvidia_driver
                        
# 2023-12-15 06:46:03  0.00B 定义构建参数
ARG CUDA_VERSION
                        
# 2023-12-15 06:46:03  0.00B 定义构建参数
ARG TARGETPLATFORM
                        
# 2023-12-15 06:46:03  0.00B 定义构建参数
ARG TRITON_VERSION
                        
# 2023-12-15 06:46:03  0.00B 定义构建参数
ARG PYTORCH_VERSION
                        
# 2023-11-28 13:17:41  0.00B 
/bin/sh -c #(nop)  CMD ["/bin/bash"]
                        
# 2023-11-28 13:17:41  72.81MB 
/bin/sh -c #(nop) ADD file:9169bb1d6ef21313aed17e924538fee03d858460ae6b05e01968457dfc043bd7 in / 
                        
# 2023-11-28 13:17:39  0.00B 
/bin/sh -c #(nop)  LABEL org.opencontainers.image.version=20.04
                        
# 2023-11-28 13:17:39  0.00B 
/bin/sh -c #(nop)  LABEL org.opencontainers.image.ref.name=ubuntu
                        
# 2023-11-28 13:17:39  0.00B 
/bin/sh -c #(nop)  ARG LAUNCHPAD_BUILD_ARCH
                        
# 2023-11-28 13:17:39  0.00B 
/bin/sh -c #(nop)  ARG RELEASE
                        
                    

镜像信息

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    "Created": "2023-12-14T22:53:46.435893129Z",
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    "Author": "",
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        "AttachStdin": false,
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        "Tty": false,
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        "StdinOnce": false,
        "Env": [
            "PATH=/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin",
            "NVIDIA_VISIBLE_DEVICES=all",
            "NVIDIA_DRIVER_CAPABILITIES=compute,utility",
            "LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64",
            "PYTORCH_VERSION=2.1.2"
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    "Architecture": "amd64",
    "Os": "linux",
    "Size": 7224079996,
    "GraphDriver": {
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