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

docker.io/pytorch/pytorch:2.1.2-cuda12.1-cudnn8-devel - 国内下载镜像源 浏览次数:48 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-devel
国内镜像 swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:2.1.2-cuda12.1-cudnn8-devel
镜像ID sha256:ecb3f786af6cb6c838d3290933dfe10f022488defd8c1f606769cb151f83140d
镜像TAG 2.1.2-cuda12.1-cudnn8-devel
大小 16.58GB
镜像源 docker.io
项目信息 Docker-Hub主页 🚀项目TAG 🚀
CMD
启动入口 /opt/nvidia/nvidia_entrypoint.sh
工作目录 /workspace
OS/平台 linux/amd64
浏览量 48 次
贡献者
镜像创建 2023-12-14T22:55:34.489319264Z
同步时间 2024-12-20 00:05
更新时间 2025-01-14 08:47
环境变量
PATH=/opt/conda/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin NVARCH=x86_64 NVIDIA_REQUIRE_CUDA=cuda>=12.1 brand=tesla,driver>=470,driver<471 brand=unknown,driver>=470,driver<471 brand=nvidia,driver>=470,driver<471 brand=nvidiartx,driver>=470,driver<471 brand=geforce,driver>=470,driver<471 brand=geforcertx,driver>=470,driver<471 brand=quadro,driver>=470,driver<471 brand=quadrortx,driver>=470,driver<471 brand=titan,driver>=470,driver<471 brand=titanrtx,driver>=470,driver<471 brand=tesla,driver>=525,driver<526 brand=unknown,driver>=525,driver<526 brand=nvidia,driver>=525,driver<526 brand=nvidiartx,driver>=525,driver<526 brand=geforce,driver>=525,driver<526 brand=geforcertx,driver>=525,driver<526 brand=quadro,driver>=525,driver<526 brand=quadrortx,driver>=525,driver<526 brand=titan,driver>=525,driver<526 brand=titanrtx,driver>=525,driver<526 NV_CUDA_CUDART_VERSION=12.1.105-1 NV_CUDA_COMPAT_PACKAGE=cuda-compat-12-1 CUDA_VERSION=12.1.1 LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64 NVIDIA_VISIBLE_DEVICES=all NVIDIA_DRIVER_CAPABILITIES=compute,utility NV_CUDA_LIB_VERSION=12.1.1-1 NV_NVTX_VERSION=12.1.105-1 NV_LIBNPP_VERSION=12.1.0.40-1 NV_LIBNPP_PACKAGE=libnpp-12-1=12.1.0.40-1 NV_LIBCUSPARSE_VERSION=12.1.0.106-1 NV_LIBCUBLAS_PACKAGE_NAME=libcublas-12-1 NV_LIBCUBLAS_VERSION=12.1.3.1-1 NV_LIBCUBLAS_PACKAGE=libcublas-12-1=12.1.3.1-1 NV_LIBNCCL_PACKAGE_NAME=libnccl2 NV_LIBNCCL_PACKAGE_VERSION=2.17.1-1 NCCL_VERSION=2.17.1-1 NV_LIBNCCL_PACKAGE=libnccl2=2.17.1-1+cuda12.1 NVIDIA_PRODUCT_NAME=CUDA NV_CUDA_CUDART_DEV_VERSION=12.1.105-1 NV_NVML_DEV_VERSION=12.1.105-1 NV_LIBCUSPARSE_DEV_VERSION=12.1.0.106-1 NV_LIBNPP_DEV_VERSION=12.1.0.40-1 NV_LIBNPP_DEV_PACKAGE=libnpp-dev-12-1=12.1.0.40-1 NV_LIBCUBLAS_DEV_VERSION=12.1.3.1-1 NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-12-1 NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-12-1=12.1.3.1-1 NV_CUDA_NSIGHT_COMPUTE_VERSION=12.1.1-1 NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE=cuda-nsight-compute-12-1=12.1.1-1 NV_NVPROF_VERSION=12.1.105-1 NV_NVPROF_DEV_PACKAGE=cuda-nvprof-12-1=12.1.105-1 NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev NV_LIBNCCL_DEV_PACKAGE_VERSION=2.17.1-1 NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.17.1-1+cuda12.1 LIBRARY_PATH=/usr/local/cuda/lib64/stubs NV_CUDNN_VERSION=8.9.0.131 NV_CUDNN_PACKAGE_NAME=libcudnn8 NV_CUDNN_PACKAGE=libcudnn8=8.9.0.131-1+cuda12.1 NV_CUDNN_PACKAGE_DEV=libcudnn8-dev=8.9.0.131-1+cuda12.1 PYTORCH_VERSION=2.1.2
镜像标签
8.9.0.131: com.nvidia.cudnn.version nvidia_driver: com.nvidia.volumes.needed NVIDIA CORPORATION <cudatools@nvidia.com>: maintainer 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: 2024-12-20 00:07

低危漏洞:163 中危漏洞:1816 高危漏洞:42 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-devel
docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:2.1.2-cuda12.1-cudnn8-devel  docker.io/pytorch/pytorch:2.1.2-cuda12.1-cudnn8-devel

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

Shell快速替换命令

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

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

镜像构建历史


# 2023-12-15 06:55:34  0.00B 设置工作目录为/workspace
WORKDIR /workspace
                        
# 2023-12-15 06:55:34  0.00B 设置环境变量 PYTORCH_VERSION
ENV PYTORCH_VERSION=2.1.2
                        
# 2023-12-15 06:55:34  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 06:55:34  0.00B 设置环境变量 NVIDIA_DRIVER_CAPABILITIES
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
                        
# 2023-12-15 06:55:34  0.00B 设置环境变量 NVIDIA_VISIBLE_DEVICES
ENV NVIDIA_VISIBLE_DEVICES=all
                        
# 2023-12-15 06:55:34  0.00B 设置环境变量 PATH
ENV PATH=/opt/conda/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
                        
# 2023-12-15 06:55:34  6.96KB 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 06:55:32  7.10GB 复制新文件或目录到容器中
COPY /opt/conda /opt/conda # buildkit
                        
# 2023-12-15 06:47:57  3.27MB 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 06:47:57  0.00B 添加元数据标签
LABEL com.nvidia.volumes.needed=nvidia_driver
                        
# 2023-12-15 06:47:57  0.00B 定义构建参数
ARG CUDA_VERSION
                        
# 2023-12-15 06:47:57  0.00B 定义构建参数
ARG TARGETPLATFORM
                        
# 2023-12-15 06:47:57  0.00B 定义构建参数
ARG TRITON_VERSION
                        
# 2023-12-15 06:47:57  0.00B 定义构建参数
ARG PYTORCH_VERSION
                        
# 2023-11-10 13:52:20  2.45GB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends     ${NV_CUDNN_PACKAGE}     ${NV_CUDNN_PACKAGE_DEV}     && apt-mark hold ${NV_CUDNN_PACKAGE_NAME}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2023-11-10 13:52:20  0.00B 添加元数据标签
LABEL com.nvidia.cudnn.version=8.9.0.131
                        
# 2023-11-10 13:52:20  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2023-11-10 13:52:20  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2023-11-10 13:52:20  0.00B 设置环境变量 NV_CUDNN_PACKAGE_DEV
ENV NV_CUDNN_PACKAGE_DEV=libcudnn8-dev=8.9.0.131-1+cuda12.1
                        
# 2023-11-10 13:52:20  0.00B 设置环境变量 NV_CUDNN_PACKAGE
ENV NV_CUDNN_PACKAGE=libcudnn8=8.9.0.131-1+cuda12.1
                        
# 2023-11-10 13:52:20  0.00B 设置环境变量 NV_CUDNN_PACKAGE_NAME
ENV NV_CUDNN_PACKAGE_NAME=libcudnn8
                        
# 2023-11-10 13:52:20  0.00B 设置环境变量 NV_CUDNN_VERSION
ENV NV_CUDNN_VERSION=8.9.0.131
                        
# 2023-11-10 13:25:45  0.00B 设置环境变量 LIBRARY_PATH
ENV LIBRARY_PATH=/usr/local/cuda/lib64/stubs
                        
# 2023-11-10 13:25:45  379.49KB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-mark hold ${NV_LIBCUBLAS_DEV_PACKAGE_NAME} ${NV_LIBNCCL_DEV_PACKAGE_NAME} # buildkit
                        
# 2023-11-10 13:25:42  4.77GB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends     libtinfo5 libncursesw5     cuda-cudart-dev-12-1=${NV_CUDA_CUDART_DEV_VERSION}     cuda-command-line-tools-12-1=${NV_CUDA_LIB_VERSION}     cuda-minimal-build-12-1=${NV_CUDA_LIB_VERSION}     cuda-libraries-dev-12-1=${NV_CUDA_LIB_VERSION}     cuda-nvml-dev-12-1=${NV_NVML_DEV_VERSION}     ${NV_NVPROF_DEV_PACKAGE}     ${NV_LIBNPP_DEV_PACKAGE}     libcusparse-dev-12-1=${NV_LIBCUSPARSE_DEV_VERSION}     ${NV_LIBCUBLAS_DEV_PACKAGE}     ${NV_LIBNCCL_DEV_PACKAGE}     ${NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2023-11-10 13:25:42  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2023-11-10 13:25:42  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2023-11-10 13:25:42  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE
ENV NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.17.1-1+cuda12.1
                        
# 2023-11-10 13:25:42  0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.17.1-1
                        
# 2023-11-10 13:25:42  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE_VERSION
ENV NV_LIBNCCL_DEV_PACKAGE_VERSION=2.17.1-1
                        
# 2023-11-10 13:25:42  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE_NAME
ENV NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev
                        
# 2023-11-10 13:25:42  0.00B 设置环境变量 NV_NVPROF_DEV_PACKAGE
ENV NV_NVPROF_DEV_PACKAGE=cuda-nvprof-12-1=12.1.105-1
                        
# 2023-11-10 13:25:42  0.00B 设置环境变量 NV_NVPROF_VERSION
ENV NV_NVPROF_VERSION=12.1.105-1
                        
# 2023-11-10 13:25:42  0.00B 设置环境变量 NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE
ENV NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE=cuda-nsight-compute-12-1=12.1.1-1
                        
# 2023-11-10 13:25:42  0.00B 设置环境变量 NV_CUDA_NSIGHT_COMPUTE_VERSION
ENV NV_CUDA_NSIGHT_COMPUTE_VERSION=12.1.1-1
                        
# 2023-11-10 13:25:42  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_PACKAGE
ENV NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-12-1=12.1.3.1-1
                        
# 2023-11-10 13:25:42  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_PACKAGE_NAME
ENV NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-12-1
                        
# 2023-11-10 13:25:42  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_VERSION
ENV NV_LIBCUBLAS_DEV_VERSION=12.1.3.1-1
                        
# 2023-11-10 13:25:42  0.00B 设置环境变量 NV_LIBNPP_DEV_PACKAGE
ENV NV_LIBNPP_DEV_PACKAGE=libnpp-dev-12-1=12.1.0.40-1
                        
# 2023-11-10 13:25:42  0.00B 设置环境变量 NV_LIBNPP_DEV_VERSION
ENV NV_LIBNPP_DEV_VERSION=12.1.0.40-1
                        
# 2023-11-10 13:25:42  0.00B 设置环境变量 NV_LIBCUSPARSE_DEV_VERSION
ENV NV_LIBCUSPARSE_DEV_VERSION=12.1.0.106-1
                        
# 2023-11-10 13:25:42  0.00B 设置环境变量 NV_NVML_DEV_VERSION
ENV NV_NVML_DEV_VERSION=12.1.105-1
                        
# 2023-11-10 13:25:42  0.00B 设置环境变量 NV_CUDA_CUDART_DEV_VERSION
ENV NV_CUDA_CUDART_DEV_VERSION=12.1.105-1
                        
# 2023-11-10 13:25:42  0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=12.1.1-1
                        
# 2023-11-10 13:14:24  0.00B 配置容器启动时运行的命令
ENTRYPOINT ["/opt/nvidia/nvidia_entrypoint.sh"]
                        
# 2023-11-10 13:14:24  0.00B 设置环境变量 NVIDIA_PRODUCT_NAME
ENV NVIDIA_PRODUCT_NAME=CUDA
                        
# 2023-11-10 13:14:24  2.53KB 复制新文件或目录到容器中
COPY nvidia_entrypoint.sh /opt/nvidia/ # buildkit
                        
# 2023-11-10 13:14:24  3.06KB 复制新文件或目录到容器中
COPY entrypoint.d/ /opt/nvidia/entrypoint.d/ # buildkit
                        
# 2023-11-10 13:14:24  259.50KB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-mark hold ${NV_LIBCUBLAS_PACKAGE_NAME} ${NV_LIBNCCL_PACKAGE_NAME} # buildkit
                        
# 2023-11-10 13:14:23  2.01GB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends     cuda-libraries-12-1=${NV_CUDA_LIB_VERSION}     ${NV_LIBNPP_PACKAGE}     cuda-nvtx-12-1=${NV_NVTX_VERSION}     libcusparse-12-1=${NV_LIBCUSPARSE_VERSION}     ${NV_LIBCUBLAS_PACKAGE}     ${NV_LIBNCCL_PACKAGE}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2023-11-10 13:14:23  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2023-11-10 13:14:23  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2023-11-10 13:14:23  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE
ENV NV_LIBNCCL_PACKAGE=libnccl2=2.17.1-1+cuda12.1
                        
# 2023-11-10 13:14:23  0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.17.1-1
                        
# 2023-11-10 13:14:23  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_VERSION
ENV NV_LIBNCCL_PACKAGE_VERSION=2.17.1-1
                        
# 2023-11-10 13:14:23  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_NAME
ENV NV_LIBNCCL_PACKAGE_NAME=libnccl2
                        
# 2023-11-10 13:14:23  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE
ENV NV_LIBCUBLAS_PACKAGE=libcublas-12-1=12.1.3.1-1
                        
# 2023-11-10 13:14:23  0.00B 设置环境变量 NV_LIBCUBLAS_VERSION
ENV NV_LIBCUBLAS_VERSION=12.1.3.1-1
                        
# 2023-11-10 13:14:23  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE_NAME
ENV NV_LIBCUBLAS_PACKAGE_NAME=libcublas-12-1
                        
# 2023-11-10 13:14:23  0.00B 设置环境变量 NV_LIBCUSPARSE_VERSION
ENV NV_LIBCUSPARSE_VERSION=12.1.0.106-1
                        
# 2023-11-10 13:14:23  0.00B 设置环境变量 NV_LIBNPP_PACKAGE
ENV NV_LIBNPP_PACKAGE=libnpp-12-1=12.1.0.40-1
                        
# 2023-11-10 13:14:23  0.00B 设置环境变量 NV_LIBNPP_VERSION
ENV NV_LIBNPP_VERSION=12.1.0.40-1
                        
# 2023-11-10 13:14:23  0.00B 设置环境变量 NV_NVTX_VERSION
ENV NV_NVTX_VERSION=12.1.105-1
                        
# 2023-11-10 13:14:23  0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=12.1.1-1
                        
# 2023-11-10 13:07:30  0.00B 设置环境变量 NVIDIA_DRIVER_CAPABILITIES
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
                        
# 2023-11-10 13:07:30  0.00B 设置环境变量 NVIDIA_VISIBLE_DEVICES
ENV NVIDIA_VISIBLE_DEVICES=all
                        
# 2023-11-10 13:07:30  17.29KB 复制新文件或目录到容器中
COPY NGC-DL-CONTAINER-LICENSE / # buildkit
                        
# 2023-11-10 13:07:29  0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64
                        
# 2023-11-10 13:07:29  0.00B 设置环境变量 PATH
ENV PATH=/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
                        
# 2023-11-10 13:07:29  46.00B 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c echo "/usr/local/nvidia/lib" >> /etc/ld.so.conf.d/nvidia.conf     && echo "/usr/local/nvidia/lib64" >> /etc/ld.so.conf.d/nvidia.conf # buildkit
                        
# 2023-11-10 13:07:29  149.60MB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends     cuda-cudart-12-1=${NV_CUDA_CUDART_VERSION}     ${NV_CUDA_COMPAT_PACKAGE}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2023-11-10 13:07:08  0.00B 设置环境变量 CUDA_VERSION
ENV CUDA_VERSION=12.1.1
                        
# 2023-11-10 13:07:08  18.32MB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends     gnupg2 curl ca-certificates &&     curl -fsSL https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/${NVARCH}/3bf863cc.pub | apt-key add - &&     echo "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/${NVARCH} /" > /etc/apt/sources.list.d/cuda.list &&     apt-get purge --autoremove -y curl     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2023-11-10 13:07:08  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2023-11-10 13:07:08  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2023-11-10 13:07:08  0.00B 设置环境变量 NV_CUDA_COMPAT_PACKAGE
ENV NV_CUDA_COMPAT_PACKAGE=cuda-compat-12-1
                        
# 2023-11-10 13:07:08  0.00B 设置环境变量 NV_CUDA_CUDART_VERSION
ENV NV_CUDA_CUDART_VERSION=12.1.105-1
                        
# 2023-11-10 13:07:08  0.00B 设置环境变量 NVIDIA_REQUIRE_CUDA brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand
ENV NVIDIA_REQUIRE_CUDA=cuda>=12.1 brand=tesla,driver>=470,driver<471 brand=unknown,driver>=470,driver<471 brand=nvidia,driver>=470,driver<471 brand=nvidiartx,driver>=470,driver<471 brand=geforce,driver>=470,driver<471 brand=geforcertx,driver>=470,driver<471 brand=quadro,driver>=470,driver<471 brand=quadrortx,driver>=470,driver<471 brand=titan,driver>=470,driver<471 brand=titanrtx,driver>=470,driver<471 brand=tesla,driver>=525,driver<526 brand=unknown,driver>=525,driver<526 brand=nvidia,driver>=525,driver<526 brand=nvidiartx,driver>=525,driver<526 brand=geforce,driver>=525,driver<526 brand=geforcertx,driver>=525,driver<526 brand=quadro,driver>=525,driver<526 brand=quadrortx,driver>=525,driver<526 brand=titan,driver>=525,driver<526 brand=titanrtx,driver>=525,driver<526
                        
# 2023-11-10 13:07:08  0.00B 设置环境变量 NVARCH
ENV NVARCH=x86_64
                        
# 2023-10-03 18:45:52  0.00B 
/bin/sh -c #(nop)  CMD ["/bin/bash"]
                        
# 2023-10-03 18:45:51  72.79MB 
/bin/sh -c #(nop) ADD file:4809da414c2d478b4d991cbdaa2df457f2b3d07d0ff6cf673f09a66f90833e81 in / 
                        
# 2023-10-03 18:45:50  0.00B 
/bin/sh -c #(nop)  LABEL org.opencontainers.image.version=20.04
                        
# 2023-10-03 18:45:50  0.00B 
/bin/sh -c #(nop)  LABEL org.opencontainers.image.ref.name=ubuntu
                        
# 2023-10-03 18:45:50  0.00B 
/bin/sh -c #(nop)  ARG LAUNCHPAD_BUILD_ARCH
                        
# 2023-10-03 18:45:50  0.00B 
/bin/sh -c #(nop)  ARG RELEASE
                        
                    

镜像信息

{
    "Id": "sha256:ecb3f786af6cb6c838d3290933dfe10f022488defd8c1f606769cb151f83140d",
    "RepoTags": [
        "pytorch/pytorch:2.1.2-cuda12.1-cudnn8-devel",
        "swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:2.1.2-cuda12.1-cudnn8-devel"
    ],
    "RepoDigests": [
        "pytorch/pytorch@sha256:a5de097b482f5927baf2322f4419f11044bfe4f08c7b7593dbaff8e41d03a204",
        "swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch@sha256:a5de097b482f5927baf2322f4419f11044bfe4f08c7b7593dbaff8e41d03a204"
    ],
    "Parent": "",
    "Comment": "buildkit.dockerfile.v0",
    "Created": "2023-12-14T22:55:34.489319264Z",
    "Container": "",
    "ContainerConfig": null,
    "DockerVersion": "",
    "Author": "",
    "Config": {
        "Hostname": "",
        "Domainname": "",
        "User": "",
        "AttachStdin": false,
        "AttachStdout": false,
        "AttachStderr": false,
        "Tty": false,
        "OpenStdin": false,
        "StdinOnce": false,
        "Env": [
            "PATH=/opt/conda/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin",
            "NVARCH=x86_64",
            "NVIDIA_REQUIRE_CUDA=cuda\u003e=12.1 brand=tesla,driver\u003e=470,driver\u003c471 brand=unknown,driver\u003e=470,driver\u003c471 brand=nvidia,driver\u003e=470,driver\u003c471 brand=nvidiartx,driver\u003e=470,driver\u003c471 brand=geforce,driver\u003e=470,driver\u003c471 brand=geforcertx,driver\u003e=470,driver\u003c471 brand=quadro,driver\u003e=470,driver\u003c471 brand=quadrortx,driver\u003e=470,driver\u003c471 brand=titan,driver\u003e=470,driver\u003c471 brand=titanrtx,driver\u003e=470,driver\u003c471 brand=tesla,driver\u003e=525,driver\u003c526 brand=unknown,driver\u003e=525,driver\u003c526 brand=nvidia,driver\u003e=525,driver\u003c526 brand=nvidiartx,driver\u003e=525,driver\u003c526 brand=geforce,driver\u003e=525,driver\u003c526 brand=geforcertx,driver\u003e=525,driver\u003c526 brand=quadro,driver\u003e=525,driver\u003c526 brand=quadrortx,driver\u003e=525,driver\u003c526 brand=titan,driver\u003e=525,driver\u003c526 brand=titanrtx,driver\u003e=525,driver\u003c526",
            "NV_CUDA_CUDART_VERSION=12.1.105-1",
            "NV_CUDA_COMPAT_PACKAGE=cuda-compat-12-1",
            "CUDA_VERSION=12.1.1",
            "LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64",
            "NVIDIA_VISIBLE_DEVICES=all",
            "NVIDIA_DRIVER_CAPABILITIES=compute,utility",
            "NV_CUDA_LIB_VERSION=12.1.1-1",
            "NV_NVTX_VERSION=12.1.105-1",
            "NV_LIBNPP_VERSION=12.1.0.40-1",
            "NV_LIBNPP_PACKAGE=libnpp-12-1=12.1.0.40-1",
            "NV_LIBCUSPARSE_VERSION=12.1.0.106-1",
            "NV_LIBCUBLAS_PACKAGE_NAME=libcublas-12-1",
            "NV_LIBCUBLAS_VERSION=12.1.3.1-1",
            "NV_LIBCUBLAS_PACKAGE=libcublas-12-1=12.1.3.1-1",
            "NV_LIBNCCL_PACKAGE_NAME=libnccl2",
            "NV_LIBNCCL_PACKAGE_VERSION=2.17.1-1",
            "NCCL_VERSION=2.17.1-1",
            "NV_LIBNCCL_PACKAGE=libnccl2=2.17.1-1+cuda12.1",
            "NVIDIA_PRODUCT_NAME=CUDA",
            "NV_CUDA_CUDART_DEV_VERSION=12.1.105-1",
            "NV_NVML_DEV_VERSION=12.1.105-1",
            "NV_LIBCUSPARSE_DEV_VERSION=12.1.0.106-1",
            "NV_LIBNPP_DEV_VERSION=12.1.0.40-1",
            "NV_LIBNPP_DEV_PACKAGE=libnpp-dev-12-1=12.1.0.40-1",
            "NV_LIBCUBLAS_DEV_VERSION=12.1.3.1-1",
            "NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-12-1",
            "NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-12-1=12.1.3.1-1",
            "NV_CUDA_NSIGHT_COMPUTE_VERSION=12.1.1-1",
            "NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE=cuda-nsight-compute-12-1=12.1.1-1",
            "NV_NVPROF_VERSION=12.1.105-1",
            "NV_NVPROF_DEV_PACKAGE=cuda-nvprof-12-1=12.1.105-1",
            "NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev",
            "NV_LIBNCCL_DEV_PACKAGE_VERSION=2.17.1-1",
            "NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.17.1-1+cuda12.1",
            "LIBRARY_PATH=/usr/local/cuda/lib64/stubs",
            "NV_CUDNN_VERSION=8.9.0.131",
            "NV_CUDNN_PACKAGE_NAME=libcudnn8",
            "NV_CUDNN_PACKAGE=libcudnn8=8.9.0.131-1+cuda12.1",
            "NV_CUDNN_PACKAGE_DEV=libcudnn8-dev=8.9.0.131-1+cuda12.1",
            "PYTORCH_VERSION=2.1.2"
        ],
        "Cmd": null,
        "Image": "",
        "Volumes": null,
        "WorkingDir": "/workspace",
        "Entrypoint": [
            "/opt/nvidia/nvidia_entrypoint.sh"
        ],
        "OnBuild": null,
        "Labels": {
            "com.nvidia.cudnn.version": "8.9.0.131",
            "com.nvidia.volumes.needed": "nvidia_driver",
            "maintainer": "NVIDIA CORPORATION \u003ccudatools@nvidia.com\u003e",
            "org.opencontainers.image.ref.name": "ubuntu",
            "org.opencontainers.image.version": "20.04"
        }
    },
    "Architecture": "amd64",
    "Os": "linux",
    "Size": 16581332651,
    "GraphDriver": {
        "Data": {
            "LowerDir": "/var/lib/docker/overlay2/a96348d4b49ed1d51777423326234f204e59b493eebb1e61b8b1663faec27c30/diff:/var/lib/docker/overlay2/26140b1993894c470d2d0b05cf35fe709fae0d3e74483c7b7119a037bd9b322a/diff:/var/lib/docker/overlay2/4abbbc1a10c41e8099082106120e1aad3d3cdef0515967a5c4d30d6d2b1188e0/diff:/var/lib/docker/overlay2/2ab7237bbeb888d3bb638a08cdf360496ae6feaa75d3afe77b325e83abf803f0/diff:/var/lib/docker/overlay2/5c2da65e1b270ac4a65c0382ac0b4d690d838cd0c40ea1b6ab3c053f31f75130/diff:/var/lib/docker/overlay2/26e3ae85ec1ecc24fa36748c944ab1687d12fbf18e154f9625ea7998efbc2b2e/diff:/var/lib/docker/overlay2/60cfffdfd5d6da4856662d7742fdb4e2cbf332c4b133fdfaedffe12719cfdb8a/diff:/var/lib/docker/overlay2/ac6566151b7b80919fd83449e9edc32b40d6d7e1c62d96f5855eb0733169b80f/diff:/var/lib/docker/overlay2/02a75db65b8c924a24a2e60402972314d74ff88a9c601d530a6290a637f09cf5/diff:/var/lib/docker/overlay2/d6f53d118586523128473ec10b384949d73a3ae829f678b6d3114e98d733c18c/diff:/var/lib/docker/overlay2/1c67b81030a3575d1b2acdb1023ffb082b746c945c36169d42f270f10257e8ba/diff:/var/lib/docker/overlay2/49db94fe7fffa899861a78533d159271d4001714b12db3f398f7b31a3a87fab2/diff:/var/lib/docker/overlay2/2d6cb7e705ae6a99298c37eda96d14353aec1fd6aa11b64e360944e7029e8209/diff:/var/lib/docker/overlay2/ae20d07f8bee6f73ce435322bd2401fa7023008b45427de43f46b92d069076e7/diff:/var/lib/docker/overlay2/5408abd3ec726f4d055e10fddd8f488a8839c8a355fe1fb064cdc9fee660e07b/diff",
            "MergedDir": "/var/lib/docker/overlay2/16ca85c5cedd3c139d4b2a5955c8ac824d71a35f70d5f2c7712843f5a22afea3/merged",
            "UpperDir": "/var/lib/docker/overlay2/16ca85c5cedd3c139d4b2a5955c8ac824d71a35f70d5f2c7712843f5a22afea3/diff",
            "WorkDir": "/var/lib/docker/overlay2/16ca85c5cedd3c139d4b2a5955c8ac824d71a35f70d5f2c7712843f5a22afea3/work"
        },
        "Name": "overlay2"
    },
    "RootFS": {
        "Type": "layers",
        "Layers": [
            "sha256:6c3e7df31590f02f10cb71fc4eb27653e9b428df2e6e5421a455b062bd2e39f9",
            "sha256:5c0359201b8f5316a9c120cc074c134e6294e6351b6ba4384a843006f6716dd0",
            "sha256:f620bf47e83df6cb9d61bf1728402f88549bca976b3047f9cb69d03be03dc21b",
            "sha256:8d78458ccbe218dba1de0b340767e15e4693d7041f6407b69b82caed09c08e0b",
            "sha256:9dbd6d766fae94f829384e71cf3ff5fedfea9f448d4069d0ce87f3d544d19ecc",
            "sha256:379cd604fb89fd203f52b15d2f09fb14f70fc08cbe9655154a4f478ab72c5d93",
            "sha256:82adc44e81b3913c7215be048da7cae287149aba6fdcaf08065662a15d8b4e85",
            "sha256:cca411d699bf4af0a4bc8f047be6f79365f026d1458f74be6a9b2d80de2514de",
            "sha256:226146661e721e03f1d7fc62bbc58adf2e8185f06c3b794624b6f5efefc28b9c",
            "sha256:0e5e6a7b15e48919ddbaf00ab643e058050d95a02f4e2f0fc84b8a1a0f56e552",
            "sha256:ad6bf06f23c6a368ade44418b3fa62a77964c45a9df1a0533434ec5ea1670a65",
            "sha256:3f2f263da0ed97f11f383e9b75db8a060c158e413aabf96ebd2a385c306b8420",
            "sha256:8eb85b561415846effcfe5ea621605cdace820a7b72511ff355264f368170296",
            "sha256:6888845e0d270797afcef96036b74bfb1315830706c569742c8dd9bb88697a77",
            "sha256:87bdf5cff876652faf60854b66b2557b6aa80669d5900d600d162aa4ff14186e",
            "sha256:ae8f674b18e3cdff4083802aeb77c0f603592fa9d9529bef262d439d36000e73"
        ]
    },
    "Metadata": {
        "LastTagTime": "2024-12-20T00:05:49.254685443+08:00"
    }
}

更多版本

docker.io/pytorch/pytorch:2.3.0-cuda12.1-cudnn8-runtime

linux/amd64 docker.io7.71GB2024-07-18 11:25
1157

docker.io/pytorch/pytorch:2.0.1-cuda11.7-cudnn8-runtime

linux/amd64 docker.io6.48GB2024-07-26 13:31
845

docker.io/pytorch/pytorch:2.3.0-cuda12.1-cudnn8-devel

linux/amd64 docker.io17.08GB2024-08-06 11:11
649

docker.io/pytorch/pytorch:2.4.1-cuda12.4-cudnn9-runtime

linux/amd64 docker.io5.99GB2024-09-21 01:42
719

docker.io/pytorch/pytorch:2.2.1-cuda12.1-cudnn8-runtime

linux/amd64 docker.io7.60GB2024-09-25 04:29
278

docker.io/pytorch/pytorch:2.4.1-cuda11.8-cudnn9-runtime

linux/amd64 docker.io6.36GB2024-09-28 00:59
313

docker.io/pytorch/pytorch:2.1.0-cuda11.8-cudnn8-devel

linux/amd64 docker.io17.39GB2024-10-02 00:43
246

docker.io/pytorch/pytorch:2.4.1-cuda11.8-cudnn9-devel

linux/amd64 docker.io13.63GB2024-10-23 00:32
182

docker.io/pytorch/pytorch:2.0.1-cuda11.7-cudnn8-devel

linux/amd64 docker.io13.17GB2024-11-01 00:22
301

docker.io/pytorch/pytorch:2.5.1-cuda12.4-cudnn9-devel

linux/amd64 docker.io13.31GB2024-11-06 01:09
155

docker.io/pytorch/pytorch:2.5.1-cuda12.4-cudnn9-runtime

linux/amd64 docker.io6.14GB2024-11-06 01:24
198

docker.io/pytorch/pytorch:2.5.0-cuda12.4-cudnn9-runtime

linux/amd64 docker.io6.13GB2024-11-06 01:38
100

docker.io/pytorch/pytorch:2.5.0-cuda12.4-cudnn9-devel

linux/amd64 docker.io13.30GB2024-11-06 01:51
95

docker.io/pytorch/pytorch:2.5.1-cuda12.1-cudnn9-runtime

linux/amd64 docker.io5.90GB2024-11-07 00:14
154

docker.io/pytorch/pytorch:2.3.1-cuda11.8-cudnn8-runtime

linux/amd64 docker.io8.17GB2024-11-08 00:19
86

docker.io/pytorch/pytorch:2.3.1-cuda12.1-cudnn8-devel

linux/amd64 docker.io17.08GB2024-11-08 00:39
85

docker.io/pytorch/pytorch:1.13.1-cuda11.6-cudnn8-devel

linux/amd64 docker.io17.52GB2024-11-08 01:12
121

docker.io/pytorch/pytorch:2.1.2-cuda11.8-cudnn8-devel

linux/amd64 docker.io17.33GB2024-12-10 00:33
70

docker.io/pytorch/pytorch:2.2.0-cuda12.1-cudnn8-devel

linux/amd64 docker.io16.99GB2024-12-15 00:21
59

docker.io/pytorch/pytorch:2.1.2-cuda12.1-cudnn8-devel

linux/amd64 docker.io16.58GB2024-12-20 00:05
47

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

linux/amd64 docker.io7.22GB2025-01-10 00:32
22

docker.io/pytorch/pytorch:2.0.0-cuda11.7-cudnn8-devel

linux/amd64 docker.io13.10GB2025-01-11 00:22
24