docker.io/pytorch/pytorch:1.13.1-cuda11.6-cudnn8-devel linux/amd64

docker.io/pytorch/pytorch:1.13.1-cuda11.6-cudnn8-devel - 国内下载镜像源 浏览次数:38 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:1.13.1-cuda11.6-cudnn8-devel
国内镜像 swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:1.13.1-cuda11.6-cudnn8-devel
镜像ID sha256:8426c5657bef5e71d50753670cc615e2e255bcc1a092dd3f855c0f55a7e8677f
镜像TAG 1.13.1-cuda11.6-cudnn8-devel
大小 17.52GB
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 38 次
贡献者
镜像创建 2022-12-20T13:28:52.592781304-08:00
同步时间 2024-11-08 01:12
更新时间 2024-11-21 07:30
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>=11.6 brand=tesla,driver>=418,driver<419 brand=tesla,driver>=450,driver<451 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 NV_CUDA_CUDART_VERSION=11.6.55-1 NV_CUDA_COMPAT_PACKAGE=cuda-compat-11-6 CUDA_VERSION=11.6.2 LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64 NVIDIA_VISIBLE_DEVICES=all NVIDIA_DRIVER_CAPABILITIES=compute,utility NV_CUDA_LIB_VERSION=11.6.2-1 NV_NVTX_VERSION=11.6.124-1 NV_LIBNPP_VERSION=11.6.3.124-1 NV_LIBNPP_PACKAGE=libnpp-11-6=11.6.3.124-1 NV_LIBCUSPARSE_VERSION=11.7.2.124-1 NV_LIBCUBLAS_PACKAGE_NAME=libcublas-11-6 NV_LIBCUBLAS_VERSION=11.9.2.110-1 NV_LIBCUBLAS_PACKAGE=libcublas-11-6=11.9.2.110-1 NV_LIBNCCL_PACKAGE_NAME=libnccl2 NV_LIBNCCL_PACKAGE_VERSION=2.12.10-1 NCCL_VERSION=2.12.10-1 NV_LIBNCCL_PACKAGE=libnccl2=2.12.10-1+cuda11.6 NVIDIA_PRODUCT_NAME=CUDA NV_CUDA_CUDART_DEV_VERSION=11.6.55-1 NV_NVML_DEV_VERSION=11.6.55-1 NV_LIBCUSPARSE_DEV_VERSION=11.7.2.124-1 NV_LIBNPP_DEV_VERSION=11.6.3.124-1 NV_LIBNPP_DEV_PACKAGE=libnpp-dev-11-6=11.6.3.124-1 NV_LIBCUBLAS_DEV_VERSION=11.9.2.110-1 NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-11-6 NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-11-6=11.9.2.110-1 NV_NVPROF_VERSION=11.6.124-1 NV_NVPROF_DEV_PACKAGE=cuda-nvprof-11-6=11.6.124-1 NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev NV_LIBNCCL_DEV_PACKAGE_VERSION=2.12.10-1 NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.12.10-1+cuda11.6 LIBRARY_PATH=/usr/local/cuda/lib64/stubs NV_CUDNN_VERSION=8.4.0.27 NV_CUDNN_PACKAGE_NAME=libcudnn8 NV_CUDNN_PACKAGE=libcudnn8=8.4.0.27-1+cuda11.6 NV_CUDNN_PACKAGE_DEV=libcudnn8-dev=8.4.0.27-1+cuda11.6 PYTORCH_VERSION=v1.13.1
镜像标签
8.4.0.27: com.nvidia.cudnn.version nvidia_driver: com.nvidia.volumes.needed NVIDIA CORPORATION <cudatools@nvidia.com>: maintainer
镜像安全扫描 查看Trivy扫描报告

系统OS: ubuntu 18.04 扫描引擎: Trivy 扫描时间: 2024-11-08 01:16

低危漏洞:48 中危漏洞:209 高危漏洞:28 严重漏洞:0
docker.io/pytorch/pytorch:1.13.1-cuda11.6-cudnn8-devel (ubuntu 18.04) (ubuntu) Java (jar) Python (python-pkg)

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:1.13.1-cuda11.6-cudnn8-devel
docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:1.13.1-cuda11.6-cudnn8-devel  docker.io/pytorch/pytorch:1.13.1-cuda11.6-cudnn8-devel

Containerd拉取命令 

ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:1.13.1-cuda11.6-cudnn8-devel
ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:1.13.1-cuda11.6-cudnn8-devel  docker.io/pytorch/pytorch:1.13.1-cuda11.6-cudnn8-devel

Shell快速替换命令 

sed -i 's#pytorch/pytorch:1.13.1-cuda11.6-cudnn8-devel#swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:1.13.1-cuda11.6-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:1.13.1-cuda11.6-cudnn8-devel && docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:1.13.1-cuda11.6-cudnn8-devel  docker.io/pytorch/pytorch:1.13.1-cuda11.6-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:1.13.1-cuda11.6-cudnn8-devel && ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:1.13.1-cuda11.6-cudnn8-devel  docker.io/pytorch/pytorch:1.13.1-cuda11.6-cudnn8-devel'

镜像历史

大小 创建时间 层信息
0.00B 2022-12-21 05:28:52 WORKDIR /workspace
0.00B 2022-12-21 05:28:51 ENV PYTORCH_VERSION=v1.13.1
0.00B 2022-12-21 05:28:51 ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64
0.00B 2022-12-21 05:28:51 ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
0.00B 2022-12-21 05:28:51 ENV NVIDIA_VISIBLE_DEVICES=all
0.00B 2022-12-21 05:28:51 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
9.86GB 2022-12-21 05:28:51 COPY /opt/conda /opt/conda # buildkit
2.99MB 2022-12-21 05:19:32 RUN |1 PYTORCH_VERSION=v1.13.1 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends ca-certificates libjpeg-dev libpng-dev && rm -rf /var/lib/apt/lists/* # buildkit
0.00B 2022-12-21 05:19:32 LABEL com.nvidia.volumes.needed=nvidia_driver
0.00B 2022-12-21 05:19:32 ARG PYTORCH_VERSION
2.81GB 2022-12-17 09:16:49 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
0.00B 2022-12-17 09:16:49 LABEL com.nvidia.cudnn.version=8.4.0.27
0.00B 2022-12-17 09:16:49 LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
0.00B 2022-12-17 09:16:49 ARG TARGETARCH
0.00B 2022-12-17 09:16:49 ENV NV_CUDNN_PACKAGE_DEV=libcudnn8-dev=8.4.0.27-1+cuda11.6
0.00B 2022-12-17 09:16:49 ENV NV_CUDNN_PACKAGE=libcudnn8=8.4.0.27-1+cuda11.6
0.00B 2022-12-17 09:16:49 ENV NV_CUDNN_PACKAGE_NAME=libcudnn8
0.00B 2022-12-17 09:16:49 ENV NV_CUDNN_VERSION=8.4.0.27
0.00B 2022-12-15 04:43:48 ENV LIBRARY_PATH=/usr/local/cuda/lib64/stubs
371.26KB 2022-12-15 04:43:48 RUN |1 TARGETARCH=amd64 /bin/sh -c apt-mark hold ${NV_LIBCUBLAS_DEV_PACKAGE_NAME} ${NV_LIBNCCL_DEV_PACKAGE_NAME} # buildkit
2.81GB 2022-12-15 04:43:46 RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends cuda-cudart-dev-11-6=${NV_CUDA_CUDART_DEV_VERSION} cuda-command-line-tools-11-6=${NV_CUDA_LIB_VERSION} cuda-minimal-build-11-6=${NV_CUDA_LIB_VERSION} cuda-libraries-dev-11-6=${NV_CUDA_LIB_VERSION} cuda-nvml-dev-11-6=${NV_NVML_DEV_VERSION} ${NV_NVPROF_DEV_PACKAGE} ${NV_LIBNPP_DEV_PACKAGE} libcusparse-dev-11-6=${NV_LIBCUSPARSE_DEV_VERSION} ${NV_LIBCUBLAS_DEV_PACKAGE} ${NV_LIBNCCL_DEV_PACKAGE} && rm -rf /var/lib/apt/lists/* # buildkit
0.00B 2022-12-15 04:43:46 LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
0.00B 2022-12-15 04:43:46 ARG TARGETARCH
0.00B 2022-12-15 04:43:46 ENV NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.12.10-1+cuda11.6
0.00B 2022-12-15 04:43:46 ENV NCCL_VERSION=2.12.10-1
0.00B 2022-12-15 04:43:46 ENV NV_LIBNCCL_DEV_PACKAGE_VERSION=2.12.10-1
0.00B 2022-12-15 04:43:46 ENV NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev
0.00B 2022-12-15 04:43:46 ENV NV_NVPROF_DEV_PACKAGE=cuda-nvprof-11-6=11.6.124-1
0.00B 2022-12-15 04:43:46 ENV NV_NVPROF_VERSION=11.6.124-1
0.00B 2022-12-15 04:43:46 ENV NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-11-6=11.9.2.110-1
0.00B 2022-12-15 04:43:46 ENV NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-11-6
0.00B 2022-12-15 04:43:46 ENV NV_LIBCUBLAS_DEV_VERSION=11.9.2.110-1
0.00B 2022-12-15 04:43:46 ENV NV_LIBNPP_DEV_PACKAGE=libnpp-dev-11-6=11.6.3.124-1
0.00B 2022-12-15 04:43:46 ENV NV_LIBNPP_DEV_VERSION=11.6.3.124-1
0.00B 2022-12-15 04:43:46 ENV NV_LIBCUSPARSE_DEV_VERSION=11.7.2.124-1
0.00B 2022-12-15 04:43:46 ENV NV_NVML_DEV_VERSION=11.6.55-1
0.00B 2022-12-15 04:43:46 ENV NV_CUDA_CUDART_DEV_VERSION=11.6.55-1
0.00B 2022-12-15 04:43:46 ENV NV_CUDA_LIB_VERSION=11.6.2-1
0.00B 2022-12-15 04:34:59 ENTRYPOINT ["/opt/nvidia/nvidia_entrypoint.sh"]
0.00B 2022-12-15 04:34:59 ENV NVIDIA_PRODUCT_NAME=CUDA
2.53KB 2022-12-15 04:34:59 COPY nvidia_entrypoint.sh /opt/nvidia/ # buildkit
3.04KB 2022-12-15 04:34:59 COPY entrypoint.d/ /opt/nvidia/entrypoint.d/ # buildkit
258.50KB 2022-12-15 04:34:58 RUN |1 TARGETARCH=amd64 /bin/sh -c apt-mark hold ${NV_LIBCUBLAS_PACKAGE_NAME} ${NV_LIBNCCL_PACKAGE_NAME} # buildkit
1.89GB 2022-12-15 04:34:58 RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends cuda-libraries-11-6=${NV_CUDA_LIB_VERSION} ${NV_LIBNPP_PACKAGE} cuda-nvtx-11-6=${NV_NVTX_VERSION} libcusparse-11-6=${NV_LIBCUSPARSE_VERSION} ${NV_LIBCUBLAS_PACKAGE} ${NV_LIBNCCL_PACKAGE} && rm -rf /var/lib/apt/lists/* # buildkit
0.00B 2022-12-15 04:34:58 LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
0.00B 2022-12-15 04:34:58 ARG TARGETARCH
0.00B 2022-12-15 04:34:58 ENV NV_LIBNCCL_PACKAGE=libnccl2=2.12.10-1+cuda11.6
0.00B 2022-12-15 04:34:58 ENV NCCL_VERSION=2.12.10-1
0.00B 2022-12-15 04:34:58 ENV NV_LIBNCCL_PACKAGE_VERSION=2.12.10-1
0.00B 2022-12-15 04:34:58 ENV NV_LIBNCCL_PACKAGE_NAME=libnccl2
0.00B 2022-12-15 04:34:58 ENV NV_LIBCUBLAS_PACKAGE=libcublas-11-6=11.9.2.110-1
0.00B 2022-12-15 04:34:58 ENV NV_LIBCUBLAS_VERSION=11.9.2.110-1
0.00B 2022-12-15 04:34:58 ENV NV_LIBCUBLAS_PACKAGE_NAME=libcublas-11-6
0.00B 2022-12-15 04:34:58 ENV NV_LIBCUSPARSE_VERSION=11.7.2.124-1
0.00B 2022-12-15 04:34:58 ENV NV_LIBNPP_PACKAGE=libnpp-11-6=11.6.3.124-1
0.00B 2022-12-15 04:34:58 ENV NV_LIBNPP_VERSION=11.6.3.124-1
0.00B 2022-12-15 04:34:58 ENV NV_NVTX_VERSION=11.6.124-1
0.00B 2022-12-15 04:34:58 ENV NV_CUDA_LIB_VERSION=11.6.2-1
0.00B 2022-12-15 04:29:36 ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
0.00B 2022-12-15 04:29:36 ENV NVIDIA_VISIBLE_DEVICES=all
16.05KB 2022-12-15 04:29:36 COPY NGC-DL-CONTAINER-LICENSE / # buildkit
0.00B 2022-12-15 04:29:36 ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64
0.00B 2022-12-15 04:29:36 ENV PATH=/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
46.00B 2022-12-15 04:29:36 RUN |1 TARGETARCH=amd64 /bin/sh -c echo "/usr/local/nvidia/lib" >> /etc/ld.so.conf.d/nvidia.conf && echo "/usr/local/nvidia/lib64" >> /etc/ld.so.conf.d/nvidia.conf # buildkit
62.89MB 2022-12-15 04:29:35 RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends cuda-cudart-11-6=${NV_CUDA_CUDART_VERSION} ${NV_CUDA_COMPAT_PACKAGE} && rm -rf /var/lib/apt/lists/* # buildkit
0.00B 2022-12-15 04:29:24 ENV CUDA_VERSION=11.6.2
16.52MB 2022-12-15 04:29:24 RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends gnupg2 curl ca-certificates && curl -fsSL https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/${NVARCH}/3bf863cc.pub | apt-key add - && echo "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/${NVARCH} /" > /etc/apt/sources.list.d/cuda.list && apt-get purge --autoremove -y curl && rm -rf /var/lib/apt/lists/* # buildkit
0.00B 2022-12-15 04:29:24 LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
0.00B 2022-12-15 04:29:24 ARG TARGETARCH
0.00B 2022-12-15 04:29:24 ENV NV_CUDA_COMPAT_PACKAGE=cuda-compat-11-6
0.00B 2022-12-15 04:29:24 ENV NV_CUDA_CUDART_VERSION=11.6.55-1
0.00B 2022-12-15 04:29:24 ENV NVIDIA_REQUIRE_CUDA=cuda>=11.6 brand=tesla,driver>=418,driver<419 brand=tesla,driver>=450,driver<451 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
0.00B 2022-12-15 04:29:24 ENV NVARCH=x86_64
0.00B 2022-12-09 09:20:12 /bin/sh -c #(nop) CMD ["bash"]
63.15MB 2022-12-09 09:20:11 /bin/sh -c #(nop) ADD file:3c88cea17de40599dc8b8da90adc8439635066835e930f9573ec6cc856c5c096 in /

镜像信息 

{
    "Id": "sha256:8426c5657bef5e71d50753670cc615e2e255bcc1a092dd3f855c0f55a7e8677f",
    "RepoTags": [
        "pytorch/pytorch:1.13.1-cuda11.6-cudnn8-devel",
        "swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:1.13.1-cuda11.6-cudnn8-devel"
    ],
    "RepoDigests": [
        "pytorch/pytorch@sha256:58d848c38665fd3ed20bee65918255cb083637c860eb4fae67face2fb2ff5702",
        "swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch@sha256:58d848c38665fd3ed20bee65918255cb083637c860eb4fae67face2fb2ff5702"
    ],
    "Parent": "",
    "Comment": "buildkit.dockerfile.v0",
    "Created": "2022-12-20T13:28:52.592781304-08:00",
    "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=11.6 brand=tesla,driver\u003e=418,driver\u003c419 brand=tesla,driver\u003e=450,driver\u003c451 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",
            "NV_CUDA_CUDART_VERSION=11.6.55-1",
            "NV_CUDA_COMPAT_PACKAGE=cuda-compat-11-6",
            "CUDA_VERSION=11.6.2",
            "LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64",
            "NVIDIA_VISIBLE_DEVICES=all",
            "NVIDIA_DRIVER_CAPABILITIES=compute,utility",
            "NV_CUDA_LIB_VERSION=11.6.2-1",
            "NV_NVTX_VERSION=11.6.124-1",
            "NV_LIBNPP_VERSION=11.6.3.124-1",
            "NV_LIBNPP_PACKAGE=libnpp-11-6=11.6.3.124-1",
            "NV_LIBCUSPARSE_VERSION=11.7.2.124-1",
            "NV_LIBCUBLAS_PACKAGE_NAME=libcublas-11-6",
            "NV_LIBCUBLAS_VERSION=11.9.2.110-1",
            "NV_LIBCUBLAS_PACKAGE=libcublas-11-6=11.9.2.110-1",
            "NV_LIBNCCL_PACKAGE_NAME=libnccl2",
            "NV_LIBNCCL_PACKAGE_VERSION=2.12.10-1",
            "NCCL_VERSION=2.12.10-1",
            "NV_LIBNCCL_PACKAGE=libnccl2=2.12.10-1+cuda11.6",
            "NVIDIA_PRODUCT_NAME=CUDA",
            "NV_CUDA_CUDART_DEV_VERSION=11.6.55-1",
            "NV_NVML_DEV_VERSION=11.6.55-1",
            "NV_LIBCUSPARSE_DEV_VERSION=11.7.2.124-1",
            "NV_LIBNPP_DEV_VERSION=11.6.3.124-1",
            "NV_LIBNPP_DEV_PACKAGE=libnpp-dev-11-6=11.6.3.124-1",
            "NV_LIBCUBLAS_DEV_VERSION=11.9.2.110-1",
            "NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-11-6",
            "NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-11-6=11.9.2.110-1",
            "NV_NVPROF_VERSION=11.6.124-1",
            "NV_NVPROF_DEV_PACKAGE=cuda-nvprof-11-6=11.6.124-1",
            "NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev",
            "NV_LIBNCCL_DEV_PACKAGE_VERSION=2.12.10-1",
            "NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.12.10-1+cuda11.6",
            "LIBRARY_PATH=/usr/local/cuda/lib64/stubs",
            "NV_CUDNN_VERSION=8.4.0.27",
            "NV_CUDNN_PACKAGE_NAME=libcudnn8",
            "NV_CUDNN_PACKAGE=libcudnn8=8.4.0.27-1+cuda11.6",
            "NV_CUDNN_PACKAGE_DEV=libcudnn8-dev=8.4.0.27-1+cuda11.6",
            "PYTORCH_VERSION=v1.13.1"
        ],
        "Cmd": null,
        "Image": "",
        "Volumes": null,
        "WorkingDir": "/workspace",
        "Entrypoint": [
            "/opt/nvidia/nvidia_entrypoint.sh"
        ],
        "OnBuild": null,
        "Labels": {
            "com.nvidia.cudnn.version": "8.4.0.27",
            "com.nvidia.volumes.needed": "nvidia_driver",
            "maintainer": "NVIDIA CORPORATION \u003ccudatools@nvidia.com\u003e"
        }
    },
    "Architecture": "amd64",
    "Os": "linux",
    "Size": 17517597870,
    "GraphDriver": {
        "Data": {
            "LowerDir": "/var/lib/docker/overlay2/55901c136085b684808f554f4f5e0347e428d5908588a7302320f105591fc167/diff:/var/lib/docker/overlay2/5c58cb36102f9941e0d99ae22b926141b3e735da6fc1c60ef3f123c8af3dae0a/diff:/var/lib/docker/overlay2/28ba894cb6be2d8617008ada7249918ca1324db9e0b938332e6d08d8d0c1d290/diff:/var/lib/docker/overlay2/8a50c65546c89c601cccbfa98ff5261dd76ee3354d3baccb6da498465742b270/diff:/var/lib/docker/overlay2/00ec0ab0a6fe8f31cf176b585e9a4045dc26d76c9db967cc8f8b42811acc25bf/diff:/var/lib/docker/overlay2/d58d03b91e6e3784319aa82bcf90a91f69365f93d22b5fcb8ede68b88769c5db/diff:/var/lib/docker/overlay2/ccc8ea55975a8ad616b29e7f84add26804041195b068c3e922c2f78cda7c9f7c/diff:/var/lib/docker/overlay2/f3088bd27ed9898f31bf3bf2e3b999c18cc8aabe7ecfa0d83efa23aa8d7c9eab/diff:/var/lib/docker/overlay2/6823b52b2db7d6dfea3e2d95eb3356977fa57dc2d6f4df1d1e6aa14491909fe4/diff:/var/lib/docker/overlay2/84e7c596b1904a7eb3ad7c76ca58a2c276bad3643b0457323437e857dcec4888/diff:/var/lib/docker/overlay2/b03f2e1f42c35741ca0ad187865f761ec4f5097cfab142ff3b8a16883b367773/diff:/var/lib/docker/overlay2/134ad7381f3d45d615d9d424e697d19a51a4f4e1b04bfeb207303f6f6f4db7c2/diff:/var/lib/docker/overlay2/9b8921a87e7f7f7ea8802fad6ca4bb0bba004db01dbd7e926b52abc3d554558a/diff:/var/lib/docker/overlay2/d104eb8c1101a0fef33a825efee6964cdb39dc4414020fbf19a87bc7ccb902ef/diff",
            "MergedDir": "/var/lib/docker/overlay2/4c1fae7ee50e16f46da3e2fc36bb997088574d5dc25f245d060845f8f76edc28/merged",
            "UpperDir": "/var/lib/docker/overlay2/4c1fae7ee50e16f46da3e2fc36bb997088574d5dc25f245d060845f8f76edc28/diff",
            "WorkDir": "/var/lib/docker/overlay2/4c1fae7ee50e16f46da3e2fc36bb997088574d5dc25f245d060845f8f76edc28/work"
        },
        "Name": "overlay2"
    },
    "RootFS": {
        "Type": "layers",
        "Layers": [
            "sha256:45bbe3d22998589317c7f6c4dd591475423bb37ca9b922529c5878653483b18d",
            "sha256:02241d7931829bb1c4072eb73959cf683686072b1653047cbc8dedb168b5be3d",
            "sha256:09276aea35f27deeb2ddc6da3332a93e22c3f398b625bfda8eca23b3f291844d",
            "sha256:5d930ae5d1b7b5a8f95c5a4e7714b23e79690d3ee28cc62fec5613337753a064",
            "sha256:3412d56495edb8b2d5e4cb28c8b9ce1d5baa4ecd55c175c176cc19068c6f6d35",
            "sha256:eb168e05fd2ed2d639caf2f0e935acede848439bcef168c6f3b09bb382e25108",
            "sha256:96e98a929bfc6eb72d5ddb703c3b07aee4a1e0b167f92da9e53b759b1c429002",
            "sha256:0c8341e8115e8d516fa0f17a5583aa42d5b65cad83d3958b6547dc83e9d88d7f",
            "sha256:7d36ccf3d469643f3dd1e493c25d8b726b0e830504c70df8b4ebb9f08af4a4bc",
            "sha256:5cb0539b8277ab0c0d4380d05a217885e856d9120be11d140d76a68c4ad8a600",
            "sha256:2f74ae2e2e0a97f1f31faf07d2c63c2aba7afdb6592efa40ac7e330bd6ced495",
            "sha256:600c8b125d324ab4673632fc99f23c08dd2ed28c96a47250d646ae86905de12b",
            "sha256:521931c43709d34997c159b396440b042c612699faa2a40690ab065c0264da3c",
            "sha256:1994aef78bb048480e2e14c3971336f7ae4b455ce3744b0ca3b7bd049c895b7c",
            "sha256:8a5e1420334970775151a54a80f4b93fbb41688141fbb5e70c4c8e496841db59"
        ]
    },
    "Metadata": {
        "LastTagTime": "2024-11-08T00:51:27.203379227+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
978

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

linux/amd64 docker.io6.48GB2024-07-26 13:31
684

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

linux/amd64 docker.io17.08GB2024-08-06 11:11
549

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

linux/amd64 docker.io5.99GB2024-09-21 01:42
550

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

linux/amd64 docker.io7.60GB2024-09-25 04:29
200

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

linux/amd64 docker.io6.36GB2024-09-28 00:59
235

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

linux/amd64 docker.io17.39GB2024-10-02 00:43
161

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

linux/amd64 docker.io13.63GB2024-10-23 00:32
116

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

linux/amd64 docker.io13.17GB2024-11-01 00:22
209

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

linux/amd64 docker.io13.31GB2024-11-06 01:09
46

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

linux/amd64 docker.io6.14GB2024-11-06 01:24
51

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

linux/amd64 docker.io6.13GB2024-11-06 01:38
29

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

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

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

linux/amd64 docker.io5.90GB2024-11-07 00:14
44

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

linux/amd64 docker.io8.17GB2024-11-08 00:19
28

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

linux/amd64 docker.io17.08GB2024-11-08 00:39
34

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

linux/amd64 docker.io17.52GB2024-11-08 01:12
37