docker.io/pytorch/pytorch:2.4.1-cuda11.8-cudnn9-devel linux/amd64

docker.io/pytorch/pytorch:2.4.1-cuda11.8-cudnn9-devel - 国内下载镜像源 浏览次数:116 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:2.4.1-cuda11.8-cudnn9-devel
国内镜像 swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:2.4.1-cuda11.8-cudnn9-devel
镜像ID sha256:c7cbbe35f744eb877e8f2f7c0dc89f1acc5f4f90e040fa6e204329ae9f871fb3
镜像TAG 2.4.1-cuda11.8-cudnn9-devel
大小 13.63GB
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 116 次
贡献者
镜像创建 2024-09-04T19:56:42.029798501Z
同步时间 2024-10-23 00:32
更新时间 2024-11-21 15:23
环境变量
PATH=/usr/local/nvidia/bin:/usr/local/cuda/bin:/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>=11.8 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=11.8.89-1 NV_CUDA_COMPAT_PACKAGE=cuda-compat-11-8 CUDA_VERSION=11.8.0 LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64 NVIDIA_VISIBLE_DEVICES=all NVIDIA_DRIVER_CAPABILITIES=compute,utility NV_CUDA_LIB_VERSION=11.8.0-1 NV_NVTX_VERSION=11.8.86-1 NV_LIBNPP_VERSION=11.8.0.86-1 NV_LIBNPP_PACKAGE=libnpp-11-8=11.8.0.86-1 NV_LIBCUSPARSE_VERSION=11.7.5.86-1 NV_LIBCUBLAS_PACKAGE_NAME=libcublas-11-8 NV_LIBCUBLAS_VERSION=11.11.3.6-1 NV_LIBCUBLAS_PACKAGE=libcublas-11-8=11.11.3.6-1 NV_LIBNCCL_PACKAGE_NAME=libnccl2 NV_LIBNCCL_PACKAGE_VERSION=2.15.5-1 NCCL_VERSION=2.15.5-1 NV_LIBNCCL_PACKAGE=libnccl2=2.15.5-1+cuda11.8 NVIDIA_PRODUCT_NAME=CUDA NV_CUDA_CUDART_DEV_VERSION=11.8.89-1 NV_NVML_DEV_VERSION=11.8.86-1 NV_LIBCUSPARSE_DEV_VERSION=11.7.5.86-1 NV_LIBNPP_DEV_VERSION=11.8.0.86-1 NV_LIBNPP_DEV_PACKAGE=libnpp-dev-11-8=11.8.0.86-1 NV_LIBCUBLAS_DEV_VERSION=11.11.3.6-1 NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-11-8 NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-11-8=11.11.3.6-1 NV_CUDA_NSIGHT_COMPUTE_VERSION=11.8.0-1 NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE=cuda-nsight-compute-11-8=11.8.0-1 NV_NVPROF_VERSION=11.8.87-1 NV_NVPROF_DEV_PACKAGE=cuda-nvprof-11-8=11.8.87-1 NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev NV_LIBNCCL_DEV_PACKAGE_VERSION=2.15.5-1 NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.15.5-1+cuda11.8 LIBRARY_PATH=/usr/local/cuda/lib64/stubs PYTORCH_VERSION=2.4.1
镜像标签
nvidia_driver: com.nvidia.volumes.needed NVIDIA CORPORATION <cudatools@nvidia.com>: maintainer ubuntu: org.opencontainers.image.ref.name 22.04: org.opencontainers.image.version
镜像安全扫描 查看Trivy扫描报告

系统OS: ubuntu 22.04 扫描引擎: Trivy 扫描时间: 2024-10-27 02:27

低危漏洞:224 中危漏洞:1694 高危漏洞:37 严重漏洞:0

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:2.4.1-cuda11.8-cudnn9-devel
docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:2.4.1-cuda11.8-cudnn9-devel  docker.io/pytorch/pytorch:2.4.1-cuda11.8-cudnn9-devel

Containerd拉取命令

ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:2.4.1-cuda11.8-cudnn9-devel
ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:2.4.1-cuda11.8-cudnn9-devel  docker.io/pytorch/pytorch:2.4.1-cuda11.8-cudnn9-devel

Shell快速替换命令

sed -i 's#pytorch/pytorch:2.4.1-cuda11.8-cudnn9-devel#swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:2.4.1-cuda11.8-cudnn9-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:2.4.1-cuda11.8-cudnn9-devel && docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:2.4.1-cuda11.8-cudnn9-devel  docker.io/pytorch/pytorch:2.4.1-cuda11.8-cudnn9-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:2.4.1-cuda11.8-cudnn9-devel && ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:2.4.1-cuda11.8-cudnn9-devel  docker.io/pytorch/pytorch:2.4.1-cuda11.8-cudnn9-devel'

镜像历史

大小 创建时间 层信息
0.00B 2024-09-05 03:56:42 WORKDIR /workspace
0.00B 2024-09-05 03:56:42 ENV PYTORCH_VERSION=2.4.1
0.00B 2024-09-05 03:56:42 ENV PATH=/usr/local/nvidia/bin:/usr/local/cuda/bin:/opt/conda/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
0.00B 2024-09-05 03:56:42 ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64
0.00B 2024-09-05 03:56:42 ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
0.00B 2024-09-05 03:56:42 ENV NVIDIA_VISIBLE_DEVICES=all
0.00B 2024-09-05 03:56:42 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
0.00B 2024-09-05 03:56:42 RUN |4 PYTORCH_VERSION=2.4.1 TRITON_VERSION= TARGETPLATFORM=linux/amd64 CUDA_VERSION=11.8.0 /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
6.25GB 2024-09-05 03:56:41 COPY /opt/conda /opt/conda # buildkit
3.31MB 2024-09-05 03:52:49 RUN |4 PYTORCH_VERSION=2.4.1 TRITON_VERSION= TARGETPLATFORM=linux/amd64 CUDA_VERSION=11.8.0 /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
0.00B 2024-09-05 03:52:49 LABEL com.nvidia.volumes.needed=nvidia_driver
0.00B 2024-09-05 03:52:49 ARG CUDA_VERSION=11.8.0
0.00B 2024-09-05 03:52:49 ARG TARGETPLATFORM=linux/amd64
0.00B 2024-09-05 03:52:49 ARG TRITON_VERSION=
0.00B 2024-09-05 03:52:49 ARG PYTORCH_VERSION=2.4.1
0.00B 2023-11-10 14:55:21 ENV LIBRARY_PATH=/usr/local/cuda/lib64/stubs
383.52KB 2023-11-10 14:55:21 RUN |1 TARGETARCH=amd64 /bin/sh -c apt-mark hold ${NV_LIBCUBLAS_DEV_PACKAGE_NAME} ${NV_LIBNCCL_DEV_PACKAGE_NAME} # buildkit
4.72GB 2023-11-10 14:55:17 RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends cuda-cudart-dev-11-8=${NV_CUDA_CUDART_DEV_VERSION} cuda-command-line-tools-11-8=${NV_CUDA_LIB_VERSION} cuda-minimal-build-11-8=${NV_CUDA_LIB_VERSION} cuda-libraries-dev-11-8=${NV_CUDA_LIB_VERSION} cuda-nvml-dev-11-8=${NV_NVML_DEV_VERSION} ${NV_NVPROF_DEV_PACKAGE} ${NV_LIBNPP_DEV_PACKAGE} libcusparse-dev-11-8=${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
0.00B 2023-11-10 14:55:17 LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
0.00B 2023-11-10 14:55:17 ARG TARGETARCH
0.00B 2023-11-10 14:55:17 ENV NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.15.5-1+cuda11.8
0.00B 2023-11-10 14:55:17 ENV NCCL_VERSION=2.15.5-1
0.00B 2023-11-10 14:55:17 ENV NV_LIBNCCL_DEV_PACKAGE_VERSION=2.15.5-1
0.00B 2023-11-10 14:55:17 ENV NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev
0.00B 2023-11-10 14:55:17 ENV NV_NVPROF_DEV_PACKAGE=cuda-nvprof-11-8=11.8.87-1
0.00B 2023-11-10 14:55:17 ENV NV_NVPROF_VERSION=11.8.87-1
0.00B 2023-11-10 14:55:17 ENV NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE=cuda-nsight-compute-11-8=11.8.0-1
0.00B 2023-11-10 14:55:17 ENV NV_CUDA_NSIGHT_COMPUTE_VERSION=11.8.0-1
0.00B 2023-11-10 14:55:17 ENV NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-11-8=11.11.3.6-1
0.00B 2023-11-10 14:55:17 ENV NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-11-8
0.00B 2023-11-10 14:55:17 ENV NV_LIBCUBLAS_DEV_VERSION=11.11.3.6-1
0.00B 2023-11-10 14:55:17 ENV NV_LIBNPP_DEV_PACKAGE=libnpp-dev-11-8=11.8.0.86-1
0.00B 2023-11-10 14:55:17 ENV NV_LIBNPP_DEV_VERSION=11.8.0.86-1
0.00B 2023-11-10 14:55:17 ENV NV_LIBCUSPARSE_DEV_VERSION=11.7.5.86-1
0.00B 2023-11-10 14:55:17 ENV NV_NVML_DEV_VERSION=11.8.86-1
0.00B 2023-11-10 14:55:17 ENV NV_CUDA_CUDART_DEV_VERSION=11.8.89-1
0.00B 2023-11-10 14:55:17 ENV NV_CUDA_LIB_VERSION=11.8.0-1
0.00B 2023-11-10 14:42:37 ENTRYPOINT ["/opt/nvidia/nvidia_entrypoint.sh"]
0.00B 2023-11-10 14:42:37 ENV NVIDIA_PRODUCT_NAME=CUDA
2.53KB 2023-11-10 14:42:37 COPY nvidia_entrypoint.sh /opt/nvidia/ # buildkit
3.06KB 2023-11-10 14:42:37 COPY entrypoint.d/ /opt/nvidia/entrypoint.d/ # buildkit
260.16KB 2023-11-10 14:42:37 RUN |1 TARGETARCH=amd64 /bin/sh -c apt-mark hold ${NV_LIBCUBLAS_PACKAGE_NAME} ${NV_LIBNCCL_PACKAGE_NAME} # buildkit
2.41GB 2023-11-10 14:42:36 RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends cuda-libraries-11-8=${NV_CUDA_LIB_VERSION} ${NV_LIBNPP_PACKAGE} cuda-nvtx-11-8=${NV_NVTX_VERSION} libcusparse-11-8=${NV_LIBCUSPARSE_VERSION} ${NV_LIBCUBLAS_PACKAGE} ${NV_LIBNCCL_PACKAGE} && rm -rf /var/lib/apt/lists/* # buildkit
0.00B 2023-11-10 14:42:36 LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
0.00B 2023-11-10 14:42:36 ARG TARGETARCH
0.00B 2023-11-10 14:42:36 ENV NV_LIBNCCL_PACKAGE=libnccl2=2.15.5-1+cuda11.8
0.00B 2023-11-10 14:42:36 ENV NCCL_VERSION=2.15.5-1
0.00B 2023-11-10 14:42:36 ENV NV_LIBNCCL_PACKAGE_VERSION=2.15.5-1
0.00B 2023-11-10 14:42:36 ENV NV_LIBNCCL_PACKAGE_NAME=libnccl2
0.00B 2023-11-10 14:42:36 ENV NV_LIBCUBLAS_PACKAGE=libcublas-11-8=11.11.3.6-1
0.00B 2023-11-10 14:42:36 ENV NV_LIBCUBLAS_VERSION=11.11.3.6-1
0.00B 2023-11-10 14:42:36 ENV NV_LIBCUBLAS_PACKAGE_NAME=libcublas-11-8
0.00B 2023-11-10 14:42:36 ENV NV_LIBCUSPARSE_VERSION=11.7.5.86-1
0.00B 2023-11-10 14:42:36 ENV NV_LIBNPP_PACKAGE=libnpp-11-8=11.8.0.86-1
0.00B 2023-11-10 14:42:36 ENV NV_LIBNPP_VERSION=11.8.0.86-1
0.00B 2023-11-10 14:42:36 ENV NV_NVTX_VERSION=11.8.86-1
0.00B 2023-11-10 14:42:36 ENV NV_CUDA_LIB_VERSION=11.8.0-1
0.00B 2023-11-10 14:37:16 ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
0.00B 2023-11-10 14:37:16 ENV NVIDIA_VISIBLE_DEVICES=all
17.29KB 2023-11-10 14:37:16 COPY NGC-DL-CONTAINER-LICENSE / # buildkit
0.00B 2023-11-10 14:37:16 ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64
0.00B 2023-11-10 14:37:16 ENV PATH=/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
46.00B 2023-11-10 14:37:16 RUN |1 TARGETARCH=amd64 /bin/sh -c echo "/usr/local/nvidia/lib" >> /etc/ld.so.conf.d/nvidia.conf && echo "/usr/local/nvidia/lib64" >> /etc/ld.so.conf.d/nvidia.conf # buildkit
150.67MB 2023-11-10 14:37:16 RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends cuda-cudart-11-8=${NV_CUDA_CUDART_VERSION} ${NV_CUDA_COMPAT_PACKAGE} && rm -rf /var/lib/apt/lists/* # buildkit
0.00B 2023-11-10 14:37:01 ENV CUDA_VERSION=11.8.0
10.56MB 2023-11-10 14:37:01 RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends gnupg2 curl ca-certificates && curl -fsSLO https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/${NVARCH}/cuda-keyring_1.0-1_all.deb && dpkg -i cuda-keyring_1.0-1_all.deb && apt-get purge --autoremove -y curl && rm -rf /var/lib/apt/lists/* # buildkit
0.00B 2023-11-10 14:37:01 LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
0.00B 2023-11-10 14:37:01 ARG TARGETARCH
0.00B 2023-11-10 14:37:01 ENV NV_CUDA_COMPAT_PACKAGE=cuda-compat-11-8
0.00B 2023-11-10 14:37:01 ENV NV_CUDA_CUDART_VERSION=11.8.89-1
0.00B 2023-11-10 14:37:01 ENV NVIDIA_REQUIRE_CUDA=cuda>=11.8 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 2023-11-10 14:37:01 ENV NVARCH=x86_64
0.00B 2023-10-05 15:33:32 /bin/sh -c #(nop) CMD ["/bin/bash"]
77.82MB 2023-10-05 15:33:32 /bin/sh -c #(nop) ADD file:63d5ab3ef0aab308c0e71cb67292c5467f60deafa9b0418cbb220affcd078444 in /
0.00B 2023-10-05 15:33:30 /bin/sh -c #(nop) LABEL org.opencontainers.image.version=22.04
0.00B 2023-10-05 15:33:30 /bin/sh -c #(nop) LABEL org.opencontainers.image.ref.name=ubuntu
0.00B 2023-10-05 15:33:30 /bin/sh -c #(nop) ARG LAUNCHPAD_BUILD_ARCH
0.00B 2023-10-05 15:33:30 /bin/sh -c #(nop) ARG RELEASE

镜像信息

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            "PATH=/usr/local/nvidia/bin:/usr/local/cuda/bin:/opt/conda/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin",
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            "NVIDIA_VISIBLE_DEVICES=all",
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            "NV_LIBNPP_VERSION=11.8.0.86-1",
            "NV_LIBNPP_PACKAGE=libnpp-11-8=11.8.0.86-1",
            "NV_LIBCUSPARSE_VERSION=11.7.5.86-1",
            "NV_LIBCUBLAS_PACKAGE_NAME=libcublas-11-8",
            "NV_LIBCUBLAS_VERSION=11.11.3.6-1",
            "NV_LIBCUBLAS_PACKAGE=libcublas-11-8=11.11.3.6-1",
            "NV_LIBNCCL_PACKAGE_NAME=libnccl2",
            "NV_LIBNCCL_PACKAGE_VERSION=2.15.5-1",
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            "NV_LIBNCCL_PACKAGE=libnccl2=2.15.5-1+cuda11.8",
            "NVIDIA_PRODUCT_NAME=CUDA",
            "NV_CUDA_CUDART_DEV_VERSION=11.8.89-1",
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            "NV_LIBCUSPARSE_DEV_VERSION=11.7.5.86-1",
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            "NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-11-8=11.11.3.6-1",
            "NV_CUDA_NSIGHT_COMPUTE_VERSION=11.8.0-1",
            "NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE=cuda-nsight-compute-11-8=11.8.0-1",
            "NV_NVPROF_VERSION=11.8.87-1",
            "NV_NVPROF_DEV_PACKAGE=cuda-nvprof-11-8=11.8.87-1",
            "NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev",
            "NV_LIBNCCL_DEV_PACKAGE_VERSION=2.15.5-1",
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}

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