docker.io/pytorch/pytorch:1.11.0-cuda11.3-cudnn8-devel linux/amd64

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:1.11.0-cuda11.3-cudnn8-devel
docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:1.11.0-cuda11.3-cudnn8-devel  docker.io/pytorch/pytorch:1.11.0-cuda11.3-cudnn8-devel

Containerd拉取命令

ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:1.11.0-cuda11.3-cudnn8-devel
ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:1.11.0-cuda11.3-cudnn8-devel  docker.io/pytorch/pytorch:1.11.0-cuda11.3-cudnn8-devel

Shell快速替换命令

sed -i 's#pytorch/pytorch:1.11.0-cuda11.3-cudnn8-devel#swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:1.11.0-cuda11.3-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:1.11.0-cuda11.3-cudnn8-devel && docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:1.11.0-cuda11.3-cudnn8-devel  docker.io/pytorch/pytorch:1.11.0-cuda11.3-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:1.11.0-cuda11.3-cudnn8-devel && ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:1.11.0-cuda11.3-cudnn8-devel  docker.io/pytorch/pytorch:1.11.0-cuda11.3-cudnn8-devel'

镜像构建历史

# 2022-03-11 01:05:02  0.00B 设置工作目录为/workspace
WORKDIR /workspace
                        
# 2022-03-11 01:04:53  0.00B 设置环境变量 PYTORCH_VERSION
ENV PYTORCH_VERSION=v1.11.0
                        
# 2022-03-11 01:04:53  0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64
                        
# 2022-03-11 01:04:53  0.00B 设置环境变量 NVIDIA_DRIVER_CAPABILITIES
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
                        
# 2022-03-11 01:04:53  0.00B 设置环境变量 NVIDIA_VISIBLE_DEVICES
ENV NVIDIA_VISIBLE_DEVICES=all
                        
# 2022-03-11 01:04:53  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
                        
# 2022-03-11 01:04:53  5.72GB 复制新文件或目录到容器中
COPY /opt/conda /opt/conda # buildkit
                        
# 2022-03-11 00:54:18  2.97MB 执行命令并创建新的镜像层
RUN |1 PYTORCH_VERSION=v1.11.0 /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
                        
# 2022-03-11 00:54:18  0.00B 添加元数据标签
LABEL com.nvidia.volumes.needed=nvidia_driver
                        
# 2022-03-11 00:54:18  0.00B 定义构建参数
ARG PYTORCH_VERSION
                        
# 2022-01-07 09:02:18  4.02GB 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
                        
# 2022-01-07 09:02:18  0.00B 添加元数据标签
LABEL com.nvidia.cudnn.version=8.2.0.53
                        
# 2022-01-07 09:02:18  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2022-01-07 09:02:18  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2022-01-07 09:02:18  0.00B 设置环境变量 NV_CUDNN_PACKAGE_NAME
ENV NV_CUDNN_PACKAGE_NAME=libcudnn8
                        
# 2022-01-07 09:02:18  0.00B 设置环境变量 NV_CUDNN_PACKAGE_DEV
ENV NV_CUDNN_PACKAGE_DEV=libcudnn8-dev=8.2.0.53-1+cuda11.3
                        
# 2022-01-07 09:02:18  0.00B 设置环境变量 NV_CUDNN_PACKAGE
ENV NV_CUDNN_PACKAGE=libcudnn8=8.2.0.53-1+cuda11.3
                        
# 2022-01-07 09:02:18  0.00B 设置环境变量 NV_CUDNN_VERSION
ENV NV_CUDNN_VERSION=8.2.0.53
                        
# 2022-01-07 08:40:23  0.00B 设置环境变量 LIBRARY_PATH
ENV LIBRARY_PATH=/usr/local/cuda/lib64/stubs
                        
# 2022-01-07 08:40:23  366.10KB 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
                        
# 2022-01-07 08:40:23  2.21GB 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-dev-11-3=${NV_CUDA_CUDART_DEV_VERSION}     cuda-command-line-tools-11-3=${NV_CUDA_LIB_VERSION}     cuda-minimal-build-11-3=${NV_CUDA_LIB_VERSION}     cuda-libraries-dev-11-3=${NV_CUDA_LIB_VERSION}     cuda-nvml-dev-11-3=${NV_NVML_DEV_VERSION}     ${NV_LIBNPP_DEV_PACKAGE}     libcusparse-dev-11-3=${NV_LIBCUSPARSE_DEV_VERSION}     ${NV_LIBCUBLAS_DEV_PACKAGE}     ${NV_LIBNCCL_DEV_PACKAGE}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2022-01-07 08:40:23  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2022-01-07 08:40:23  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2022-01-07 08:40:23  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE
ENV NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.9.6-1+cuda11.3
                        
# 2022-01-07 08:40:23  0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.9.6-1
                        
# 2022-01-07 08:40:23  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE_VERSION
ENV NV_LIBNCCL_DEV_PACKAGE_VERSION=2.9.6-1
                        
# 2022-01-07 08:40:23  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE_NAME
ENV NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev
                        
# 2022-01-07 08:40:23  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_PACKAGE
ENV NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-11-3=11.4.2.10064-1
                        
# 2022-01-07 08:40:23  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_PACKAGE_NAME
ENV NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-11-3
                        
# 2022-01-07 08:40:23  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_VERSION
ENV NV_LIBCUBLAS_DEV_VERSION=11.4.2.10064-1
                        
# 2022-01-07 08:40:23  0.00B 设置环境变量 NV_LIBNPP_DEV_PACKAGE
ENV NV_LIBNPP_DEV_PACKAGE=libnpp-dev-11-3=11.3.3.44-1
                        
# 2022-01-07 08:40:23  0.00B 设置环境变量 NV_LIBNPP_DEV_VERSION
ENV NV_LIBNPP_DEV_VERSION=11.3.3.44-1
                        
# 2022-01-07 08:40:23  0.00B 设置环境变量 NV_LIBCUSPARSE_DEV_VERSION
ENV NV_LIBCUSPARSE_DEV_VERSION=11.5.0.58-1
                        
# 2022-01-07 08:40:23  0.00B 设置环境变量 NV_NVML_DEV_VERSION
ENV NV_NVML_DEV_VERSION=11.3.58-1
                        
# 2022-01-07 08:40:23  0.00B 设置环境变量 NV_CUDA_CUDART_DEV_VERSION
ENV NV_CUDA_CUDART_DEV_VERSION=11.3.58-1
                        
# 2022-01-07 08:40:23  0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=11.3.0-1
                        
# 2022-01-07 08:32:51  254.37KB 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
                        
# 2022-01-07 08:32:51  1.64GB 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-11-3=${NV_CUDA_LIB_VERSION}     ${NV_LIBNPP_PACKAGE}     cuda-nvtx-11-3=${NV_NVTX_VERSION}     libcusparse-11-3=${NV_LIBCUSPARSE_VERSION}     ${NV_LIBCUBLAS_PACKAGE}     ${NV_LIBNCCL_PACKAGE}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2022-01-07 08:32:51  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2022-01-07 08:32:51  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2022-01-07 08:32:51  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE
ENV NV_LIBNCCL_PACKAGE=libnccl2=2.9.6-1+cuda11.3
                        
# 2022-01-07 08:32:51  0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.9.6-1
                        
# 2022-01-07 08:32:51  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_VERSION
ENV NV_LIBNCCL_PACKAGE_VERSION=2.9.6-1
                        
# 2022-01-07 08:32:51  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_NAME
ENV NV_LIBNCCL_PACKAGE_NAME=libnccl2
                        
# 2022-01-07 08:32:51  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE
ENV NV_LIBCUBLAS_PACKAGE=libcublas-11-3=11.4.2.10064-1
                        
# 2022-01-07 08:32:51  0.00B 设置环境变量 NV_LIBCUBLAS_VERSION
ENV NV_LIBCUBLAS_VERSION=11.4.2.10064-1
                        
# 2022-01-07 08:32:51  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE_NAME
ENV NV_LIBCUBLAS_PACKAGE_NAME=libcublas-11-3
                        
# 2022-01-07 08:32:51  0.00B 设置环境变量 NV_LIBCUSPARSE_VERSION
ENV NV_LIBCUSPARSE_VERSION=11.5.0.58-1
                        
# 2022-01-07 08:32:51  0.00B 设置环境变量 NV_LIBNPP_PACKAGE
ENV NV_LIBNPP_PACKAGE=libnpp-11-3=11.3.3.44-1
                        
# 2022-01-07 08:32:51  0.00B 设置环境变量 NV_LIBNPP_VERSION
ENV NV_LIBNPP_VERSION=11.3.3.44-1
                        
# 2022-01-07 08:32:51  0.00B 设置环境变量 NV_NVTX_VERSION
ENV NV_NVTX_VERSION=11.3.58-1
                        
# 2022-01-07 08:32:51  0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=11.3.0-1
                        
# 2022-01-07 08:28:31  0.00B 设置环境变量 NVIDIA_DRIVER_CAPABILITIES
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
                        
# 2022-01-07 08:28:31  0.00B 设置环境变量 NVIDIA_VISIBLE_DEVICES
ENV NVIDIA_VISIBLE_DEVICES=all
                        
# 2022-01-07 08:28:31  16.05KB 复制新文件或目录到容器中
COPY NGC-DL-CONTAINER-LICENSE / # buildkit
                        
# 2022-01-07 08:28:31  0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64
                        
# 2022-01-07 08:28:31  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
                        
# 2022-01-07 08:28:31  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
                        
# 2022-01-07 08:28:30  34.18MB 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-11-3=${NV_CUDA_CUDART_VERSION}     ${NV_CUDA_COMPAT_PACKAGE}     && ln -s cuda-11.3 /usr/local/cuda &&     rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2022-01-07 08:28:20  0.00B 设置环境变量 CUDA_VERSION
ENV CUDA_VERSION=11.3.0
                        
# 2022-01-07 08:28:20  16.53MB 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/ubuntu1804/${NVARCH}/7fa2af80.pub | apt-key add - &&     echo "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/${NVARCH} /" > /etc/apt/sources.list.d/cuda.list &&     if [ ! -z ${NV_ML_REPO_ENABLED} ]; then echo "deb ${NV_ML_REPO_URL} /" > /etc/apt/sources.list.d/nvidia-ml.list; fi &&     apt-get purge --autoremove -y curl     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2022-01-07 08:28:20  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2022-01-07 08:28:20  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2022-01-07 08:28:20  0.00B 设置环境变量 NV_ML_REPO_URL
ENV NV_ML_REPO_URL=https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64
                        
# 2022-01-07 08:28:20  0.00B 设置环境变量 NV_ML_REPO_ENABLED
ENV NV_ML_REPO_ENABLED=1
                        
# 2022-01-07 08:28:20  0.00B 设置环境变量 NV_CUDA_COMPAT_PACKAGE
ENV NV_CUDA_COMPAT_PACKAGE=cuda-compat-11-3
                        
# 2022-01-07 08:28:20  0.00B 设置环境变量 NV_CUDA_CUDART_VERSION
ENV NV_CUDA_CUDART_VERSION=11.3.58-1
                        
# 2022-01-07 08:28:20  0.00B 设置环境变量 NVIDIA_REQUIRE_CUDA brand brand driver>
ENV NVIDIA_REQUIRE_CUDA=cuda>=11.3 brand=tesla,driver>=418,driver<419 brand=tesla,driver>=440,driver<441 driver>=450
                        
# 2022-01-07 08:28:20  0.00B 设置环境变量 NVARCH
ENV NVARCH=x86_64
                        
# 2021-10-01 10:23:24  0.00B 
/bin/sh -c #(nop)  CMD ["bash"]
                        
# 2021-10-01 10:23:23  63.14MB 
/bin/sh -c #(nop) ADD file:0d82cd095966e8ee78b593cb47a352eec842edb7bd9d9468e8a70154522447d1 in / 
                        
                    

镜像信息

{
    "Id": "sha256:730572d0c0ddf5884066e32294d6fd06d698105c7cb5f4a84a8395cfa71063bf",
    "RepoTags": [
        "pytorch/pytorch:1.11.0-cuda11.3-cudnn8-devel",
        "swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:1.11.0-cuda11.3-cudnn8-devel"
    ],
    "RepoDigests": [
        "pytorch/pytorch@sha256:9bfcfa72b6b244c1fbfa24864eec97fb29cfafc065999e9a9ba913fa1e690a02",
        "swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch@sha256:9bfcfa72b6b244c1fbfa24864eec97fb29cfafc065999e9a9ba913fa1e690a02"
    ],
    "Parent": "",
    "Comment": "buildkit.dockerfile.v0",
    "Created": "2022-03-10T09:05:02.590393656-08:00",
    "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=11.3 brand=tesla,driver\u003e=418,driver\u003c419 brand=tesla,driver\u003e=440,driver\u003c441 driver\u003e=450",
            "NV_CUDA_CUDART_VERSION=11.3.58-1",
            "NV_CUDA_COMPAT_PACKAGE=cuda-compat-11-3",
            "NV_ML_REPO_ENABLED=1",
            "NV_ML_REPO_URL=https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64",
            "CUDA_VERSION=11.3.0",
            "LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64",
            "NVIDIA_VISIBLE_DEVICES=all",
            "NVIDIA_DRIVER_CAPABILITIES=compute,utility",
            "NV_CUDA_LIB_VERSION=11.3.0-1",
            "NV_NVTX_VERSION=11.3.58-1",
            "NV_LIBNPP_VERSION=11.3.3.44-1",
            "NV_LIBNPP_PACKAGE=libnpp-11-3=11.3.3.44-1",
            "NV_LIBCUSPARSE_VERSION=11.5.0.58-1",
            "NV_LIBCUBLAS_PACKAGE_NAME=libcublas-11-3",
            "NV_LIBCUBLAS_VERSION=11.4.2.10064-1",
            "NV_LIBCUBLAS_PACKAGE=libcublas-11-3=11.4.2.10064-1",
            "NV_LIBNCCL_PACKAGE_NAME=libnccl2",
            "NV_LIBNCCL_PACKAGE_VERSION=2.9.6-1",
            "NCCL_VERSION=2.9.6-1",
            "NV_LIBNCCL_PACKAGE=libnccl2=2.9.6-1+cuda11.3",
            "NV_CUDA_CUDART_DEV_VERSION=11.3.58-1",
            "NV_NVML_DEV_VERSION=11.3.58-1",
            "NV_LIBCUSPARSE_DEV_VERSION=11.5.0.58-1",
            "NV_LIBNPP_DEV_VERSION=11.3.3.44-1",
            "NV_LIBNPP_DEV_PACKAGE=libnpp-dev-11-3=11.3.3.44-1",
            "NV_LIBCUBLAS_DEV_VERSION=11.4.2.10064-1",
            "NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-11-3",
            "NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-11-3=11.4.2.10064-1",
            "NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev",
            "NV_LIBNCCL_DEV_PACKAGE_VERSION=2.9.6-1",
            "NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.9.6-1+cuda11.3",
            "LIBRARY_PATH=/usr/local/cuda/lib64/stubs",
            "NV_CUDNN_VERSION=8.2.0.53",
            "NV_CUDNN_PACKAGE=libcudnn8=8.2.0.53-1+cuda11.3",
            "NV_CUDNN_PACKAGE_DEV=libcudnn8-dev=8.2.0.53-1+cuda11.3",
            "NV_CUDNN_PACKAGE_NAME=libcudnn8",
            "PYTORCH_VERSION=v1.11.0"
        ],
        "Cmd": [
            "bash"
        ],
        "Image": "",
        "Volumes": null,
        "WorkingDir": "/workspace",
        "Entrypoint": null,
        "OnBuild": null,
        "Labels": {
            "com.nvidia.cudnn.version": "8.2.0.53",
            "com.nvidia.volumes.needed": "nvidia_driver",
            "maintainer": "NVIDIA CORPORATION \u003ccudatools@nvidia.com\u003e"
        }
    },
    "Architecture": "amd64",
    "Os": "linux",
    "Size": 13710363237,
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