docker.io/chiefcontainer/chief:v1.11 linux/amd64

docker.io/chiefcontainer/chief:v1.11 - 国内下载镜像源 浏览次数:12

该Docker镜像 docker.io/chiefcontainer/chief 是由Chief Container提供的。 具体的描述信息需要参考镜像的官方文档或其维护者的说明，因为我没有访问外部资源的能力，无法获取该镜像的详细信息。

源镜像 docker.io/chiefcontainer/chief:v1.11
国内镜像 swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/chiefcontainer/chief:v1.11
镜像ID sha256:afdd2a3c95c83dfaf6a0dda6496f0432ef443c65892e14711fbe23d5f0524717
镜像TAG v1.11
大小 65.65GB
镜像源 docker.io
项目信息 Docker-Hub主页 🚀项目TAG 🚀
CMD /bin/sh -c sleep infinity
启动入口
工作目录
OS/平台 linux/amd64
浏览量 12 次
贡献者
镜像创建 2024-09-21T07:00:57.576196709Z
同步时间 2025-05-30 07:24
更新时间 2025-05-31 13:50
开放端口
10201/tcp 10202/tcp 10203/tcp 10204/tcp 10205/tcp 10206/tcp 10207/tcp 10208/tcp 10220/tcp 10221/tcp 10222/tcp 10223/tcp 10316/tcp 10335/tcp 10443/tcp 10987/tcp 11164/tcp 11696/tcp 12052/tcp 12833/tcp 13062/tcp 15225/tcp 15244/tcp 15405/tcp 15576/tcp 15717/tcp 15802/tcp 16180/tcp 16187/tcp 16549/tcp 17068/tcp 17625/tcp 17702/tcp 18015/tcp 18061/tcp 18415/tcp 18452/tcp 18644/tcp 19225/tcp 19352/tcp 19501/tcp 22/tcp
环境变量
VNC_PORT=16180 VSCODE_PORT=18061 JUPYTER_PORT=10335 VNC_PASSWD=QAZwsx123 VSCODE_PASSWD=QAZwsx123 JUPYTER_PASSWD=QAZwsx123 RDMA= TENSORBOARD_PORT=17625 TENSORBOARD_PATH=/root/Tensorboard PATH=/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>=11.4 brand=tesla,driver>=418,driver<419 brand=tesla,driver>=440,driver<441 driver>=450 NV_CUDA_CUDART_VERSION=11.4.108-1 NV_CUDA_COMPAT_PACKAGE=cuda-compat-11-4 CUDA_VERSION=11.4.1 LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64 NVIDIA_VISIBLE_DEVICES=all NVIDIA_DRIVER_CAPABILITIES=compute,utility NV_CUDA_LIB_VERSION=11.4.1-1 NV_NVTX_VERSION=11.4.100-1 NV_LIBNPP_VERSION=11.4.0.90-1 NV_LIBCUSPARSE_VERSION=11.6.0.100-1 NV_LIBCUBLAS_PACKAGE_NAME=libcublas-11-4 NV_LIBCUBLAS_VERSION=11.5.4.8-1 NV_LIBCUBLAS_PACKAGE=libcublas-11-4=11.5.4.8-1 NV_LIBNCCL_PACKAGE_NAME=libnccl2 NV_LIBNCCL_PACKAGE_VERSION=2.10.3-1 NCCL_VERSION=2.10.3-1 NV_LIBNCCL_PACKAGE=libnccl2=2.10.3-1+cuda11.4 NV_CUDA_CUDART_DEV_VERSION=11.4.108-1 NV_NVML_DEV_VERSION=11.4.43-1 NV_LIBCUSPARSE_DEV_VERSION=11.6.0.100-1 NV_LIBNPP_DEV_VERSION=11.4.0.90-1 NV_LIBCUBLAS_DEV_VERSION=11.5.4.8-1 NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-11-4 NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-11-4=11.5.4.8-1 NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev NV_LIBNCCL_DEV_PACKAGE_VERSION=2.10.3-1 NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.10.3-1+cuda11.4 LIBRARY_PATH=/usr/local/cuda/lib64/stubs NV_CUDNN_VERSION=8.2.2.26 NV_CUDNN_PACKAGE=libcudnn8=8.2.2.26-1+cuda11.4 NV_CUDNN_PACKAGE_DEV=libcudnn8-dev=8.2.2.26-1+cuda11.4 NV_CUDNN_PACKAGE_NAME=libcudnn8
镜像标签
8.2.2.26: com.nvidia.cudnn.version NVIDIA CORPORATION <cudatools@nvidia.com>: maintainer
无权限下载?点我修复 生成Docker Run命令

Docker拉取命令 

docker pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/chiefcontainer/chief:v1.11
docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/chiefcontainer/chief:v1.11  docker.io/chiefcontainer/chief:v1.11

Containerd拉取命令 

ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/chiefcontainer/chief:v1.11
ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/chiefcontainer/chief:v1.11  docker.io/chiefcontainer/chief:v1.11

Shell快速替换命令 

sed -i 's#chiefcontainer/chief:v1.11#swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/chiefcontainer/chief:v1.11#' 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/chiefcontainer/chief:v1.11 && docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/chiefcontainer/chief:v1.11  docker.io/chiefcontainer/chief:v1.11'

Ansible快速分发-Containerd 

#ansible k8s -m shell -a 'ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/chiefcontainer/chief:v1.11 && ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/chiefcontainer/chief:v1.11  docker.io/chiefcontainer/chief:v1.11'

镜像构建历史 


# 2024-09-21 15:00:57  236.32KB 
/bin/sh -c sleep infinity
                        
# 2024-09-21 14:00:58  234.50KB 
/bin/sh -c sleep infinity
                        
# 2024-09-21 13:55:15  253.28KB 
/bin/sh -c sleep infinity
                        
# 2024-04-13 08:13:41  40.02GB 
/bin/sh -c bash /root/scm.sh && sleep infinity
                        
# 2024-03-16 12:04:36  684.71MB 
/bin/sh -c bash /root/scm.sh && sleep infinity
                        
# 2023-11-03 16:48:40  824.73MB 
/bin/sh -c bash /root/scm.sh && sleep infinity
                        
# 2023-09-21 18:44:13  422.17MB 
/bin/sh -c bash /root/scm.sh && sleep infinity
                        
# 2023-08-12 14:08:42  200.04MB 
/bin/sh -c bash /root/scm.sh && sleep infinity
                        
# 2023-08-08 10:36:30  110.76MB 
/bin/sh -c bash /root/scm.sh && sleep infinity
                        
# 2023-08-03 16:16:08  321.03MB 
/bin/sh -c bash /root/scm.sh && sleep infinity
                        
# 2023-08-03 12:43:38  173.29MB 
/bin/sh -c bash /root/scm.sh && sleep infinity
                        
# 2023-08-01 12:51:27  1.82GB 
/bin/sh -c bash /root/scm.sh && sleep infinity
                        
# 2022-05-05 14:46:43  7.63GB 
/bin/sh -c cd /root/ && bash scm.sh  && sleep infinity
                        
# 2022-05-03 17:29:18  47.56MB 
/bin/sh -c cd /root/  && nvidia-smi && python3 tf2-mnist-tb.py && python3 tf2-mnist.py && sleep infinity
                        
# 2022-05-03 17:08:43  283.48MB 
/bin/sh -c cd /root/ && bash scm.sh && nvidia-smi && python3 tf2-mnist-tb.py && python3 tf2-mnist.py && sleep infinity
                        
# 2022-05-03 16:49:18  1.38GB 
/bin/sh -c cd /root/ && bash scm.sh && nvidia-smi && python3 tf2-mnist-tb.py && python3 tf2-mnist.py && sleep infinity
                        
# 2022-05-03 16:09:41  193.34KB 
/bin/sh -c cd /root/ && bash scm.sh && nvidia-smi && python3 tf2-mnist-tb.py && python3 tf2-mnist.py && sleep infinity
                        
# 2022-05-02 11:21:19  2.89GB 
/bin/sh -c sleep infinity
                        
# 2021-08-04 05:02:33  3.78GB 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
                        
# 2021-08-04 05:02:33  0.00B 添加元数据标签
LABEL com.nvidia.cudnn.version=8.2.2.26
                        
# 2021-08-04 05:02:33  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2021-08-04 05:02:33  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2021-08-04 05:02:33  0.00B 设置环境变量 NV_CUDNN_PACKAGE_NAME
ENV NV_CUDNN_PACKAGE_NAME=libcudnn8
                        
# 2021-08-04 05:02:33  0.00B 设置环境变量 NV_CUDNN_PACKAGE_DEV
ENV NV_CUDNN_PACKAGE_DEV=libcudnn8-dev=8.2.2.26-1+cuda11.4
                        
# 2021-08-04 05:02:33  0.00B 设置环境变量 NV_CUDNN_PACKAGE
ENV NV_CUDNN_PACKAGE=libcudnn8=8.2.2.26-1+cuda11.4
                        
# 2021-08-04 05:02:33  0.00B 设置环境变量 NV_CUDNN_VERSION
ENV NV_CUDNN_VERSION=8.2.2.26
                        
# 2021-08-04 04:59:50  0.00B 设置环境变量 LIBRARY_PATH
ENV LIBRARY_PATH=/usr/local/cuda/lib64/stubs
                        
# 2021-08-04 04:59:50  376.17KB 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
                        
# 2021-08-04 04:59:50  2.92GB 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-11-4=${NV_CUDA_CUDART_DEV_VERSION}     cuda-command-line-tools-11-4=${NV_CUDA_LIB_VERSION}     cuda-minimal-build-11-4=${NV_CUDA_LIB_VERSION}     cuda-libraries-dev-11-4=${NV_CUDA_LIB_VERSION}     cuda-nvml-dev-11-4=${NV_NVML_DEV_VERSION}     libnpp-dev-11-4=${NV_LIBNPP_DEV_VERSION}     libcusparse-dev-11-4=${NV_LIBCUSPARSE_DEV_VERSION}     ${NV_LIBCUBLAS_DEV_PACKAGE}     ${NV_LIBNCCL_DEV_PACKAGE}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2021-08-04 04:59:50  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2021-08-04 04:59:50  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2021-08-04 04:59:50  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE
ENV NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.10.3-1+cuda11.4
                        
# 2021-08-04 04:59:50  0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.10.3-1
                        
# 2021-08-04 04:59:50  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE_VERSION
ENV NV_LIBNCCL_DEV_PACKAGE_VERSION=2.10.3-1
                        
# 2021-08-04 04:59:50  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE_NAME
ENV NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev
                        
# 2021-08-04 04:59:50  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_PACKAGE
ENV NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-11-4=11.5.4.8-1
                        
# 2021-08-04 04:59:50  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_PACKAGE_NAME
ENV NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-11-4
                        
# 2021-08-04 04:59:50  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_VERSION
ENV NV_LIBCUBLAS_DEV_VERSION=11.5.4.8-1
                        
# 2021-08-04 04:59:50  0.00B 设置环境变量 NV_LIBNPP_DEV_VERSION
ENV NV_LIBNPP_DEV_VERSION=11.4.0.90-1
                        
# 2021-08-04 04:59:50  0.00B 设置环境变量 NV_LIBCUSPARSE_DEV_VERSION
ENV NV_LIBCUSPARSE_DEV_VERSION=11.6.0.100-1
                        
# 2021-08-04 04:59:50  0.00B 设置环境变量 NV_NVML_DEV_VERSION
ENV NV_NVML_DEV_VERSION=11.4.43-1
                        
# 2021-08-04 04:59:50  0.00B 设置环境变量 NV_CUDA_CUDART_DEV_VERSION
ENV NV_CUDA_CUDART_DEV_VERSION=11.4.108-1
                        
# 2021-08-04 04:59:50  0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=11.4.1-1
                        
# 2021-08-04 04:53:23  259.78KB 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
                        
# 2021-08-04 04:53:23  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-11-4=${NV_CUDA_LIB_VERSION}     libnpp-11-4=${NV_LIBNPP_VERSION}     cuda-nvtx-11-4=${NV_NVTX_VERSION}     libcusparse-11-4=${NV_LIBCUSPARSE_VERSION}     ${NV_LIBCUBLAS_PACKAGE}     ${NV_LIBNCCL_PACKAGE}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2021-08-04 04:53:23  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2021-08-04 04:53:23  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2021-08-04 04:53:23  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE
ENV NV_LIBNCCL_PACKAGE=libnccl2=2.10.3-1+cuda11.4
                        
# 2021-08-04 04:53:23  0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.10.3-1
                        
# 2021-08-04 04:53:23  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_VERSION
ENV NV_LIBNCCL_PACKAGE_VERSION=2.10.3-1
                        
# 2021-08-04 04:53:23  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_NAME
ENV NV_LIBNCCL_PACKAGE_NAME=libnccl2
                        
# 2021-08-04 04:53:23  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE
ENV NV_LIBCUBLAS_PACKAGE=libcublas-11-4=11.5.4.8-1
                        
# 2021-08-04 04:53:23  0.00B 设置环境变量 NV_LIBCUBLAS_VERSION
ENV NV_LIBCUBLAS_VERSION=11.5.4.8-1
                        
# 2021-08-04 04:53:23  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE_NAME
ENV NV_LIBCUBLAS_PACKAGE_NAME=libcublas-11-4
                        
# 2021-08-04 04:53:23  0.00B 设置环境变量 NV_LIBCUSPARSE_VERSION
ENV NV_LIBCUSPARSE_VERSION=11.6.0.100-1
                        
# 2021-08-04 04:53:23  0.00B 设置环境变量 NV_LIBNPP_VERSION
ENV NV_LIBNPP_VERSION=11.4.0.90-1
                        
# 2021-08-04 04:53:23  0.00B 设置环境变量 NV_NVTX_VERSION
ENV NV_NVTX_VERSION=11.4.100-1
                        
# 2021-08-04 04:53:23  0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=11.4.1-1
                        
# 2021-08-04 04:53:23  0.00B 设置环境变量 NVIDIA_DRIVER_CAPABILITIES
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
                        
# 2021-08-04 04:53:23  0.00B 设置环境变量 NVIDIA_VISIBLE_DEVICES
ENV NVIDIA_VISIBLE_DEVICES=all
                        
# 2021-08-04 04:53:23  16.05KB 复制新文件或目录到容器中
COPY NGC-DL-CONTAINER-LICENSE / # buildkit
                        
# 2021-08-04 04:53:23  0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64
                        
# 2021-08-04 04:53:23  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
                        
# 2021-08-04 04:53:23  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
                        
# 2021-08-04 04:53:23  34.86MB 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-11-4=${NV_CUDA_CUDART_VERSION}     ${NV_CUDA_COMPAT_PACKAGE}     && ln -s cuda-11.4 /usr/local/cuda &&     rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2021-08-04 04:53:23  0.00B 设置环境变量 CUDA_VERSION
ENV CUDA_VERSION=11.4.1
                        
# 2021-08-04 04:53:23  18.28MB 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/${NVARCH}/7fa2af80.pub | apt-key add - &&     echo "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/${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
                        
# 2021-08-04 04:53:23  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2021-08-04 04:53:23  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2021-08-04 04:53:23  0.00B 设置环境变量 NV_CUDA_COMPAT_PACKAGE
ENV NV_CUDA_COMPAT_PACKAGE=cuda-compat-11-4
                        
# 2021-08-04 04:53:23  0.00B 设置环境变量 NV_CUDA_CUDART_VERSION
ENV NV_CUDA_CUDART_VERSION=11.4.108-1
                        
# 2021-08-04 04:53:23  0.00B 设置环境变量 NVIDIA_REQUIRE_CUDA brand brand driver>
ENV NVIDIA_REQUIRE_CUDA=cuda>=11.4 brand=tesla,driver>=418,driver<419 brand=tesla,driver>=440,driver<441 driver>=450
                        
# 2021-08-04 04:53:23  0.00B 设置环境变量 NVARCH
ENV NVARCH=x86_64
                        
# 2021-07-27 05:21:40  0.00B 
/bin/sh -c #(nop)  CMD ["bash"]
                        
# 2021-07-27 05:21:39  72.78MB 
/bin/sh -c #(nop) ADD file:524e8d93ad65f08a0cb0d144268350186e36f508006b05b8faf2e1289499b59f in /

镜像信息 

{
    "Id": "sha256:afdd2a3c95c83dfaf6a0dda6496f0432ef443c65892e14711fbe23d5f0524717",
    "RepoTags": [
        "chiefcontainer/chief:v1.11",
        "swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/chiefcontainer/chief:v1.11"
    ],
    "RepoDigests": [
        "chiefcontainer/chief@sha256:4b4e559b9d3303ecc5720c25a3d9c52422759293830eae0da80d49b2f721f5f7",
        "swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/chiefcontainer/chief@sha256:4b4e559b9d3303ecc5720c25a3d9c52422759293830eae0da80d49b2f721f5f7"
    ],
    "Parent": "",
    "Comment": "",
    "Created": "2024-09-21T07:00:57.576196709Z",
    "Container": "",
    "ContainerConfig": null,
    "DockerVersion": "24.0.2",
    "Author": "",
    "Config": {
        "Hostname": "",
        "Domainname": "",
        "User": "",
        "AttachStdin": false,
        "AttachStdout": false,
        "AttachStderr": false,
        "ExposedPorts": {
            "10201/tcp": {},
            "10202/tcp": {},
            "10203/tcp": {},
            "10204/tcp": {},
            "10205/tcp": {},
            "10206/tcp": {},
            "10207/tcp": {},
            "10208/tcp": {},
            "10220/tcp": {},
            "10221/tcp": {},
            "10222/tcp": {},
            "10223/tcp": {},
            "10316/tcp": {},
            "10335/tcp": {},
            "10443/tcp": {},
            "10987/tcp": {},
            "11164/tcp": {},
            "11696/tcp": {},
            "12052/tcp": {},
            "12833/tcp": {},
            "13062/tcp": {},
            "15225/tcp": {},
            "15244/tcp": {},
            "15405/tcp": {},
            "15576/tcp": {},
            "15717/tcp": {},
            "15802/tcp": {},
            "16180/tcp": {},
            "16187/tcp": {},
            "16549/tcp": {},
            "17068/tcp": {},
            "17625/tcp": {},
            "17702/tcp": {},
            "18015/tcp": {},
            "18061/tcp": {},
            "18415/tcp": {},
            "18452/tcp": {},
            "18644/tcp": {},
            "19225/tcp": {},
            "19352/tcp": {},
            "19501/tcp": {},
            "22/tcp": {}
        },
        "Tty": false,
        "OpenStdin": false,
        "StdinOnce": false,
        "Env": [
            "VNC_PORT=16180",
            "VSCODE_PORT=18061",
            "JUPYTER_PORT=10335",
            "VNC_PASSWD=QAZwsx123",
            "VSCODE_PASSWD=QAZwsx123",
            "JUPYTER_PASSWD=QAZwsx123",
            "RDMA=",
            "TENSORBOARD_PORT=17625",
            "TENSORBOARD_PATH=/root/Tensorboard",
            "PATH=/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=11.4 brand=tesla,driver\u003e=418,driver\u003c419 brand=tesla,driver\u003e=440,driver\u003c441 driver\u003e=450",
            "NV_CUDA_CUDART_VERSION=11.4.108-1",
            "NV_CUDA_COMPAT_PACKAGE=cuda-compat-11-4",
            "CUDA_VERSION=11.4.1",
            "LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64",
            "NVIDIA_VISIBLE_DEVICES=all",
            "NVIDIA_DRIVER_CAPABILITIES=compute,utility",
            "NV_CUDA_LIB_VERSION=11.4.1-1",
            "NV_NVTX_VERSION=11.4.100-1",
            "NV_LIBNPP_VERSION=11.4.0.90-1",
            "NV_LIBCUSPARSE_VERSION=11.6.0.100-1",
            "NV_LIBCUBLAS_PACKAGE_NAME=libcublas-11-4",
            "NV_LIBCUBLAS_VERSION=11.5.4.8-1",
            "NV_LIBCUBLAS_PACKAGE=libcublas-11-4=11.5.4.8-1",
            "NV_LIBNCCL_PACKAGE_NAME=libnccl2",
            "NV_LIBNCCL_PACKAGE_VERSION=2.10.3-1",
            "NCCL_VERSION=2.10.3-1",
            "NV_LIBNCCL_PACKAGE=libnccl2=2.10.3-1+cuda11.4",
            "NV_CUDA_CUDART_DEV_VERSION=11.4.108-1",
            "NV_NVML_DEV_VERSION=11.4.43-1",
            "NV_LIBCUSPARSE_DEV_VERSION=11.6.0.100-1",
            "NV_LIBNPP_DEV_VERSION=11.4.0.90-1",
            "NV_LIBCUBLAS_DEV_VERSION=11.5.4.8-1",
            "NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-11-4",
            "NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-11-4=11.5.4.8-1",
            "NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev",
            "NV_LIBNCCL_DEV_PACKAGE_VERSION=2.10.3-1",
            "NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.10.3-1+cuda11.4",
            "LIBRARY_PATH=/usr/local/cuda/lib64/stubs",
            "NV_CUDNN_VERSION=8.2.2.26",
            "NV_CUDNN_PACKAGE=libcudnn8=8.2.2.26-1+cuda11.4",
            "NV_CUDNN_PACKAGE_DEV=libcudnn8-dev=8.2.2.26-1+cuda11.4",
            "NV_CUDNN_PACKAGE_NAME=libcudnn8"
        ],
        "Cmd": [
            "/bin/sh",
            "-c",
            "sleep infinity"
        ],
        "Image": "",
        "Volumes": null,
        "WorkingDir": "",
        "Entrypoint": null,
        "OnBuild": null,
        "Labels": {
            "com.nvidia.cudnn.version": "8.2.2.26",
            "maintainer": "NVIDIA CORPORATION \u003ccudatools@nvidia.com\u003e"
        }
    },
    "Architecture": "amd64",
    "Os": "linux",
    "Size": 65652963617,
    "GraphDriver": {
        "Data": {
            "LowerDir": "/var/lib/docker/overlay2/fd7b4a3167e56a65787e982f4708c65d2faa95b9d2e13d69befad624224cd1f6/diff:/var/lib/docker/overlay2/c2a8a9339a9eaa4ed615a25ef6c9223ea46f8e6860e09afc8d0fd409b84d6487/diff:/var/lib/docker/overlay2/a86459d80b87cf4de2189a132f5e110ae702e7dd6da23ae58c9dfc6760a686e5/diff:/var/lib/docker/overlay2/843102dcce5d7b94d891396c528071898841b9f6c3ebeb6c2c618c5c5702e14b/diff:/var/lib/docker/overlay2/ad1b370d82c777c6550ee784e3fb12070de6c160512dd6f679f5d5aea2c312be/diff:/var/lib/docker/overlay2/57c2997b3b218cef07bd537befa59f738909fe65393fab3b1e74802968de011b/diff:/var/lib/docker/overlay2/436dc70326f4cfb5fa23e12242cdeb88f49b1d9009c664d6f683cac737e9dc17/diff:/var/lib/docker/overlay2/cddfde31d57fb6231f4d60197ea30673f1628d2ea161488a331d8bce5bf0202d/diff:/var/lib/docker/overlay2/7844728e745d87e4d426acee984e5766fddbc7dce46dd1001b7d8cf3e8cf5224/diff:/var/lib/docker/overlay2/fd27595b54335eb1b9ecc05ef7ca614d1f8f640eab8799b20887f2afb5f5d793/diff:/var/lib/docker/overlay2/3c1841c72f6d08eacda463263cf53b43439f2557377106d905029044624ad1b4/diff:/var/lib/docker/overlay2/f3c11c37895a2132d72b35c7907f26127c4f2bc9126ac401c56edd3bd8f6dcdb/diff:/var/lib/docker/overlay2/ff640a9bfad8bb684ff9d83231d5db984f43c19bbc63b0d6b7b7b89b2c5405a7/diff:/var/lib/docker/overlay2/3fae9699885c3fb65f23f519af12282c4ec1941bd38d5f08d776952217f234f3/diff:/var/lib/docker/overlay2/580a45184e8400e91e1529e0fc6e8ee65c48cee9a7c6141456bf720f7175c784/diff:/var/lib/docker/overlay2/8cf4526031196b9325a8a1d2ad56cb57127e4e18b315e671b3c72af0e17e6090/diff:/var/lib/docker/overlay2/391aafa5bd417f62447300df8d849012abd944755020ef6ffd0224f543ee0e46/diff:/var/lib/docker/overlay2/a1cdc6c5c0abc87bc9bf6f20787f8a7f60b47bb576117d0657a47fa8e8cb1bb3/diff:/var/lib/docker/overlay2/1bce56b6d994421c9e8e7ab1c3fc8162a0807ce519d20a0d3c76245b948dc059/diff:/var/lib/docker/overlay2/8ef55d134fc082e3ac7355cb2c398cc622206aa5193b9f33f846c95493137cd9/diff:/var/lib/docker/overlay2/b681c775e8f7aafadde3c2c0cb8c964a7b3e3b34931fd6088254a1d562b01358/diff:/var/lib/docker/overlay2/b894b99fbb9cbcb840cc0beed4ee65b8068d032ab6e5e73ab21b1a0c2402b622/diff:/var/lib/docker/overlay2/82bf74d26395a96b5f0c495839a87ff8490a25f9014d6da63a895f4ad6ec62a2/diff:/var/lib/docker/overlay2/6f6fc192909a6cd45f7132f8564623a28134a6f2038a118f9549ce67b347ca3e/diff:/var/lib/docker/overlay2/4077d33cb10c8135b6d24e43ff67f8171cbf5ed943a8ad1cc1c4d25d2c05901e/diff:/var/lib/docker/overlay2/b641c53b61a749099bc73439e27462e6d145af5c68d6cd135c10fcbba621cfc3/diff:/var/lib/docker/overlay2/70785b02abd4708d17c982796ebc65d959f64a25b893c5b96a569f76cbdca562/diff",
            "MergedDir": "/var/lib/docker/overlay2/26f57c831feb9b518fb218f4a0504e59cf7bf352ea41b808103bc9905c678fee/merged",
            "UpperDir": "/var/lib/docker/overlay2/26f57c831feb9b518fb218f4a0504e59cf7bf352ea41b808103bc9905c678fee/diff",
            "WorkDir": "/var/lib/docker/overlay2/26f57c831feb9b518fb218f4a0504e59cf7bf352ea41b808103bc9905c678fee/work"
        },
        "Name": "overlay2"
    },
    "RootFS": {
        "Type": "layers",
        "Layers": [
            "sha256:7555a8182c42c7737a384cfe03a3c7329f646a3bf389c4bcd75379fc85e6c144",
            "sha256:9488b6ecfd17a10a626d643505235825020891c183e45bb0dabeb457431d44c7",
            "sha256:1daea283ece173bfc2a02c734e9b910baaf56ec171473ba3c8f75662cc32a1cf",
            "sha256:a0651f94e72e52d866cc8ad747eb495a5109cb7b53a651a6a76b51d760282160",
            "sha256:e8f568d4c02e007b722c749c4d4e4e5c85331c3fee20fc0367f841809c3f71e8",
            "sha256:2be221d09227575d2111ae5ed34ce6fe3b2302398eee80c02cc450023d1760e8",
            "sha256:56ebb6dddfc52fad8a19a70f06b3174333b48d8534090e35d502afbb1c6bcb47",
            "sha256:c5b09b69535ba02b0d8a2ad0381bad15a51ec5c7dc35a3029ed47739c57d1cba",
            "sha256:bc1e0a67ee2b472f9fbb62085d569431f8a5baf4d1ee26e1fc419f8f85e46cbd",
            "sha256:2cdf9982548e9bef9835b133b765a5f7a890f5b02b11b1b51e54cac7ff9e07fa",
            "sha256:4f825aa4059da9c0535e0344c4aaf5670518a1a2ebd64efac5184db1e13fd0d4",
            "sha256:fb788819f8d91a751126541bc6332f858b865577aa0d2441dc2e6ceae7814bd3",
            "sha256:8a2aa5180f5692939edb4b36c2e467906ba9c67381aca8b138a9e04d55c4df9e",
            "sha256:d5f9dfa32b9796e3d335f4707f037fa471687083fe59f243b72f34035eb02be3",
            "sha256:5766ab22e3940d8d28945244042a649fad1220b6ec705f9a450bb5e4f40a5c15",
            "sha256:bfb1cf091a1036aab1184d97659ffa7c87e094dd643318812f555364e41ad6a3",
            "sha256:6bcf384629d364857916414a18859ffa74bf2a518f24a6582e9cba22a68ca89a",
            "sha256:cbc3a4d3d69dfe08e24d5bd8742ea2f106718164969669937835fa90e2dba276",
            "sha256:123c1ac9b2928a04e2247aa2b2cbc02a5f9dd6739abc44e62fd3489311c26bc9",
            "sha256:0d15dedbcd9f755f73ce09c1f06b69d1e55deb6201bff6cb4518e60ac533149f",
            "sha256:caa004d5cd8bc05a04acccfc160a70fb7fa24780ac66dad36c04dd29b1059609",
            "sha256:fb078a860b55ce714f78a8c40f5012a61f7cc5fbe416d6501a4f6fe07b05b181",
            "sha256:b8595ef8270d94f19de9b3539136ce432a9a2a8581d0311144299c3d36a0d142",
            "sha256:57f54bc3f62a2e6c71859d9a35f549a9e32041c6ae204e6cfb8c6e99087a686c",
            "sha256:edbad9e1bc71965914f42a2b812da6baa5f7905d7c9c9db2cd6364bf3b42de13",
            "sha256:f176c46992cef2f7ea7d1294db97d3d0401f64c3682fa04572834c03b8b362a4",
            "sha256:d744399e4f43a58a3f5a4c7295a7f69e8f577bb653b6c1a00489dd5344044818",
            "sha256:08268d19d5a8e0e6d0e503563374d4aa6be4dc9afbb074e38b8bd9e995f0f5ce"
        ]
    },
    "Metadata": {
        "LastTagTime": "2025-05-30T05:34:55.175004856+08:00"
    }
}

更多版本

docker.io/chiefcontainer/chief:v1.11

linux/amd64 docker.io65.65GB2025-05-30 07:24
11