docker.io/kjaebye/mujoco200:stable linux/amd64

Docker拉取命令

docker pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/kjaebye/mujoco200:stable
docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/kjaebye/mujoco200:stable  docker.io/kjaebye/mujoco200:stable

Containerd拉取命令

ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/kjaebye/mujoco200:stable
ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/kjaebye/mujoco200:stable  docker.io/kjaebye/mujoco200:stable

Shell快速替换命令

sed -i 's#kjaebye/mujoco200:stable#swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/kjaebye/mujoco200:stable#' 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/kjaebye/mujoco200:stable && docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/kjaebye/mujoco200:stable  docker.io/kjaebye/mujoco200:stable'

Ansible快速分发-Containerd

#ansible k8s -m shell -a 'ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/kjaebye/mujoco200:stable && ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/kjaebye/mujoco200:stable  docker.io/kjaebye/mujoco200:stable'

镜像构建历史

# 2023-04-03 15:51:58  151.20MB 
/bin/sh -c pip install mujoco_py==2.0.2.8
                        
# 2023-04-03 15:51:27  2.39KB 
/bin/sh -c echo 'export LD_LIBRARY_PATH=/root/.mujoco/mujoco200/bin:${LD_LIBRARY_PATH}' >> /etc/bash.bashrc
                        
# 2023-04-03 15:51:27  0.00B 
/bin/sh -c #(nop)  ENV LD_LIBRARY_PATH=/root/.mujoco/mujoco200/bin:/usr/local/nvidia/lib:/usr/local/nvidia/lib64
                        
# 2023-04-03 15:51:27  768.00B 
/bin/sh -c wget -P /root/.mujoco/mujoco200/bin/ https://roboti.us/file/mjkey.txt
                        
# 2023-04-03 15:51:25  8.87MB 
/bin/sh -c mv mujoco200_linux /root/.mujoco/mujoco200
                        
# 2023-04-03 15:51:24  0.00B 
/bin/sh -c rm mujoco200_linux.zip
                        
# 2023-04-03 15:51:24  8.87MB 
/bin/sh -c unzip mujoco200_linux.zip
                        
# 2023-04-03 15:51:23  4.43MB 
/bin/sh -c wget https://www.roboti.us/download/mujoco200_linux.zip
                        
# 2023-04-03 15:51:08  3.19KB 
/bin/sh -c echo '# startup run \n  if [ -f /root/start_ssh.sh ]; then \n      /root/start_ssh.sh \n  fi' >> /root/.bashrc
                        
# 2023-04-03 15:51:07  153.00B 
/bin/sh -c chmod +x /root/start_ssh.sh
                        
# 2023-04-03 15:51:07  153.00B 
/bin/sh -c echo '#!/bin/bash \n  LOGTIME=$(date "+%Y-%m-%d %H:%M:%S") \n  echo "[$LOGTIME] startup run..." >>/root/start_ssh.log \n  service ssh start >>/root/start_ssh.log' >> /root/start_ssh.sh
                        
# 2023-04-03 15:51:06  0.00B 
/bin/sh -c touch /root/start_ssh.sh
                        
# 2023-04-03 15:51:05  0.00B 
/bin/sh -c service ssh restart
                        
# 2023-04-03 15:51:05  3.39KB 
/bin/sh -c echo 'X11UseLocalhost no' >> /etc/ssh/sshd_config
                        
# 2023-04-03 15:51:04  3.37KB 
/bin/sh -c echo 'X11Displayoffset 10' >> /etc/ssh/sshd_config
                        
# 2023-04-03 15:51:03  3.35KB 
/bin/sh -c echo 'X11Forwarding yes' >> /etc/ssh/sshd_config
                        
# 2023-04-03 15:51:03  3.34KB 
/bin/sh -c echo 'PasswordAuthentication yes' >> /etc/ssh/sshd_config
                        
# 2023-04-03 15:51:02  3.31KB 
/bin/sh -c echo 'PermitRootLogin yes' >> /etc/ssh/sshd_config
                        
# 2023-04-03 15:51:02  776.00B 
/bin/sh -c echo "root:123123" | chpasswd
                        
# 2023-04-03 15:51:01  95.05MB 
/bin/sh -c apt-get install   libosmesa6-dev   libgl1-mesa-glx   libglfw3   libglew-dev   patchelf   gcc   python3.8-dev   unzip -y   libxrandr2   libxinerama1   libxcursor1   vim   openssh-server
                        
# 2023-04-03 15:50:36  768.00B 
/bin/sh -c #(nop) COPY file:b64b40240ac47710cb231cf8551ed20d6757514d4082863364f9b63d00439f49 in /root/.mujoco/mjkey.txt 
                        
# 2023-04-03 15:50:36  0.00B 
/bin/sh -c mkdir /root/.mujoco
                        
# 2023-04-03 15:50:36  0.00B 
/bin/sh -c rm get-pip.py
                        
# 2023-04-03 15:50:35  20.79MB 
/bin/sh -c python get-pip.py
                        
# 2023-04-03 15:50:28  2.57MB 
/bin/sh -c wget https://bootstrap.pypa.io/get-pip.py
                        
# 2023-04-03 15:50:27  4.08MB 
/bin/sh -c apt-get install python3-distutils -y
                        
# 2023-04-03 15:50:22  18.00B 
/bin/sh -c ln -s /usr/bin/python3.8 /usr/bin/python
                        
# 2023-04-03 15:50:22  18.00B 
/bin/sh -c ln -s /usr/bin/python3.8 /usr/bin/python3
                        
# 2023-04-03 15:50:21  0.00B 
/bin/sh -c rm /usr/bin/python3
                        
# 2023-04-03 15:50:20  14.63KB 
/bin/sh -c apt-get install python3.8 -y
                        
# 2023-04-03 15:50:19  676.42KB 
/bin/sh -c add-apt-repository ppa:deadsnakes/ppa -y
                        
# 2023-04-03 15:50:10  113.95MB 
/bin/sh -c apt-get install software-properties-common -y
                        
# 2023-04-03 15:49:31  217.66MB 
/bin/sh -c apt-get install git wget libgl1-mesa-glx -y
                        
# 2023-04-03 15:49:01  4.58MB 
/bin/sh -c DEBIAN_FRONTEND="noninteractive" apt-get install tzdata -y
                        
# 2023-04-03 15:48:57  43.32MB 
/bin/sh -c apt-get update
                        
# 2022-10-28 08:19:10  2.82GB 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
                        
# 2022-10-28 08:19:10  0.00B 添加元数据标签
LABEL com.nvidia.cudnn.version=8.1.1.33
                        
# 2022-10-28 08:19:10  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2022-10-28 08:19:10  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2022-10-28 08:19:10  0.00B 设置环境变量 NV_CUDNN_PACKAGE_DEV
ENV NV_CUDNN_PACKAGE_DEV=libcudnn8-dev=8.1.1.33-1+cuda11.2
                        
# 2022-10-28 08:19:10  0.00B 设置环境变量 NV_CUDNN_PACKAGE
ENV NV_CUDNN_PACKAGE=libcudnn8=8.1.1.33-1+cuda11.2
                        
# 2022-10-28 08:19:10  0.00B 设置环境变量 NV_CUDNN_PACKAGE_NAME
ENV NV_CUDNN_PACKAGE_NAME=libcudnn8
                        
# 2022-10-28 08:19:10  0.00B 设置环境变量 NV_CUDNN_VERSION
ENV NV_CUDNN_VERSION=8.1.1.33
                        
# 2022-10-28 08:00:29  0.00B 设置环境变量 LIBRARY_PATH
ENV LIBRARY_PATH=/usr/local/cuda/lib64/stubs
                        
# 2022-10-28 08:00:29  367.08KB 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
                        
# 2022-10-28 08:00:28  2.31GB 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-11-2=${NV_CUDA_CUDART_DEV_VERSION}     cuda-command-line-tools-11-2=${NV_CUDA_LIB_VERSION}     cuda-minimal-build-11-2=${NV_CUDA_LIB_VERSION}     cuda-libraries-dev-11-2=${NV_CUDA_LIB_VERSION}     cuda-nvml-dev-11-2=${NV_NVML_DEV_VERSION}     ${NV_NVPROF_DEV_PACKAGE}     ${NV_LIBNPP_DEV_PACKAGE}     libcusparse-dev-11-2=${NV_LIBCUSPARSE_DEV_VERSION}     ${NV_LIBCUBLAS_DEV_PACKAGE}     ${NV_LIBNCCL_DEV_PACKAGE}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2022-10-28 08:00:28  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2022-10-28 08:00:28  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2022-10-28 08:00:28  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE
ENV NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.8.4-1+cuda11.2
                        
# 2022-10-28 08:00:28  0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.8.4-1
                        
# 2022-10-28 08:00:28  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE_VERSION
ENV NV_LIBNCCL_DEV_PACKAGE_VERSION=2.8.4-1
                        
# 2022-10-28 08:00:28  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE_NAME
ENV NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev
                        
# 2022-10-28 08:00:28  0.00B 设置环境变量 NV_NVPROF_DEV_PACKAGE
ENV NV_NVPROF_DEV_PACKAGE=cuda-nvprof-11-2=11.2.152-1
                        
# 2022-10-28 08:00:28  0.00B 设置环境变量 NV_NVPROF_VERSION
ENV NV_NVPROF_VERSION=11.2.152-1
                        
# 2022-10-28 08:00:28  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_PACKAGE
ENV NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-11-2=11.4.1.1043-1
                        
# 2022-10-28 08:00:28  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_PACKAGE_NAME
ENV NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-11-2
                        
# 2022-10-28 08:00:28  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_VERSION
ENV NV_LIBCUBLAS_DEV_VERSION=11.4.1.1043-1
                        
# 2022-10-28 08:00:28  0.00B 设置环境变量 NV_LIBNPP_DEV_PACKAGE
ENV NV_LIBNPP_DEV_PACKAGE=libnpp-dev-11-2=11.3.2.152-1
                        
# 2022-10-28 08:00:28  0.00B 设置环境变量 NV_LIBNPP_DEV_VERSION
ENV NV_LIBNPP_DEV_VERSION=11.3.2.152-1
                        
# 2022-10-28 08:00:28  0.00B 设置环境变量 NV_LIBCUSPARSE_DEV_VERSION
ENV NV_LIBCUSPARSE_DEV_VERSION=11.4.1.1152-1
                        
# 2022-10-28 08:00:28  0.00B 设置环境变量 NV_NVML_DEV_VERSION
ENV NV_NVML_DEV_VERSION=11.2.152-1
                        
# 2022-10-28 08:00:28  0.00B 设置环境变量 NV_CUDA_CUDART_DEV_VERSION
ENV NV_CUDA_CUDART_DEV_VERSION=11.2.152-1
                        
# 2022-10-28 08:00:28  0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=11.2.2-1
                        
# 2022-10-28 07:50:56  252.23KB 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
                        
# 2022-10-28 07:50:55  1.79GB 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-11-2=${NV_CUDA_LIB_VERSION}     ${NV_LIBNPP_PACKAGE}     cuda-nvtx-11-2=${NV_NVTX_VERSION}     libcusparse-11-2=${NV_LIBCUSPARSE_VERSION}     ${NV_LIBCUBLAS_PACKAGE}     ${NV_LIBNCCL_PACKAGE}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2022-10-28 07:50:55  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2022-10-28 07:50:55  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2022-10-28 07:50:55  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE
ENV NV_LIBNCCL_PACKAGE=libnccl2=2.8.4-1+cuda11.2
                        
# 2022-10-28 07:50:55  0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.8.4-1
                        
# 2022-10-28 07:50:55  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_VERSION
ENV NV_LIBNCCL_PACKAGE_VERSION=2.8.4-1
                        
# 2022-10-28 07:50:55  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_NAME
ENV NV_LIBNCCL_PACKAGE_NAME=libnccl2
                        
# 2022-10-28 07:50:55  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE
ENV NV_LIBCUBLAS_PACKAGE=libcublas-11-2=11.4.1.1043-1
                        
# 2022-10-28 07:50:55  0.00B 设置环境变量 NV_LIBCUBLAS_VERSION
ENV NV_LIBCUBLAS_VERSION=11.4.1.1043-1
                        
# 2022-10-28 07:50:55  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE_NAME
ENV NV_LIBCUBLAS_PACKAGE_NAME=libcublas-11-2
                        
# 2022-10-28 07:50:55  0.00B 设置环境变量 NV_LIBCUSPARSE_VERSION
ENV NV_LIBCUSPARSE_VERSION=11.4.1.1152-1
                        
# 2022-10-28 07:50:55  0.00B 设置环境变量 NV_LIBNPP_PACKAGE
ENV NV_LIBNPP_PACKAGE=libnpp-11-2=11.3.2.152-1
                        
# 2022-10-28 07:50:55  0.00B 设置环境变量 NV_LIBNPP_VERSION
ENV NV_LIBNPP_VERSION=11.3.2.152-1
                        
# 2022-10-28 07:50:55  0.00B 设置环境变量 NV_NVTX_VERSION
ENV NV_NVTX_VERSION=11.2.152-1
                        
# 2022-10-28 07:50:55  0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=11.2.2-1
                        
# 2022-10-28 07:46:10  0.00B 设置环境变量 NVIDIA_DRIVER_CAPABILITIES
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
                        
# 2022-10-28 07:46:10  0.00B 设置环境变量 NVIDIA_VISIBLE_DEVICES
ENV NVIDIA_VISIBLE_DEVICES=all
                        
# 2022-10-28 07:46:10  16.05KB 复制新文件或目录到容器中
COPY NGC-DL-CONTAINER-LICENSE / # buildkit
                        
# 2022-10-28 07:46:10  0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64
                        
# 2022-10-28 07:46:10  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
                        
# 2022-10-28 07:46:10  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
                        
# 2022-10-28 07:46:10  33.47MB 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-11-2=${NV_CUDA_CUDART_VERSION}     ${NV_CUDA_COMPAT_PACKAGE}     && ln -s cuda-11.2 /usr/local/cuda &&     rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2022-10-28 07:46:01  0.00B 设置环境变量 CUDA_VERSION
ENV CUDA_VERSION=11.2.2
                        
# 2022-10-28 07:46:01  18.29MB 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
                        
# 2022-10-28 07:46:01  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2022-10-28 07:46:01  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2022-10-28 07:46:01  0.00B 设置环境变量 NV_CUDA_COMPAT_PACKAGE
ENV NV_CUDA_COMPAT_PACKAGE=cuda-compat-11-2
                        
# 2022-10-28 07:46:01  0.00B 设置环境变量 NV_CUDA_CUDART_VERSION
ENV NV_CUDA_CUDART_VERSION=11.2.152-1
                        
# 2022-10-28 07:46:01  0.00B 设置环境变量 NVIDIA_REQUIRE_CUDA brand brand
ENV NVIDIA_REQUIRE_CUDA=cuda>=11.2 brand=tesla,driver>=418,driver<419 brand=tesla,driver>=450,driver<451
                        
# 2022-10-28 07:46:01  0.00B 设置环境变量 NVARCH
ENV NVARCH=x86_64
                        
# 2022-10-25 09:53:35  0.00B 
/bin/sh -c #(nop)  CMD ["bash"]
                        
# 2022-10-25 09:53:34  72.79MB 
/bin/sh -c #(nop) ADD file:7633003155a1059419aa1a6756fafb6e4f419d65bff7feb7c945de1e29dccb1e in / 
                        
                    

镜像信息

{
    "Id": "sha256:ad5b7fc7fe90ebabc0c76cfe3fccf0387e8939b0fa3420ce1a8c12bf686bf712",
    "RepoTags": [
        "kjaebye/mujoco200:stable",
        "swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/kjaebye/mujoco200:stable"
    ],
    "RepoDigests": [
        "kjaebye/mujoco200@sha256:155726315df852d74780f3ab47908562883a2858f3c9f5dede77baf0f9b61f25",
        "swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/kjaebye/mujoco200@sha256:155726315df852d74780f3ab47908562883a2858f3c9f5dede77baf0f9b61f25"
    ],
    "Parent": "",
    "Comment": "",
    "Created": "2023-04-03T07:51:58.758325816Z",
    "Container": "",
    "ContainerConfig": null,
    "DockerVersion": "20.10.22",
    "Author": "",
    "Config": {
        "Hostname": "",
        "Domainname": "",
        "User": "",
        "AttachStdin": false,
        "AttachStdout": false,
        "AttachStderr": false,
        "Tty": false,
        "OpenStdin": false,
        "StdinOnce": false,
        "Env": [
            "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=11.2 brand=tesla,driver\u003e=418,driver\u003c419 brand=tesla,driver\u003e=450,driver\u003c451",
            "NV_CUDA_CUDART_VERSION=11.2.152-1",
            "NV_CUDA_COMPAT_PACKAGE=cuda-compat-11-2",
            "CUDA_VERSION=11.2.2",
            "LD_LIBRARY_PATH=/root/.mujoco/mujoco200/bin:/usr/local/nvidia/lib:/usr/local/nvidia/lib64",
            "NVIDIA_VISIBLE_DEVICES=all",
            "NVIDIA_DRIVER_CAPABILITIES=compute,utility",
            "NV_CUDA_LIB_VERSION=11.2.2-1",
            "NV_NVTX_VERSION=11.2.152-1",
            "NV_LIBNPP_VERSION=11.3.2.152-1",
            "NV_LIBNPP_PACKAGE=libnpp-11-2=11.3.2.152-1",
            "NV_LIBCUSPARSE_VERSION=11.4.1.1152-1",
            "NV_LIBCUBLAS_PACKAGE_NAME=libcublas-11-2",
            "NV_LIBCUBLAS_VERSION=11.4.1.1043-1",
            "NV_LIBCUBLAS_PACKAGE=libcublas-11-2=11.4.1.1043-1",
            "NV_LIBNCCL_PACKAGE_NAME=libnccl2",
            "NV_LIBNCCL_PACKAGE_VERSION=2.8.4-1",
            "NCCL_VERSION=2.8.4-1",
            "NV_LIBNCCL_PACKAGE=libnccl2=2.8.4-1+cuda11.2",
            "NV_CUDA_CUDART_DEV_VERSION=11.2.152-1",
            "NV_NVML_DEV_VERSION=11.2.152-1",
            "NV_LIBCUSPARSE_DEV_VERSION=11.4.1.1152-1",
            "NV_LIBNPP_DEV_VERSION=11.3.2.152-1",
            "NV_LIBNPP_DEV_PACKAGE=libnpp-dev-11-2=11.3.2.152-1",
            "NV_LIBCUBLAS_DEV_VERSION=11.4.1.1043-1",
            "NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-11-2",
            "NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-11-2=11.4.1.1043-1",
            "NV_NVPROF_VERSION=11.2.152-1",
            "NV_NVPROF_DEV_PACKAGE=cuda-nvprof-11-2=11.2.152-1",
            "NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev",
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