docker.io/pytorch/pytorch:1.12.1-cuda11.3-cudnn8-devel linux/amd64

docker.io/pytorch/pytorch:1.12.1-cuda11.3-cudnn8-devel - 国内下载镜像源 浏览次数:7 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:1.12.1-cuda11.3-cudnn8-devel
国内镜像 swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:1.12.1-cuda11.3-cudnn8-devel
镜像ID sha256:fa50f7fed43abfb8603ccc5a6cd9c39f5b872c95a23c5ebdd479a09c3e10b9b6
镜像TAG 1.12.1-cuda11.3-cudnn8-devel
大小 14.06GB
镜像源 docker.io
项目信息 Docker-Hub主页 🚀项目TAG 🚀
CMD bash
启动入口
工作目录 /workspace
OS/平台 linux/amd64
浏览量 7 次
贡献者
镜像创建 2022-08-05T10:33:12.309297059-07:00
同步时间 2026-06-06 02:30
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>=11.3 brand=tesla,driver>=418,driver<419 driver>=450 NV_CUDA_CUDART_VERSION=11.3.109-1 NV_CUDA_COMPAT_PACKAGE=cuda-compat-11-3 CUDA_VERSION=11.3.1 LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64 NVIDIA_VISIBLE_DEVICES=all NVIDIA_DRIVER_CAPABILITIES=compute,utility NV_CUDA_LIB_VERSION=11.3.1-1 NV_NVTX_VERSION=11.3.109-1 NV_LIBNPP_VERSION=11.3.3.95-1 NV_LIBNPP_PACKAGE=libnpp-11-3=11.3.3.95-1 NV_LIBCUSPARSE_VERSION=11.6.0.109-1 NV_LIBCUBLAS_PACKAGE_NAME=libcublas-11-3 NV_LIBCUBLAS_VERSION=11.5.1.109-1 NV_LIBCUBLAS_PACKAGE=libcublas-11-3=11.5.1.109-1 NV_LIBNCCL_PACKAGE_NAME=libnccl2 NV_LIBNCCL_PACKAGE_VERSION=2.9.9-1 NCCL_VERSION=2.9.9-1 NV_LIBNCCL_PACKAGE=libnccl2=2.9.9-1+cuda11.3 NV_CUDA_CUDART_DEV_VERSION=11.3.109-1 NV_NVML_DEV_VERSION=11.3.58-1 NV_LIBCUSPARSE_DEV_VERSION=11.6.0.109-1 NV_LIBNPP_DEV_VERSION=11.3.3.95-1 NV_LIBNPP_DEV_PACKAGE=libnpp-dev-11-3=11.3.3.95-1 NV_LIBCUBLAS_DEV_VERSION=11.5.1.109-1 NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-11-3 NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-11-3=11.5.1.109-1 NV_NVPROF_VERSION=11.3.111-1 NV_NVPROF_DEV_PACKAGE=cuda-nvprof-11-3=11.3.111-1 NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev NV_LIBNCCL_DEV_PACKAGE_VERSION=2.9.9-1 NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.9.9-1+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=v1.12.1-rc5
镜像标签
8.2.0.53: com.nvidia.cudnn.version nvidia_driver: com.nvidia.volumes.needed NVIDIA CORPORATION <cudatools@nvidia.com>: maintainer

Docker拉取命令

docker pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:1.12.1-cuda11.3-cudnn8-devel
docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:1.12.1-cuda11.3-cudnn8-devel  docker.io/pytorch/pytorch:1.12.1-cuda11.3-cudnn8-devel

Containerd拉取命令

ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:1.12.1-cuda11.3-cudnn8-devel
ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:1.12.1-cuda11.3-cudnn8-devel  docker.io/pytorch/pytorch:1.12.1-cuda11.3-cudnn8-devel

Shell快速替换命令

sed -i 's#pytorch/pytorch:1.12.1-cuda11.3-cudnn8-devel#swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:1.12.1-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:1.12.1-cuda11.3-cudnn8-devel && docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:1.12.1-cuda11.3-cudnn8-devel  docker.io/pytorch/pytorch:1.12.1-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:1.12.1-cuda11.3-cudnn8-devel && ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:1.12.1-cuda11.3-cudnn8-devel  docker.io/pytorch/pytorch:1.12.1-cuda11.3-cudnn8-devel'

镜像构建历史


# 2022-08-06 01:33:12  0.00B 设置工作目录为/workspace
WORKDIR /workspace
                        
# 2022-08-06 01:33:11  0.00B 设置环境变量 PYTORCH_VERSION
ENV PYTORCH_VERSION=v1.12.1-rc5
                        
# 2022-08-06 01:33:11  0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64
                        
# 2022-08-06 01:33:11  0.00B 设置环境变量 NVIDIA_DRIVER_CAPABILITIES
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
                        
# 2022-08-06 01:33:11  0.00B 设置环境变量 NVIDIA_VISIBLE_DEVICES
ENV NVIDIA_VISIBLE_DEVICES=all
                        
# 2022-08-06 01:33:11  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
                        
# 2022-08-06 01:33:11  5.83GB 复制新文件或目录到容器中
COPY /opt/conda /opt/conda # buildkit
                        
# 2022-08-06 01:27:14  4.52MB 执行命令并创建新的镜像层
RUN |1 PYTORCH_VERSION=v1.12.1-rc5 /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
                        
# 2022-08-06 01:27:14  0.00B 添加元数据标签
LABEL com.nvidia.volumes.needed=nvidia_driver
                        
# 2022-08-06 01:27:14  0.00B 定义构建参数
ARG PYTORCH_VERSION
                        
# 2022-05-20 14:55:11  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
                        
# 2022-05-20 14:55:11  0.00B 添加元数据标签
LABEL com.nvidia.cudnn.version=8.2.0.53
                        
# 2022-05-20 14:55:11  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2022-05-20 14:55:11  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2022-05-20 14:55:11  0.00B 设置环境变量 NV_CUDNN_PACKAGE_NAME
ENV NV_CUDNN_PACKAGE_NAME=libcudnn8
                        
# 2022-05-20 14:55:11  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
                        
# 2022-05-20 14:55:11  0.00B 设置环境变量 NV_CUDNN_PACKAGE
ENV NV_CUDNN_PACKAGE=libcudnn8=8.2.0.53-1+cuda11.3
                        
# 2022-05-20 14:55:11  0.00B 设置环境变量 NV_CUDNN_VERSION
ENV NV_CUDNN_VERSION=8.2.0.53
                        
# 2022-05-20 14:41:38  0.00B 设置环境变量 LIBRARY_PATH
ENV LIBRARY_PATH=/usr/local/cuda/lib64/stubs
                        
# 2022-05-20 14:41:38  367.10KB 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
                        
# 2022-05-20 14:41:37  2.36GB 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_NVPROF_DEV_PACKAGE}     ${NV_LIBNPP_DEV_PACKAGE}     libcusparse-dev-11-3=${NV_LIBCUSPARSE_DEV_VERSION}     ${NV_LIBCUBLAS_DEV_PACKAGE}     ${NV_LIBNCCL_DEV_PACKAGE}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2022-05-20 14:41:37  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2022-05-20 14:41:37  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2022-05-20 14:41:37  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE
ENV NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.9.9-1+cuda11.3
                        
# 2022-05-20 14:41:37  0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.9.9-1
                        
# 2022-05-20 14:41:37  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE_VERSION
ENV NV_LIBNCCL_DEV_PACKAGE_VERSION=2.9.9-1
                        
# 2022-05-20 14:41:37  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE_NAME
ENV NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev
                        
# 2022-05-20 14:41:37  0.00B 设置环境变量 NV_NVPROF_DEV_PACKAGE
ENV NV_NVPROF_DEV_PACKAGE=cuda-nvprof-11-3=11.3.111-1
                        
# 2022-05-20 14:41:37  0.00B 设置环境变量 NV_NVPROF_VERSION
ENV NV_NVPROF_VERSION=11.3.111-1
                        
# 2022-05-20 14:41:37  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_PACKAGE
ENV NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-11-3=11.5.1.109-1
                        
# 2022-05-20 14:41:37  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_PACKAGE_NAME
ENV NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-11-3
                        
# 2022-05-20 14:41:37  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_VERSION
ENV NV_LIBCUBLAS_DEV_VERSION=11.5.1.109-1
                        
# 2022-05-20 14:41:37  0.00B 设置环境变量 NV_LIBNPP_DEV_PACKAGE
ENV NV_LIBNPP_DEV_PACKAGE=libnpp-dev-11-3=11.3.3.95-1
                        
# 2022-05-20 14:41:37  0.00B 设置环境变量 NV_LIBNPP_DEV_VERSION
ENV NV_LIBNPP_DEV_VERSION=11.3.3.95-1
                        
# 2022-05-20 14:41:37  0.00B 设置环境变量 NV_LIBCUSPARSE_DEV_VERSION
ENV NV_LIBCUSPARSE_DEV_VERSION=11.6.0.109-1
                        
# 2022-05-20 14:41:37  0.00B 设置环境变量 NV_NVML_DEV_VERSION
ENV NV_NVML_DEV_VERSION=11.3.58-1
                        
# 2022-05-20 14:41:37  0.00B 设置环境变量 NV_CUDA_CUDART_DEV_VERSION
ENV NV_CUDA_CUDART_DEV_VERSION=11.3.109-1
                        
# 2022-05-20 14:41:37  0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=11.3.1-1
                        
# 2022-05-20 14:34:48  255.32KB 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
                        
# 2022-05-20 14:34:48  1.74GB 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
                        
# 2022-05-20 14:34:48  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2022-05-20 14:34:48  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2022-05-20 14:34:48  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE
ENV NV_LIBNCCL_PACKAGE=libnccl2=2.9.9-1+cuda11.3
                        
# 2022-05-20 14:34:48  0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.9.9-1
                        
# 2022-05-20 14:34:48  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_VERSION
ENV NV_LIBNCCL_PACKAGE_VERSION=2.9.9-1
                        
# 2022-05-20 14:34:48  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_NAME
ENV NV_LIBNCCL_PACKAGE_NAME=libnccl2
                        
# 2022-05-20 14:34:48  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE
ENV NV_LIBCUBLAS_PACKAGE=libcublas-11-3=11.5.1.109-1
                        
# 2022-05-20 14:34:48  0.00B 设置环境变量 NV_LIBCUBLAS_VERSION
ENV NV_LIBCUBLAS_VERSION=11.5.1.109-1
                        
# 2022-05-20 14:34:48  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE_NAME
ENV NV_LIBCUBLAS_PACKAGE_NAME=libcublas-11-3
                        
# 2022-05-20 14:34:48  0.00B 设置环境变量 NV_LIBCUSPARSE_VERSION
ENV NV_LIBCUSPARSE_VERSION=11.6.0.109-1
                        
# 2022-05-20 14:34:48  0.00B 设置环境变量 NV_LIBNPP_PACKAGE
ENV NV_LIBNPP_PACKAGE=libnpp-11-3=11.3.3.95-1
                        
# 2022-05-20 14:34:48  0.00B 设置环境变量 NV_LIBNPP_VERSION
ENV NV_LIBNPP_VERSION=11.3.3.95-1
                        
# 2022-05-20 14:34:48  0.00B 设置环境变量 NV_NVTX_VERSION
ENV NV_NVTX_VERSION=11.3.109-1
                        
# 2022-05-20 14:34:48  0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=11.3.1-1
                        
# 2022-05-20 14:31:18  0.00B 设置环境变量 NVIDIA_DRIVER_CAPABILITIES
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
                        
# 2022-05-20 14:31:18  0.00B 设置环境变量 NVIDIA_VISIBLE_DEVICES
ENV NVIDIA_VISIBLE_DEVICES=all
                        
# 2022-05-20 14:31:18  16.05KB 复制新文件或目录到容器中
COPY NGC-DL-CONTAINER-LICENSE / # buildkit
                        
# 2022-05-20 14:31:18  0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64
                        
# 2022-05-20 14:31:18  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
                        
# 2022-05-20 14:31:18  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
                        
# 2022-05-20 14:31:17  34.25MB 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
                        
# 2022-05-20 14:31:07  0.00B 设置环境变量 CUDA_VERSION
ENV CUDA_VERSION=11.3.1
                        
# 2022-05-20 14:31:07  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/${NVARCH}/3bf863cc.pub | apt-key add - &&     echo "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/${NVARCH} /" > /etc/apt/sources.list.d/cuda.list &&     apt-get purge --autoremove -y curl     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2022-05-20 14:31:07  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2022-05-20 14:31:07  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2022-05-20 14:31:07  0.00B 设置环境变量 NV_CUDA_COMPAT_PACKAGE
ENV NV_CUDA_COMPAT_PACKAGE=cuda-compat-11-3
                        
# 2022-05-20 14:31:07  0.00B 设置环境变量 NV_CUDA_CUDART_VERSION
ENV NV_CUDA_CUDART_VERSION=11.3.109-1
                        
# 2022-05-20 14:31:07  0.00B 设置环境变量 NVIDIA_REQUIRE_CUDA brand driver>
ENV NVIDIA_REQUIRE_CUDA=cuda>=11.3 brand=tesla,driver>=418,driver<419 driver>=450
                        
# 2022-05-20 14:31:07  0.00B 设置环境变量 NVARCH
ENV NVARCH=x86_64
                        
# 2022-04-30 07:20:51  0.00B 
/bin/sh -c #(nop)  CMD ["bash"]
                        
# 2022-04-30 07:20:51  63.15MB 
/bin/sh -c #(nop) ADD file:f657a56a18426c3a88d620a7024e7b91424d926e7b47faa6a97c2369c4c4a228 in / 
                        
                    

镜像信息

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    "Id": "sha256:fa50f7fed43abfb8603ccc5a6cd9c39f5b872c95a23c5ebdd479a09c3e10b9b6",
    "RepoTags": [
        "pytorch/pytorch:1.12.1-cuda11.3-cudnn8-devel",
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    "RepoDigests": [
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    ],
    "Parent": "",
    "Comment": "buildkit.dockerfile.v0",
    "Created": "2022-08-05T10:33:12.309297059-07:00",
    "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 driver\u003e=450",
            "NV_CUDA_CUDART_VERSION=11.3.109-1",
            "NV_CUDA_COMPAT_PACKAGE=cuda-compat-11-3",
            "CUDA_VERSION=11.3.1",
            "LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64",
            "NVIDIA_VISIBLE_DEVICES=all",
            "NVIDIA_DRIVER_CAPABILITIES=compute,utility",
            "NV_CUDA_LIB_VERSION=11.3.1-1",
            "NV_NVTX_VERSION=11.3.109-1",
            "NV_LIBNPP_VERSION=11.3.3.95-1",
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