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>=11.6 brand=tesla,driver>=418,driver<419 brand=tesla,driver>=450,driver<451 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=11.6.55-1
NV_CUDA_COMPAT_PACKAGE=cuda-compat-11-6
CUDA_VERSION=11.6.2
LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64
NVIDIA_VISIBLE_DEVICES=all
NVIDIA_DRIVER_CAPABILITIES=compute,utility
NV_CUDA_LIB_VERSION=11.6.2-1
NV_NVTX_VERSION=11.6.124-1
NV_LIBNPP_VERSION=11.6.3.124-1
NV_LIBNPP_PACKAGE=libnpp-11-6=11.6.3.124-1
NV_LIBCUSPARSE_VERSION=11.7.2.124-1
NV_LIBCUBLAS_PACKAGE_NAME=libcublas-11-6
NV_LIBCUBLAS_VERSION=11.9.2.110-1
NV_LIBCUBLAS_PACKAGE=libcublas-11-6=11.9.2.110-1
NV_LIBNCCL_PACKAGE_NAME=libnccl2
NV_LIBNCCL_PACKAGE_VERSION=2.12.10-1
NCCL_VERSION=2.12.10-1
NV_LIBNCCL_PACKAGE=libnccl2=2.12.10-1+cuda11.6
NVIDIA_PRODUCT_NAME=CUDA
NV_CUDA_CUDART_DEV_VERSION=11.6.55-1
NV_NVML_DEV_VERSION=11.6.55-1
NV_LIBCUSPARSE_DEV_VERSION=11.7.2.124-1
NV_LIBNPP_DEV_VERSION=11.6.3.124-1
NV_LIBNPP_DEV_PACKAGE=libnpp-dev-11-6=11.6.3.124-1
NV_LIBCUBLAS_DEV_VERSION=11.9.2.110-1
NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-11-6
NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-11-6=11.9.2.110-1
NV_NVPROF_VERSION=11.6.124-1
NV_NVPROF_DEV_PACKAGE=cuda-nvprof-11-6=11.6.124-1
NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev
NV_LIBNCCL_DEV_PACKAGE_VERSION=2.12.10-1
NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.12.10-1+cuda11.6
LIBRARY_PATH=/usr/local/cuda/lib64/stubs
NV_CUDNN_VERSION=8.4.0.27
NV_CUDNN_PACKAGE_NAME=libcudnn8
NV_CUDNN_PACKAGE=libcudnn8=8.4.0.27-1+cuda11.6
NV_CUDNN_PACKAGE_DEV=libcudnn8-dev=8.4.0.27-1+cuda11.6
PYTORCH_VERSION=v1.13.1
镜像构建历史
# 2022-12-21 05:28:52 0.00B 设置工作目录为/workspace
WORKDIR /workspace
# 2022-12-21 05:28:51 0.00B 设置环境变量 PYTORCH_VERSION
ENV PYTORCH_VERSION=v1.13.1
# 2022-12-21 05:28:51 0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64
# 2022-12-21 05:28:51 0.00B 设置环境变量 NVIDIA_DRIVER_CAPABILITIES
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
# 2022-12-21 05:28:51 0.00B 设置环境变量 NVIDIA_VISIBLE_DEVICES
ENV NVIDIA_VISIBLE_DEVICES=all
# 2022-12-21 05:28:51 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
# 2022-12-21 05:28:51 9.86GB 复制新文件或目录到容器中
COPY /opt/conda /opt/conda # buildkit
# 2022-12-21 05:19:32 2.99MB 执行命令并创建新的镜像层
RUN |1 PYTORCH_VERSION=v1.13.1 /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
# 2022-12-21 05:19:32 0.00B 添加元数据标签
LABEL com.nvidia.volumes.needed=nvidia_driver
# 2022-12-21 05:19:32 0.00B 定义构建参数
ARG PYTORCH_VERSION
# 2022-12-17 09:16:49 2.81GB 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
# 2022-12-17 09:16:49 0.00B 添加元数据标签
LABEL com.nvidia.cudnn.version=8.4.0.27
# 2022-12-17 09:16:49 0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
# 2022-12-17 09:16:49 0.00B 定义构建参数
ARG TARGETARCH
# 2022-12-17 09:16:49 0.00B 设置环境变量 NV_CUDNN_PACKAGE_DEV
ENV NV_CUDNN_PACKAGE_DEV=libcudnn8-dev=8.4.0.27-1+cuda11.6
# 2022-12-17 09:16:49 0.00B 设置环境变量 NV_CUDNN_PACKAGE
ENV NV_CUDNN_PACKAGE=libcudnn8=8.4.0.27-1+cuda11.6
# 2022-12-17 09:16:49 0.00B 设置环境变量 NV_CUDNN_PACKAGE_NAME
ENV NV_CUDNN_PACKAGE_NAME=libcudnn8
# 2022-12-17 09:16:49 0.00B 设置环境变量 NV_CUDNN_VERSION
ENV NV_CUDNN_VERSION=8.4.0.27
# 2022-12-15 04:43:48 0.00B 设置环境变量 LIBRARY_PATH
ENV LIBRARY_PATH=/usr/local/cuda/lib64/stubs
# 2022-12-15 04:43:48 371.26KB 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} ${NV_LIBNCCL_DEV_PACKAGE_NAME} # buildkit
# 2022-12-15 04:43:46 2.81GB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends cuda-cudart-dev-11-6=${NV_CUDA_CUDART_DEV_VERSION} cuda-command-line-tools-11-6=${NV_CUDA_LIB_VERSION} cuda-minimal-build-11-6=${NV_CUDA_LIB_VERSION} cuda-libraries-dev-11-6=${NV_CUDA_LIB_VERSION} cuda-nvml-dev-11-6=${NV_NVML_DEV_VERSION} ${NV_NVPROF_DEV_PACKAGE} ${NV_LIBNPP_DEV_PACKAGE} libcusparse-dev-11-6=${NV_LIBCUSPARSE_DEV_VERSION} ${NV_LIBCUBLAS_DEV_PACKAGE} ${NV_LIBNCCL_DEV_PACKAGE} && rm -rf /var/lib/apt/lists/* # buildkit
# 2022-12-15 04:43:46 0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
# 2022-12-15 04:43:46 0.00B 定义构建参数
ARG TARGETARCH
# 2022-12-15 04:43:46 0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE
ENV NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.12.10-1+cuda11.6
# 2022-12-15 04:43:46 0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.12.10-1
# 2022-12-15 04:43:46 0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE_VERSION
ENV NV_LIBNCCL_DEV_PACKAGE_VERSION=2.12.10-1
# 2022-12-15 04:43:46 0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE_NAME
ENV NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev
# 2022-12-15 04:43:46 0.00B 设置环境变量 NV_NVPROF_DEV_PACKAGE
ENV NV_NVPROF_DEV_PACKAGE=cuda-nvprof-11-6=11.6.124-1
# 2022-12-15 04:43:46 0.00B 设置环境变量 NV_NVPROF_VERSION
ENV NV_NVPROF_VERSION=11.6.124-1
# 2022-12-15 04:43:46 0.00B 设置环境变量 NV_LIBCUBLAS_DEV_PACKAGE
ENV NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-11-6=11.9.2.110-1
# 2022-12-15 04:43:46 0.00B 设置环境变量 NV_LIBCUBLAS_DEV_PACKAGE_NAME
ENV NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-11-6
# 2022-12-15 04:43:46 0.00B 设置环境变量 NV_LIBCUBLAS_DEV_VERSION
ENV NV_LIBCUBLAS_DEV_VERSION=11.9.2.110-1
# 2022-12-15 04:43:46 0.00B 设置环境变量 NV_LIBNPP_DEV_PACKAGE
ENV NV_LIBNPP_DEV_PACKAGE=libnpp-dev-11-6=11.6.3.124-1
# 2022-12-15 04:43:46 0.00B 设置环境变量 NV_LIBNPP_DEV_VERSION
ENV NV_LIBNPP_DEV_VERSION=11.6.3.124-1
# 2022-12-15 04:43:46 0.00B 设置环境变量 NV_LIBCUSPARSE_DEV_VERSION
ENV NV_LIBCUSPARSE_DEV_VERSION=11.7.2.124-1
# 2022-12-15 04:43:46 0.00B 设置环境变量 NV_NVML_DEV_VERSION
ENV NV_NVML_DEV_VERSION=11.6.55-1
# 2022-12-15 04:43:46 0.00B 设置环境变量 NV_CUDA_CUDART_DEV_VERSION
ENV NV_CUDA_CUDART_DEV_VERSION=11.6.55-1
# 2022-12-15 04:43:46 0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=11.6.2-1
# 2022-12-15 04:34:59 0.00B 配置容器启动时运行的命令
ENTRYPOINT ["/opt/nvidia/nvidia_entrypoint.sh"]
# 2022-12-15 04:34:59 0.00B 设置环境变量 NVIDIA_PRODUCT_NAME
ENV NVIDIA_PRODUCT_NAME=CUDA
# 2022-12-15 04:34:59 2.53KB 复制新文件或目录到容器中
COPY nvidia_entrypoint.sh /opt/nvidia/ # buildkit
# 2022-12-15 04:34:59 3.04KB 复制新文件或目录到容器中
COPY entrypoint.d/ /opt/nvidia/entrypoint.d/ # buildkit
# 2022-12-15 04:34:58 258.50KB 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} ${NV_LIBNCCL_PACKAGE_NAME} # buildkit
# 2022-12-15 04:34:58 1.89GB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends cuda-libraries-11-6=${NV_CUDA_LIB_VERSION} ${NV_LIBNPP_PACKAGE} cuda-nvtx-11-6=${NV_NVTX_VERSION} libcusparse-11-6=${NV_LIBCUSPARSE_VERSION} ${NV_LIBCUBLAS_PACKAGE} ${NV_LIBNCCL_PACKAGE} && rm -rf /var/lib/apt/lists/* # buildkit
# 2022-12-15 04:34:58 0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
# 2022-12-15 04:34:58 0.00B 定义构建参数
ARG TARGETARCH
# 2022-12-15 04:34:58 0.00B 设置环境变量 NV_LIBNCCL_PACKAGE
ENV NV_LIBNCCL_PACKAGE=libnccl2=2.12.10-1+cuda11.6
# 2022-12-15 04:34:58 0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.12.10-1
# 2022-12-15 04:34:58 0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_VERSION
ENV NV_LIBNCCL_PACKAGE_VERSION=2.12.10-1
# 2022-12-15 04:34:58 0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_NAME
ENV NV_LIBNCCL_PACKAGE_NAME=libnccl2
# 2022-12-15 04:34:58 0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE
ENV NV_LIBCUBLAS_PACKAGE=libcublas-11-6=11.9.2.110-1
# 2022-12-15 04:34:58 0.00B 设置环境变量 NV_LIBCUBLAS_VERSION
ENV NV_LIBCUBLAS_VERSION=11.9.2.110-1
# 2022-12-15 04:34:58 0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE_NAME
ENV NV_LIBCUBLAS_PACKAGE_NAME=libcublas-11-6
# 2022-12-15 04:34:58 0.00B 设置环境变量 NV_LIBCUSPARSE_VERSION
ENV NV_LIBCUSPARSE_VERSION=11.7.2.124-1
# 2022-12-15 04:34:58 0.00B 设置环境变量 NV_LIBNPP_PACKAGE
ENV NV_LIBNPP_PACKAGE=libnpp-11-6=11.6.3.124-1
# 2022-12-15 04:34:58 0.00B 设置环境变量 NV_LIBNPP_VERSION
ENV NV_LIBNPP_VERSION=11.6.3.124-1
# 2022-12-15 04:34:58 0.00B 设置环境变量 NV_NVTX_VERSION
ENV NV_NVTX_VERSION=11.6.124-1
# 2022-12-15 04:34:58 0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=11.6.2-1
# 2022-12-15 04:29:36 0.00B 设置环境变量 NVIDIA_DRIVER_CAPABILITIES
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
# 2022-12-15 04:29:36 0.00B 设置环境变量 NVIDIA_VISIBLE_DEVICES
ENV NVIDIA_VISIBLE_DEVICES=all
# 2022-12-15 04:29:36 16.05KB 复制新文件或目录到容器中
COPY NGC-DL-CONTAINER-LICENSE / # buildkit
# 2022-12-15 04:29:36 0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64
# 2022-12-15 04:29:36 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
# 2022-12-15 04:29:36 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
# 2022-12-15 04:29:35 62.89MB 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-11-6=${NV_CUDA_CUDART_VERSION} ${NV_CUDA_COMPAT_PACKAGE} && rm -rf /var/lib/apt/lists/* # buildkit
# 2022-12-15 04:29:24 0.00B 设置环境变量 CUDA_VERSION
ENV CUDA_VERSION=11.6.2
# 2022-12-15 04:29:24 16.52MB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends gnupg2 curl ca-certificates && curl -fsSL https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/${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
# 2022-12-15 04:29:24 0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
# 2022-12-15 04:29:24 0.00B 定义构建参数
ARG TARGETARCH
# 2022-12-15 04:29:24 0.00B 设置环境变量 NV_CUDA_COMPAT_PACKAGE
ENV NV_CUDA_COMPAT_PACKAGE=cuda-compat-11-6
# 2022-12-15 04:29:24 0.00B 设置环境变量 NV_CUDA_CUDART_VERSION
ENV NV_CUDA_CUDART_VERSION=11.6.55-1
# 2022-12-15 04:29:24 0.00B 设置环境变量 NVIDIA_REQUIRE_CUDA brand brand brand brand brand brand brand brand brand brand brand brand
ENV NVIDIA_REQUIRE_CUDA=cuda>=11.6 brand=tesla,driver>=418,driver<419 brand=tesla,driver>=450,driver<451 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
# 2022-12-15 04:29:24 0.00B 设置环境变量 NVARCH
ENV NVARCH=x86_64
# 2022-12-09 09:20:12 0.00B
/bin/sh -c #(nop) CMD ["bash"]
# 2022-12-09 09:20:11 63.15MB
/bin/sh -c #(nop) ADD file:3c88cea17de40599dc8b8da90adc8439635066835e930f9573ec6cc856c5c096 in /
镜像信息
{
"Id": "sha256:8426c5657bef5e71d50753670cc615e2e255bcc1a092dd3f855c0f55a7e8677f",
"RepoTags": [
"pytorch/pytorch:1.13.1-cuda11.6-cudnn8-devel",
"swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:1.13.1-cuda11.6-cudnn8-devel"
],
"RepoDigests": [
"pytorch/pytorch@sha256:58d848c38665fd3ed20bee65918255cb083637c860eb4fae67face2fb2ff5702",
"swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch@sha256:58d848c38665fd3ed20bee65918255cb083637c860eb4fae67face2fb2ff5702"
],
"Parent": "",
"Comment": "buildkit.dockerfile.v0",
"Created": "2022-12-20T13:28:52.592781304-08:00",
"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=11.6 brand=tesla,driver\u003e=418,driver\u003c419 brand=tesla,driver\u003e=450,driver\u003c451 brand=tesla,driver\u003e=470,driver\u003c471 brand=unknown,driver\u003e=470,driver\u003c471 brand=nvidia,driver\u003e=470,driver\u003c471 brand=nvidiartx,driver\u003e=470,driver\u003c471 brand=geforce,driver\u003e=470,driver\u003c471 brand=geforcertx,driver\u003e=470,driver\u003c471 brand=quadro,driver\u003e=470,driver\u003c471 brand=quadrortx,driver\u003e=470,driver\u003c471 brand=titan,driver\u003e=470,driver\u003c471 brand=titanrtx,driver\u003e=470,driver\u003c471",
"NV_CUDA_CUDART_VERSION=11.6.55-1",
"NV_CUDA_COMPAT_PACKAGE=cuda-compat-11-6",
"CUDA_VERSION=11.6.2",
"LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64",
"NVIDIA_VISIBLE_DEVICES=all",
"NVIDIA_DRIVER_CAPABILITIES=compute,utility",
"NV_CUDA_LIB_VERSION=11.6.2-1",
"NV_NVTX_VERSION=11.6.124-1",
"NV_LIBNPP_VERSION=11.6.3.124-1",
"NV_LIBNPP_PACKAGE=libnpp-11-6=11.6.3.124-1",
"NV_LIBCUSPARSE_VERSION=11.7.2.124-1",
"NV_LIBCUBLAS_PACKAGE_NAME=libcublas-11-6",
"NV_LIBCUBLAS_VERSION=11.9.2.110-1",
"NV_LIBCUBLAS_PACKAGE=libcublas-11-6=11.9.2.110-1",
"NV_LIBNCCL_PACKAGE_NAME=libnccl2",
"NV_LIBNCCL_PACKAGE_VERSION=2.12.10-1",
"NCCL_VERSION=2.12.10-1",
"NV_LIBNCCL_PACKAGE=libnccl2=2.12.10-1+cuda11.6",
"NVIDIA_PRODUCT_NAME=CUDA",
"NV_CUDA_CUDART_DEV_VERSION=11.6.55-1",
"NV_NVML_DEV_VERSION=11.6.55-1",
"NV_LIBCUSPARSE_DEV_VERSION=11.7.2.124-1",
"NV_LIBNPP_DEV_VERSION=11.6.3.124-1",
"NV_LIBNPP_DEV_PACKAGE=libnpp-dev-11-6=11.6.3.124-1",
"NV_LIBCUBLAS_DEV_VERSION=11.9.2.110-1",
"NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-11-6",
"NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-11-6=11.9.2.110-1",
"NV_NVPROF_VERSION=11.6.124-1",
"NV_NVPROF_DEV_PACKAGE=cuda-nvprof-11-6=11.6.124-1",
"NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev",
"NV_LIBNCCL_DEV_PACKAGE_VERSION=2.12.10-1",
"NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.12.10-1+cuda11.6",
"LIBRARY_PATH=/usr/local/cuda/lib64/stubs",
"NV_CUDNN_VERSION=8.4.0.27",
"NV_CUDNN_PACKAGE_NAME=libcudnn8",
"NV_CUDNN_PACKAGE=libcudnn8=8.4.0.27-1+cuda11.6",
"NV_CUDNN_PACKAGE_DEV=libcudnn8-dev=8.4.0.27-1+cuda11.6",
"PYTORCH_VERSION=v1.13.1"
],
"Cmd": null,
"Image": "",
"Volumes": null,
"WorkingDir": "/workspace",
"Entrypoint": [
"/opt/nvidia/nvidia_entrypoint.sh"
],
"OnBuild": null,
"Labels": {
"com.nvidia.cudnn.version": "8.4.0.27",
"com.nvidia.volumes.needed": "nvidia_driver",
"maintainer": "NVIDIA CORPORATION \u003ccudatools@nvidia.com\u003e"
}
},
"Architecture": "amd64",
"Os": "linux",
"Size": 17517597870,
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