docker.io/rayproject/ray:nightly-py312-cu128 - 镜像下载

docker.io/rayproject/ray:nightly-py312-cu128

linux/amd64 docker.io deerluffy 贡献

_rayproject/ray_ RAY 是一个基于 Python 的高性能计算框架，可以在多种环境中运行，包括本地、云和集群。Ray 提供了高效的并行计算能力，并且可以与其他库和框架集成。 -Ray 的主要特点有： * 高性能：Ray 使用了高性能的编译器和执行引擎，可以在多种环境中运行。 * 可扩展性：Ray 可以轻松地 scales to thousands of machines and can handle large-scale computations. * 可组合性：Ray 可以与其他库和框架集成，例如 TensorFlow、PyTorch 和 scikit-learn。总的来说，《RAY》是一个功能强大且灵活的计算框架，可以满足各种计算需求。

393

浏览次数

12.57GB

镜像大小

源镜像

docker.io/rayproject/ray:nightly-py312-cu128

国内镜像

swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/rayproject/ray:nightly-py312-cu128

镜像ID

sha256:5ea8a8f5af6d1f25ab12c33e95d23f2b74557d41b1cfdde61a1eb506aa1d0462

镜像 TAG

nightly-py312-cu128

镜像大小

12.57GB

平台架构

linux/amd64

镜像源

docker.io

项目信息

Hub 主页所有 TAG

CMD

启动入口

/opt/nvidia/nvidia_entrypoint.sh

工作目录

/home/ray

OS/平台

linux/amd64

镜像创建

2025-09-08T06:06:05.904382293Z

同步时间

2025-09-09 11:39

浏览量

393 次

贡献者

deerluffy

⚙️ 环境变量 45

Key	Value
`PATH=/home/ray/anaconda3/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/nvidia/bin`	`0`
`NVARCH=x86_64`	`1`
NVIDIA_REQUIRE_CUDA=cuda>=12.8 brand=unknown,driver>=470,driver<471 brand=grid,driver>=470,driver<471 brand=tesla,driver>=470,driver<471 brand=nvidia,driver>=470,driver<471 brand=quadro,driver>=470,driver<471 brand=quadrortx,driver>=470,driver<471 brand=nvidiartx,driver>=470,driver<471 brand=vapps,driver>=470,driver<471 brand=vpc,driver>=470,driver<471 brand=vcs,driver>=470,driver<471 brand=vws,driver>=470,driver<471 brand=cloudgaming,driver>=470,driver<471 brand=unknown,driver>=535,driver<536 brand=grid,driver>=535,driver<536 brand=tesla,driver>=535,driver<536 brand=nvidia,driver>=535,driver<536 brand=quadro,driver>=535,driver<536 brand=quadrortx,driver>=535,driver<536 brand=nvidiartx,driver>=535,driver<536 brand=vapps,driver>=535,driver<536 brand=vpc,driver>=535,driver<536 brand=vcs,driver>=535,driver<536 brand=vws,driver>=535,driver<536 brand=cloudgaming,driver>=535,driver<536 brand=unknown,driver>=550,driver<551 brand=grid,driver>=550,driver<551 brand=tesla,driver>=550,driver<551 brand=nvidia,driver>=550,driver<551 brand=quadro,driver>=550,driver<551 brand=quadrortx,driver>=550,driver<551 brand=nvidiartx,driver>=550,driver<551 brand=vapps,driver>=550,driver<551 brand=vpc,driver>=550,driver<551 brand=vcs,driver>=550,driver<551 brand=vws,driver>=550,driver<551 brand=cloudgaming,driver>=550,driver<551 brand=unknown,driver>=560,driver<561 brand=grid,driver>=560,driver<561 brand=tesla,driver>=560,driver<561 brand=nvidia,driver>=560,driver<561 brand=quadro,driver>=560,driver<561 brand=quadrortx,driver>=560,driver<561 brand=nvidiartx,driver>=560,driver<561 brand=vapps,driver>=560,driver<561 brand=vpc,driver>=560,driver<561 brand=vcs,driver>=560,driver<561 brand=vws,driver>=560,driver<561 brand=cloudgaming,driver>=560,driver<561 brand=unknown,driver>=565,driver<566 brand=grid,driver>=565,driver<566 brand=tesla,driver>=565,driver<566 brand=nvidia,driver>=565,driver<566 brand=quadro,driver>=565,driver<566 brand=quadrortx,driver>=565,driver<566 brand=nvidiartx,driver>=565,driver<566 brand=vapps,driver>=565,driver<566 brand=vpc,driver>=565,driver<566 brand=vcs,driver>=565,driver<566 brand=vws,driver>=565,driver<566 brand=cloudgaming,driver>=565,driver<566	`2`
`NV_CUDA_CUDART_VERSION=12.8.90-1`	`3`
`CUDA_VERSION=12.8.1`	`4`
`LD_LIBRARY_PATH=/usr/local/cuda/lib64:/usr/local/nvidia/lib64`	`5`
`NVIDIA_VISIBLE_DEVICES=all`	`6`
`NVIDIA_DRIVER_CAPABILITIES=compute,utility`	`7`
`NV_CUDA_LIB_VERSION=12.8.1-1`	`8`
`NV_NVTX_VERSION=12.8.90-1`	`9`
`NV_LIBNPP_VERSION=12.3.3.100-1`	`10`
`NV_LIBNPP_PACKAGE=libnpp-12-8=12.3.3.100-1`	`11`
`NV_LIBCUSPARSE_VERSION=12.5.8.93-1`	`12`
`NV_LIBCUBLAS_PACKAGE_NAME=libcublas-12-8`	`13`
`NV_LIBCUBLAS_VERSION=12.8.4.1-1`	`14`
`NV_LIBCUBLAS_PACKAGE=libcublas-12-8=12.8.4.1-1`	`15`
`NV_LIBNCCL_PACKAGE_NAME=libnccl2`	`16`
`NV_LIBNCCL_PACKAGE_VERSION=2.25.1-1`	`17`
`NCCL_VERSION=2.25.1-1`	`18`
`NV_LIBNCCL_PACKAGE=libnccl2=2.25.1-1+cuda12.8`	`19`
`NVIDIA_PRODUCT_NAME=CUDA`	`20`
`NV_CUDA_CUDART_DEV_VERSION=12.8.90-1`	`21`
`NV_NVML_DEV_VERSION=12.8.90-1`	`22`
`NV_LIBCUSPARSE_DEV_VERSION=12.5.8.93-1`	`23`
`NV_LIBNPP_DEV_VERSION=12.3.3.100-1`	`24`
`NV_LIBNPP_DEV_PACKAGE=libnpp-dev-12-8=12.3.3.100-1`	`25`
`NV_LIBCUBLAS_DEV_VERSION=12.8.4.1-1`	`26`
`NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-12-8`	`27`
`NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-12-8=12.8.4.1-1`	`28`
`NV_CUDA_NSIGHT_COMPUTE_VERSION=12.8.1-1`	`29`
`NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE=cuda-nsight-compute-12-8=12.8.1-1`	`30`
`NV_NVPROF_VERSION=12.8.90-1`	`31`
`NV_NVPROF_DEV_PACKAGE=cuda-nvprof-12-8=12.8.90-1`	`32`
`NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev`	`33`
`NV_LIBNCCL_DEV_PACKAGE_VERSION=2.25.1-1`	`34`
`NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.25.1-1+cuda12.8`	`35`
`LIBRARY_PATH=/usr/local/cuda/lib64/stubs`	`36`
`NV_CUDNN_VERSION=9.8.0.87-1`	`37`
`NV_CUDNN_PACKAGE_NAME=libcudnn9-cuda-12`	`38`
`NV_CUDNN_PACKAGE=libcudnn9-cuda-12=9.8.0.87-1`	`39`
`NV_CUDNN_PACKAGE_DEV=libcudnn9-dev-cuda-12=9.8.0.87-1`	`40`
`TZ=America/Los_Angeles`	`41`
`LC_ALL=C.UTF-8`	`42`
`LANG=C.UTF-8`	`43`
`HOME=/home/ray`	`44`

🏷️ 镜像标签 4

Key	Value
`9.8.0.87-1`	`com.nvidia.cudnn.version`
`NVIDIA CORPORATION <cudatools@nvidia.com>`	`maintainer`
`ubuntu`	`org.opencontainers.image.ref.name`
`22.04`	`org.opencontainers.image.version`

Chatgpt|Claude一站式支持平台提供先进的AI镜像服务，助你在国内优雅的使用Chatgpt和Claude等AI服务

无权限下载？点我修复生成 Docker Run 命令生成 Kubernetes YAML

Docker拉取命令

docker pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/rayproject/ray:nightly-py312-cu128
docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/rayproject/ray:nightly-py312-cu128  docker.io/rayproject/ray:nightly-py312-cu128

Containerd拉取命令

ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/rayproject/ray:nightly-py312-cu128
ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/rayproject/ray:nightly-py312-cu128  docker.io/rayproject/ray:nightly-py312-cu128

Shell快速替换命令

sed -i 's#rayproject/ray:nightly-py312-cu128#swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/rayproject/ray:nightly-py312-cu128#' 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/rayproject/ray:nightly-py312-cu128 && docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/rayproject/ray:nightly-py312-cu128  docker.io/rayproject/ray:nightly-py312-cu128'

Ansible快速分发-Containerd

#ansible k8s -m shell -a 'ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/rayproject/ray:nightly-py312-cu128 && ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/rayproject/ray:nightly-py312-cu128  docker.io/rayproject/ray:nightly-py312-cu128'

镜像构建历史


# 2025-09-08 14:06:05  19.61KB 执行命令并创建新的镜像层
RUN |3 WHEEL_PATH=.whl/ray-3.0.0.dev0-cp312-cp312-manylinux2014_x86_64.whl FIND_LINKS_PATH=.whl CONSTRAINTS_FILE=requirements_compiled.txt /bin/bash -c $HOME/anaconda3/bin/pip freeze > /home/ray/pip-freeze.txt # buildkit
                        
# 2025-09-08 14:06:05  874.62MB 执行命令并创建新的镜像层
RUN |3 WHEEL_PATH=.whl/ray-3.0.0.dev0-cp312-cp312-manylinux2014_x86_64.whl FIND_LINKS_PATH=.whl CONSTRAINTS_FILE=requirements_compiled.txt /bin/bash -c $HOME/anaconda3/bin/pip --no-cache-dir install -c $CONSTRAINTS_FILE     `basename $WHEEL_PATH`[all]     --find-links $FIND_LINKS_PATH && sudo rm `basename $WHEEL_PATH` # buildkit
                        
# 2025-09-08 14:05:24  85.50MB 复制新文件或目录到容器中
COPY .whl .whl # buildkit
                        
# 2025-09-08 14:05:24  70.60MB 复制新文件或目录到容器中
COPY .whl/ray-3.0.0.dev0-cp312-cp312-manylinux2014_x86_64.whl . # buildkit
                        
# 2025-09-08 14:05:24  0.00B 定义构建参数
ARG CONSTRAINTS_FILE=requirements_compiled.txt
                        
# 2025-09-08 14:05:24  0.00B 定义构建参数
ARG FIND_LINKS_PATH=.whl
                        
# 2025-09-08 14:05:24  0.00B 定义构建参数
ARG WHEEL_PATH
                        
# 2025-09-08 13:10:41  0.00B 设置工作目录为/home/ray
WORKDIR /home/ray
                        
# 2025-09-08 13:10:41  680.55MB 执行命令并创建新的镜像层
RUN |4 DEBIAN_FRONTEND=noninteractive PYTHON_VERSION=3.12 RAY_UID=1000 RAY_GID=100 /bin/bash -c /dev/pipes/EOF # buildkit
                        
# 2025-09-08 13:09:58  0.00B 
SHELL [/bin/bash -c]
                        
# 2025-09-08 13:09:58  59.98KB 复制新文件或目录到容器中
COPY python/requirements_compiled.txt /home/ray/requirements_compiled.txt # buildkit
                        
# 2025-09-08 13:09:58  0.00B 设置环境变量 HOME
ENV HOME=/home/ray
                        
# 2025-09-08 13:09:58  0.00B 指定运行容器时使用的用户
USER 1000
                        
# 2025-09-08 13:09:58  470.72MB 执行命令并创建新的镜像层
RUN |4 DEBIAN_FRONTEND=noninteractive PYTHON_VERSION=3.12 RAY_UID=1000 RAY_GID=100 /bin/sh -c /dev/pipes/EOF # buildkit
                        
# 2025-09-08 13:09:58  0.00B 定义构建参数
ARG RAY_GID=100
                        
# 2025-09-08 13:09:58  0.00B 定义构建参数
ARG RAY_UID=1000
                        
# 2025-09-08 13:09:58  0.00B 定义构建参数
ARG PYTHON_VERSION=3.9
                        
# 2025-09-08 13:09:58  0.00B 定义构建参数
ARG DEBIAN_FRONTEND=noninteractive
                        
# 2025-09-08 13:09:58  0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/cuda/lib64:/usr/local/nvidia/lib64
                        
# 2025-09-08 13:09:58  0.00B 设置环境变量 PATH
ENV PATH=/home/ray/anaconda3/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/nvidia/bin
                        
# 2025-09-08 13:09:58  0.00B 设置环境变量 LANG
ENV LANG=C.UTF-8
                        
# 2025-09-08 13:09:58  0.00B 设置环境变量 LC_ALL
ENV LC_ALL=C.UTF-8
                        
# 2025-09-08 13:09:58  0.00B 设置环境变量 TZ
ENV TZ=America/Los_Angeles
                        
# 2025-03-11 07:14:56  1.05GB 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
                        
# 2025-03-11 07:14:56  0.00B 添加元数据标签
LABEL com.nvidia.cudnn.version=9.8.0.87-1
                        
# 2025-03-11 07:14:56  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2025-03-11 07:14:56  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2025-03-11 07:14:56  0.00B 设置环境变量 NV_CUDNN_PACKAGE_DEV
ENV NV_CUDNN_PACKAGE_DEV=libcudnn9-dev-cuda-12=9.8.0.87-1
                        
# 2025-03-11 07:14:56  0.00B 设置环境变量 NV_CUDNN_PACKAGE
ENV NV_CUDNN_PACKAGE=libcudnn9-cuda-12=9.8.0.87-1
                        
# 2025-03-11 07:14:56  0.00B 设置环境变量 NV_CUDNN_PACKAGE_NAME
ENV NV_CUDNN_PACKAGE_NAME=libcudnn9-cuda-12
                        
# 2025-03-11 07:14:56  0.00B 设置环境变量 NV_CUDNN_VERSION
ENV NV_CUDNN_VERSION=9.8.0.87-1
                        
# 2025-03-11 06:36:52  0.00B 设置环境变量 LIBRARY_PATH
ENV LIBRARY_PATH=/usr/local/cuda/lib64/stubs
                        
# 2025-03-11 06:36:52  389.48KB 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
                        
# 2025-03-11 06:36:52  5.94GB 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-12-8=${NV_CUDA_CUDART_DEV_VERSION}     cuda-command-line-tools-12-8=${NV_CUDA_LIB_VERSION}     cuda-minimal-build-12-8=${NV_CUDA_LIB_VERSION}     cuda-libraries-dev-12-8=${NV_CUDA_LIB_VERSION}     cuda-nvml-dev-12-8=${NV_NVML_DEV_VERSION}     ${NV_NVPROF_DEV_PACKAGE}     ${NV_LIBNPP_DEV_PACKAGE}     libcusparse-dev-12-8=${NV_LIBCUSPARSE_DEV_VERSION}     ${NV_LIBCUBLAS_DEV_PACKAGE}     ${NV_LIBNCCL_DEV_PACKAGE}     ${NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2025-03-11 06:36:52  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2025-03-11 06:36:52  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2025-03-11 06:36:52  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE
ENV NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.25.1-1+cuda12.8
                        
# 2025-03-11 06:36:52  0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.25.1-1
                        
# 2025-03-11 06:36:52  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE_VERSION
ENV NV_LIBNCCL_DEV_PACKAGE_VERSION=2.25.1-1
                        
# 2025-03-11 06:36:52  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE_NAME
ENV NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev
                        
# 2025-03-11 06:36:52  0.00B 设置环境变量 NV_NVPROF_DEV_PACKAGE
ENV NV_NVPROF_DEV_PACKAGE=cuda-nvprof-12-8=12.8.90-1
                        
# 2025-03-11 06:36:52  0.00B 设置环境变量 NV_NVPROF_VERSION
ENV NV_NVPROF_VERSION=12.8.90-1
                        
# 2025-03-11 06:36:52  0.00B 设置环境变量 NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE
ENV NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE=cuda-nsight-compute-12-8=12.8.1-1
                        
# 2025-03-11 06:36:52  0.00B 设置环境变量 NV_CUDA_NSIGHT_COMPUTE_VERSION
ENV NV_CUDA_NSIGHT_COMPUTE_VERSION=12.8.1-1
                        
# 2025-03-11 06:36:52  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_PACKAGE
ENV NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-12-8=12.8.4.1-1
                        
# 2025-03-11 06:36:52  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_PACKAGE_NAME
ENV NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-12-8
                        
# 2025-03-11 06:36:52  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_VERSION
ENV NV_LIBCUBLAS_DEV_VERSION=12.8.4.1-1
                        
# 2025-03-11 06:36:52  0.00B 设置环境变量 NV_LIBNPP_DEV_PACKAGE
ENV NV_LIBNPP_DEV_PACKAGE=libnpp-dev-12-8=12.3.3.100-1
                        
# 2025-03-11 06:36:52  0.00B 设置环境变量 NV_LIBNPP_DEV_VERSION
ENV NV_LIBNPP_DEV_VERSION=12.3.3.100-1
                        
# 2025-03-11 06:36:52  0.00B 设置环境变量 NV_LIBCUSPARSE_DEV_VERSION
ENV NV_LIBCUSPARSE_DEV_VERSION=12.5.8.93-1
                        
# 2025-03-11 06:36:52  0.00B 设置环境变量 NV_NVML_DEV_VERSION
ENV NV_NVML_DEV_VERSION=12.8.90-1
                        
# 2025-03-11 06:36:52  0.00B 设置环境变量 NV_CUDA_CUDART_DEV_VERSION
ENV NV_CUDA_CUDART_DEV_VERSION=12.8.90-1
                        
# 2025-03-11 06:36:52  0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=12.8.1-1
                        
# 2025-03-11 06:24:31  0.00B 配置容器启动时运行的命令
ENTRYPOINT ["/opt/nvidia/nvidia_entrypoint.sh"]
                        
# 2025-03-11 06:24:31  0.00B 设置环境变量 NVIDIA_PRODUCT_NAME
ENV NVIDIA_PRODUCT_NAME=CUDA
                        
# 2025-03-11 06:24:31  2.53KB 复制新文件或目录到容器中
COPY nvidia_entrypoint.sh /opt/nvidia/ # buildkit
                        
# 2025-03-11 06:24:31  3.06KB 复制新文件或目录到容器中
COPY entrypoint.d/ /opt/nvidia/entrypoint.d/ # buildkit
                        
# 2025-03-11 06:24:31  263.00KB 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
                        
# 2025-03-11 06:24:31  3.11GB 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-12-8=${NV_CUDA_LIB_VERSION}     ${NV_LIBNPP_PACKAGE}     cuda-nvtx-12-8=${NV_NVTX_VERSION}     libcusparse-12-8=${NV_LIBCUSPARSE_VERSION}     ${NV_LIBCUBLAS_PACKAGE}     ${NV_LIBNCCL_PACKAGE}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2025-03-11 06:24:31  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2025-03-11 06:24:31  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2025-03-11 06:24:31  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE
ENV NV_LIBNCCL_PACKAGE=libnccl2=2.25.1-1+cuda12.8
                        
# 2025-03-11 06:24:31  0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.25.1-1
                        
# 2025-03-11 06:24:31  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_VERSION
ENV NV_LIBNCCL_PACKAGE_VERSION=2.25.1-1
                        
# 2025-03-11 06:24:31  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_NAME
ENV NV_LIBNCCL_PACKAGE_NAME=libnccl2
                        
# 2025-03-11 06:24:31  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE
ENV NV_LIBCUBLAS_PACKAGE=libcublas-12-8=12.8.4.1-1
                        
# 2025-03-11 06:24:31  0.00B 设置环境变量 NV_LIBCUBLAS_VERSION
ENV NV_LIBCUBLAS_VERSION=12.8.4.1-1
                        
# 2025-03-11 06:24:31  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE_NAME
ENV NV_LIBCUBLAS_PACKAGE_NAME=libcublas-12-8
                        
# 2025-03-11 06:24:31  0.00B 设置环境变量 NV_LIBCUSPARSE_VERSION
ENV NV_LIBCUSPARSE_VERSION=12.5.8.93-1
                        
# 2025-03-11 06:24:31  0.00B 设置环境变量 NV_LIBNPP_PACKAGE
ENV NV_LIBNPP_PACKAGE=libnpp-12-8=12.3.3.100-1
                        
# 2025-03-11 06:24:31  0.00B 设置环境变量 NV_LIBNPP_VERSION
ENV NV_LIBNPP_VERSION=12.3.3.100-1
                        
# 2025-03-11 06:24:31  0.00B 设置环境变量 NV_NVTX_VERSION
ENV NV_NVTX_VERSION=12.8.90-1
                        
# 2025-03-11 06:24:31  0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=12.8.1-1
                        
# 2025-03-11 06:19:20  0.00B 设置环境变量 NVIDIA_DRIVER_CAPABILITIES
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
                        
# 2025-03-11 06:19:20  0.00B 设置环境变量 NVIDIA_VISIBLE_DEVICES
ENV NVIDIA_VISIBLE_DEVICES=all
                        
# 2025-03-11 06:19:20  17.29KB 复制新文件或目录到容器中
COPY NGC-DL-CONTAINER-LICENSE / # buildkit
                        
# 2025-03-11 06:19:20  0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/cuda/lib64
                        
# 2025-03-11 06:19:20  0.00B 设置环境变量 PATH
ENV PATH=/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
                        
# 2025-03-11 06:19:20  22.00B 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c echo "/usr/local/cuda/lib64" >> /etc/ld.so.conf.d/nvidia.conf # buildkit
                        
# 2025-03-11 06:19:20  203.35MB 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-12-8=${NV_CUDA_CUDART_VERSION}     cuda-compat-12-8     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2025-03-11 06:19:05  0.00B 设置环境变量 CUDA_VERSION
ENV CUDA_VERSION=12.8.1
                        
# 2025-03-11 06:19:05  10.60MB 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 -fsSLO https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/${NVARCH}/cuda-keyring_1.1-1_all.deb &&     dpkg -i cuda-keyring_1.1-1_all.deb &&     apt-get purge --autoremove -y curl     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2025-03-11 06:19:05  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2025-03-11 06:19:05  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2025-03-11 06:19:05  0.00B 设置环境变量 NV_CUDA_CUDART_VERSION
ENV NV_CUDA_CUDART_VERSION=12.8.90-1
                        
# 2025-03-11 06:19:05  0.00B 设置环境变量 NVIDIA_REQUIRE_CUDA brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand
ENV NVIDIA_REQUIRE_CUDA=cuda>=12.8 brand=unknown,driver>=470,driver<471 brand=grid,driver>=470,driver<471 brand=tesla,driver>=470,driver<471 brand=nvidia,driver>=470,driver<471 brand=quadro,driver>=470,driver<471 brand=quadrortx,driver>=470,driver<471 brand=nvidiartx,driver>=470,driver<471 brand=vapps,driver>=470,driver<471 brand=vpc,driver>=470,driver<471 brand=vcs,driver>=470,driver<471 brand=vws,driver>=470,driver<471 brand=cloudgaming,driver>=470,driver<471 brand=unknown,driver>=535,driver<536 brand=grid,driver>=535,driver<536 brand=tesla,driver>=535,driver<536 brand=nvidia,driver>=535,driver<536 brand=quadro,driver>=535,driver<536 brand=quadrortx,driver>=535,driver<536 brand=nvidiartx,driver>=535,driver<536 brand=vapps,driver>=535,driver<536 brand=vpc,driver>=535,driver<536 brand=vcs,driver>=535,driver<536 brand=vws,driver>=535,driver<536 brand=cloudgaming,driver>=535,driver<536 brand=unknown,driver>=550,driver<551 brand=grid,driver>=550,driver<551 brand=tesla,driver>=550,driver<551 brand=nvidia,driver>=550,driver<551 brand=quadro,driver>=550,driver<551 brand=quadrortx,driver>=550,driver<551 brand=nvidiartx,driver>=550,driver<551 brand=vapps,driver>=550,driver<551 brand=vpc,driver>=550,driver<551 brand=vcs,driver>=550,driver<551 brand=vws,driver>=550,driver<551 brand=cloudgaming,driver>=550,driver<551 brand=unknown,driver>=560,driver<561 brand=grid,driver>=560,driver<561 brand=tesla,driver>=560,driver<561 brand=nvidia,driver>=560,driver<561 brand=quadro,driver>=560,driver<561 brand=quadrortx,driver>=560,driver<561 brand=nvidiartx,driver>=560,driver<561 brand=vapps,driver>=560,driver<561 brand=vpc,driver>=560,driver<561 brand=vcs,driver>=560,driver<561 brand=vws,driver>=560,driver<561 brand=cloudgaming,driver>=560,driver<561 brand=unknown,driver>=565,driver<566 brand=grid,driver>=565,driver<566 brand=tesla,driver>=565,driver<566 brand=nvidia,driver>=565,driver<566 brand=quadro,driver>=565,driver<566 brand=quadrortx,driver>=565,driver<566 brand=nvidiartx,driver>=565,driver<566 brand=vapps,driver>=565,driver<566 brand=vpc,driver>=565,driver<566 brand=vcs,driver>=565,driver<566 brand=vws,driver>=565,driver<566 brand=cloudgaming,driver>=565,driver<566
                        
# 2025-03-11 06:19:05  0.00B 设置环境变量 NVARCH
ENV NVARCH=x86_64
                        
# 2025-01-26 13:31:11  0.00B 
/bin/sh -c #(nop)  CMD ["/bin/bash"]
                        
# 2025-01-26 13:31:10  77.86MB 
/bin/sh -c #(nop) ADD file:1b6c8c9518be42fa2afe5e241ca31677fce58d27cdfa88baa91a65a259be3637 in / 
                        
# 2025-01-26 13:31:07  0.00B 
/bin/sh -c #(nop)  LABEL org.opencontainers.image.version=22.04
                        
# 2025-01-26 13:31:07  0.00B 
/bin/sh -c #(nop)  LABEL org.opencontainers.image.ref.name=ubuntu
                        
# 2025-01-26 13:31:07  0.00B 
/bin/sh -c #(nop)  ARG LAUNCHPAD_BUILD_ARCH
                        
# 2025-01-26 13:31:07  0.00B 
/bin/sh -c #(nop)  ARG RELEASE

镜像信息

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    "RepoTags": [
        "rayproject/ray:nightly-py312-cu128",
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    "RepoDigests": [
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    ],
    "Parent": "",
    "Comment": "buildkit.dockerfile.v0",
    "Created": "2025-09-08T06:06:05.904382293Z",
    "Container": "",
    "ContainerConfig": null,
    "DockerVersion": "",
    "Author": "",
    "Config": {
        "Hostname": "",
        "Domainname": "",
        "User": "1000",
        "AttachStdin": false,
        "AttachStdout": false,
        "AttachStderr": false,
        "Tty": false,
        "OpenStdin": false,
        "StdinOnce": false,
        "Env": [
            "PATH=/home/ray/anaconda3/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/nvidia/bin",
            "NVARCH=x86_64",
            "NVIDIA_REQUIRE_CUDA=cuda\u003e=12.8 brand=unknown,driver\u003e=470,driver\u003c471 brand=grid,driver\u003e=470,driver\u003c471 brand=tesla,driver\u003e=470,driver\u003c471 brand=nvidia,driver\u003e=470,driver\u003c471 brand=quadro,driver\u003e=470,driver\u003c471 brand=quadrortx,driver\u003e=470,driver\u003c471 brand=nvidiartx,driver\u003e=470,driver\u003c471 brand=vapps,driver\u003e=470,driver\u003c471 brand=vpc,driver\u003e=470,driver\u003c471 brand=vcs,driver\u003e=470,driver\u003c471 brand=vws,driver\u003e=470,driver\u003c471 brand=cloudgaming,driver\u003e=470,driver\u003c471 brand=unknown,driver\u003e=535,driver\u003c536 brand=grid,driver\u003e=535,driver\u003c536 brand=tesla,driver\u003e=535,driver\u003c536 brand=nvidia,driver\u003e=535,driver\u003c536 brand=quadro,driver\u003e=535,driver\u003c536 brand=quadrortx,driver\u003e=535,driver\u003c536 brand=nvidiartx,driver\u003e=535,driver\u003c536 brand=vapps,driver\u003e=535,driver\u003c536 brand=vpc,driver\u003e=535,driver\u003c536 brand=vcs,driver\u003e=535,driver\u003c536 brand=vws,driver\u003e=535,driver\u003c536 brand=cloudgaming,driver\u003e=535,driver\u003c536 brand=unknown,driver\u003e=550,driver\u003c551 brand=grid,driver\u003e=550,driver\u003c551 brand=tesla,driver\u003e=550,driver\u003c551 brand=nvidia,driver\u003e=550,driver\u003c551 brand=quadro,driver\u003e=550,driver\u003c551 brand=quadrortx,driver\u003e=550,driver\u003c551 brand=nvidiartx,driver\u003e=550,driver\u003c551 brand=vapps,driver\u003e=550,driver\u003c551 brand=vpc,driver\u003e=550,driver\u003c551 brand=vcs,driver\u003e=550,driver\u003c551 brand=vws,driver\u003e=550,driver\u003c551 brand=cloudgaming,driver\u003e=550,driver\u003c551 brand=unknown,driver\u003e=560,driver\u003c561 brand=grid,driver\u003e=560,driver\u003c561 brand=tesla,driver\u003e=560,driver\u003c561 brand=nvidia,driver\u003e=560,driver\u003c561 brand=quadro,driver\u003e=560,driver\u003c561 brand=quadrortx,driver\u003e=560,driver\u003c561 brand=nvidiartx,driver\u003e=560,driver\u003c561 brand=vapps,driver\u003e=560,driver\u003c561 brand=vpc,driver\u003e=560,driver\u003c561 brand=vcs,driver\u003e=560,driver\u003c561 brand=vws,driver\u003e=560,driver\u003c561 brand=cloudgaming,driver\u003e=560,driver\u003c561 brand=unknown,driver\u003e=565,driver\u003c566 brand=grid,driver\u003e=565,driver\u003c566 brand=tesla,driver\u003e=565,driver\u003c566 brand=nvidia,driver\u003e=565,driver\u003c566 brand=quadro,driver\u003e=565,driver\u003c566 brand=quadrortx,driver\u003e=565,driver\u003c566 brand=nvidiartx,driver\u003e=565,driver\u003c566 brand=vapps,driver\u003e=565,driver\u003c566 brand=vpc,driver\u003e=565,driver\u003c566 brand=vcs,driver\u003e=565,driver\u003c566 brand=vws,driver\u003e=565,driver\u003c566 brand=cloudgaming,driver\u003e=565,driver\u003c566",
            "NV_CUDA_CUDART_VERSION=12.8.90-1",
            "CUDA_VERSION=12.8.1",
            "LD_LIBRARY_PATH=/usr/local/cuda/lib64:/usr/local/nvidia/lib64",
            "NVIDIA_VISIBLE_DEVICES=all",
            "NVIDIA_DRIVER_CAPABILITIES=compute,utility",
            "NV_CUDA_LIB_VERSION=12.8.1-1",
            "NV_NVTX_VERSION=12.8.90-1",
            "NV_LIBNPP_VERSION=12.3.3.100-1",
            "NV_LIBNPP_PACKAGE=libnpp-12-8=12.3.3.100-1",
            "NV_LIBCUSPARSE_VERSION=12.5.8.93-1",
            "NV_LIBCUBLAS_PACKAGE_NAME=libcublas-12-8",
            "NV_LIBCUBLAS_VERSION=12.8.4.1-1",
            "NV_LIBCUBLAS_PACKAGE=libcublas-12-8=12.8.4.1-1",
            "NV_LIBNCCL_PACKAGE_NAME=libnccl2",
            "NV_LIBNCCL_PACKAGE_VERSION=2.25.1-1",
            "NCCL_VERSION=2.25.1-1",
            "NV_LIBNCCL_PACKAGE=libnccl2=2.25.1-1+cuda12.8",
            "NVIDIA_PRODUCT_NAME=CUDA",
            "NV_CUDA_CUDART_DEV_VERSION=12.8.90-1",
            "NV_NVML_DEV_VERSION=12.8.90-1",
            "NV_LIBCUSPARSE_DEV_VERSION=12.5.8.93-1",
            "NV_LIBNPP_DEV_VERSION=12.3.3.100-1",
            "NV_LIBNPP_DEV_PACKAGE=libnpp-dev-12-8=12.3.3.100-1",
            "NV_LIBCUBLAS_DEV_VERSION=12.8.4.1-1",
            "NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-12-8",
            "NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-12-8=12.8.4.1-1",
            "NV_CUDA_NSIGHT_COMPUTE_VERSION=12.8.1-1",
            "NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE=cuda-nsight-compute-12-8=12.8.1-1",
            "NV_NVPROF_VERSION=12.8.90-1",
            "NV_NVPROF_DEV_PACKAGE=cuda-nvprof-12-8=12.8.90-1",
            "NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev",
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            "LIBRARY_PATH=/usr/local/cuda/lib64/stubs",
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            "NV_CUDNN_PACKAGE=libcudnn9-cuda-12=9.8.0.87-1",
            "NV_CUDNN_PACKAGE_DEV=libcudnn9-dev-cuda-12=9.8.0.87-1",
            "TZ=America/Los_Angeles",
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        "Image": "",
        "Volumes": null,
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        "Entrypoint": [
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        "Labels": {
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    "Metadata": {
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}

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