docker.io/rayproject/ray:2.55.0-py312-gpu - 镜像下载

docker.io/rayproject/ray:2.55.0-py312-gpu

linux/amd64 docker.io

_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。

浏览次数

11.65GB

镜像大小

国内镜像

swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/rayproject/ray:2.55.0-py312-gpu

源镜像

docker.io/rayproject/ray:2.55.0-py312-gpu

镜像ID

sha256:6f8c0fad3bdf4e54d88e83a91eadeaeb7a1e5117a84cee2da4f9e87bb771f65d

镜像 TAG

2.55.0-py312-gpu

镜像大小

11.65GB

平台架构

linux/amd64

镜像源

docker.io

项目信息

Hub 主页所有 TAG

CMD

/bin/bash

启动入口

/opt/nvidia/nvidia_entrypoint.sh

工作目录

/home/ray

OS/平台

linux/amd64

镜像创建

2026-04-11T05:22:10.940945551Z

同步时间

2026-07-23 01:27

浏览量

10 次

贡献者

⚙️ 环境变量 46

Key	Value
`PATH=/home/ray/anaconda3/bin:/usr/local/nvidia/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>=12.1 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 brand=tesla,driver>=525,driver<526 brand=unknown,driver>=525,driver<526 brand=nvidia,driver>=525,driver<526 brand=nvidiartx,driver>=525,driver<526 brand=geforce,driver>=525,driver<526 brand=geforcertx,driver>=525,driver<526 brand=quadro,driver>=525,driver<526 brand=quadrortx,driver>=525,driver<526 brand=titan,driver>=525,driver<526 brand=titanrtx,driver>=525,driver<526	`2`
`NV_CUDA_CUDART_VERSION=12.1.105-1`	`3`
`NV_CUDA_COMPAT_PACKAGE=cuda-compat-12-1`	`4`
`CUDA_VERSION=12.1.1`	`5`
`LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64:/usr/local/nvidia/lib64`	`6`
`NVIDIA_VISIBLE_DEVICES=all`	`7`
`NVIDIA_DRIVER_CAPABILITIES=compute,utility`	`8`
`NV_CUDA_LIB_VERSION=12.1.1-1`	`9`
`NV_NVTX_VERSION=12.1.105-1`	`10`
`NV_LIBNPP_VERSION=12.1.0.40-1`	`11`
`NV_LIBNPP_PACKAGE=libnpp-12-1=12.1.0.40-1`	`12`
`NV_LIBCUSPARSE_VERSION=12.1.0.106-1`	`13`
`NV_LIBCUBLAS_PACKAGE_NAME=libcublas-12-1`	`14`
`NV_LIBCUBLAS_VERSION=12.1.3.1-1`	`15`
`NV_LIBCUBLAS_PACKAGE=libcublas-12-1=12.1.3.1-1`	`16`
`NV_LIBNCCL_PACKAGE_NAME=libnccl2`	`17`
`NV_LIBNCCL_PACKAGE_VERSION=2.17.1-1`	`18`
`NCCL_VERSION=2.17.1-1`	`19`
`NV_LIBNCCL_PACKAGE=libnccl2=2.17.1-1+cuda12.1`	`20`
`NVIDIA_PRODUCT_NAME=CUDA`	`21`
`NV_CUDA_CUDART_DEV_VERSION=12.1.105-1`	`22`
`NV_NVML_DEV_VERSION=12.1.105-1`	`23`
`NV_LIBCUSPARSE_DEV_VERSION=12.1.0.106-1`	`24`
`NV_LIBNPP_DEV_VERSION=12.1.0.40-1`	`25`
`NV_LIBNPP_DEV_PACKAGE=libnpp-dev-12-1=12.1.0.40-1`	`26`
`NV_LIBCUBLAS_DEV_VERSION=12.1.3.1-1`	`27`
`NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-12-1`	`28`
`NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-12-1=12.1.3.1-1`	`29`
`NV_CUDA_NSIGHT_COMPUTE_VERSION=12.1.1-1`	`30`
`NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE=cuda-nsight-compute-12-1=12.1.1-1`	`31`
`NV_NVPROF_VERSION=12.1.105-1`	`32`
`NV_NVPROF_DEV_PACKAGE=cuda-nvprof-12-1=12.1.105-1`	`33`
`NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev`	`34`
`NV_LIBNCCL_DEV_PACKAGE_VERSION=2.17.1-1`	`35`
`NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.17.1-1+cuda12.1`	`36`
`LIBRARY_PATH=/usr/local/cuda/lib64/stubs`	`37`
`NV_CUDNN_VERSION=8.9.0.131`	`38`
`NV_CUDNN_PACKAGE_NAME=libcudnn8`	`39`
`NV_CUDNN_PACKAGE=libcudnn8=8.9.0.131-1+cuda12.1`	`40`
`NV_CUDNN_PACKAGE_DEV=libcudnn8-dev=8.9.0.131-1+cuda12.1`	`41`
`TZ=America/Los_Angeles`	`42`
`LC_ALL=C.UTF-8`	`43`
`LANG=C.UTF-8`	`44`
`HOME=/home/ray`	`45`

🏷️ 镜像标签 6

Key	Value
`8.9.0.131`	`com.nvidia.cudnn.version`
`58af3fc5cad7e74001b3f89bffd9052a9e7aa2bb`	`io.ray.ray-commit`
`2.55.0`	`io.ray.ray-version`
`NVIDIA CORPORATION <cudatools@nvidia.com>`	`maintainer`
`ubuntu`	`org.opencontainers.image.ref.name`
`22.04`	`org.opencontainers.image.version`

🛡️ 镜像安全扫描

ubuntu 22.04 Trivy 2026-07-23 01:28 查看完整报告

388

低危 LOW

2621

中危 MEDIUM

247

高危 HIGH

严重 CRITICAL

受影响目标 (5)

docker.io/rayproject/ray:2.55.0-py312-gpu (ubuntu 22.04) ubuntu Java jar Python python-pkg usr/local/bin/uv rustbinary usr/local/bin/uvx rustbinary

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:2.55.0-py312-gpu
docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/rayproject/ray:2.55.0-py312-gpu  docker.io/rayproject/ray:2.55.0-py312-gpu

Containerd拉取命令

ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/rayproject/ray:2.55.0-py312-gpu
ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/rayproject/ray:2.55.0-py312-gpu  docker.io/rayproject/ray:2.55.0-py312-gpu

Shell快速替换命令

sed -i 's#rayproject/ray:2.55.0-py312-gpu#swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/rayproject/ray:2.55.0-py312-gpu#' 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:2.55.0-py312-gpu && docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/rayproject/ray:2.55.0-py312-gpu  docker.io/rayproject/ray:2.55.0-py312-gpu'

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:2.55.0-py312-gpu && ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/rayproject/ray:2.55.0-py312-gpu  docker.io/rayproject/ray:2.55.0-py312-gpu'

镜像构建历史


# 2026-04-11 13:22:10  0.00B 设置默认要执行的命令
CMD ["/bin/bash"]
                        
# 2026-04-11 13:22:10  937.27MB 执行命令并创建新的镜像层
RUN |3 IMAGE_TYPE=ray RAY_COMMIT=58af3fc5cad7e74001b3f89bffd9052a9e7aa2bb RAY_VERSION=2.55.0 /bin/bash -c /dev/pipes/EOF # buildkit
                        
# 2026-04-11 13:21:26  73.77MB 复制新文件或目录到容器中
COPY /opt/artifacts/*.whl /home/ray/ # buildkit
                        
# 2026-04-11 13:21:26  0.00B 添加元数据标签
LABEL io.ray.ray-version=2.55.0
                        
# 2026-04-11 13:21:26  0.00B 添加元数据标签
LABEL io.ray.ray-commit=58af3fc5cad7e74001b3f89bffd9052a9e7aa2bb
                        
# 2026-04-11 13:21:26  0.00B 定义构建参数
ARG RAY_VERSION=3.0.0.dev0
                        
# 2026-04-11 13:21:26  0.00B 定义构建参数
ARG RAY_COMMIT=unknown-commit
                        
# 2026-04-11 13:21:26  0.00B 定义构建参数
ARG IMAGE_TYPE=ray
                        
# 2026-04-11 12:49:41  0.00B 设置工作目录为/home/ray
WORKDIR /home/ray
                        
# 2026-04-11 12:49:41  634.42MB 执行命令并创建新的镜像层
RUN |6 DEBIAN_FRONTEND=noninteractive PYTHON_VERSION=3.12 CONSTRAINTS_FILE=python/requirements_compiled_py3.12.txt PYTHON_DEPSET=python/deplocks/base_deps/ray_base_deps_py3.12.lock RAY_UID=1000 RAY_GID=100 /bin/bash -c /dev/pipes/EOF # buildkit
                        
# 2026-04-11 12:48:54  0.00B 
SHELL [/bin/bash -c]
                        
# 2026-04-11 12:48:54  88.30KB 复制新文件或目录到容器中
COPY python/deplocks/base_deps/ray_base_deps_py3.12.lock /home/ray/python_depset.lock # buildkit
                        
# 2026-04-11 12:48:54  61.60KB 复制新文件或目录到容器中
COPY python/requirements_compiled_py3.12.txt /home/ray/requirements_compiled.txt # buildkit
                        
# 2026-04-11 12:48:54  0.00B 设置工作目录为/home/ray
WORKDIR /home/ray
                        
# 2026-04-11 12:48:54  0.00B 设置环境变量 HOME
ENV HOME=/home/ray
                        
# 2026-04-11 12:48:54  0.00B 指定运行容器时使用的用户
USER 1000
                        
# 2026-04-11 12:48:54  16.71MB 复制新文件或目录到容器中
COPY /usr/local/bin/haproxy /usr/local/bin/haproxy # buildkit
                        
# 2026-04-11 12:48:39  500.69MB 执行命令并创建新的镜像层
RUN |6 DEBIAN_FRONTEND=noninteractive PYTHON_VERSION=3.12 CONSTRAINTS_FILE=python/requirements_compiled_py3.12.txt PYTHON_DEPSET=python/deplocks/base_deps/ray_base_deps_py3.12.lock RAY_UID=1000 RAY_GID=100 /bin/sh -c /dev/pipes/EOF # buildkit
                        
# 2026-04-11 12:48:39  0.00B 定义构建参数
ARG RAY_GID=100
                        
# 2026-04-11 12:48:39  0.00B 定义构建参数
ARG RAY_UID=1000
                        
# 2026-04-11 12:48:39  0.00B 定义构建参数
ARG PYTHON_DEPSET=python/deplocks/base_deps/ray_base_deps_py3.12.lock
                        
# 2026-04-11 12:48:39  0.00B 定义构建参数
ARG CONSTRAINTS_FILE=python/requirements_compiled_py3.12.txt
                        
# 2026-04-11 12:48:39  0.00B 定义构建参数
ARG PYTHON_VERSION=3.10
                        
# 2026-04-11 12:48:39  0.00B 定义构建参数
ARG DEBIAN_FRONTEND=noninteractive
                        
# 2026-04-11 12:48:39  0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64:/usr/local/nvidia/lib64
                        
# 2026-04-11 12:48:39  0.00B 设置环境变量 PATH
ENV PATH=/home/ray/anaconda3/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/nvidia/bin
                        
# 2026-04-11 12:48:39  0.00B 设置环境变量 LANG
ENV LANG=C.UTF-8
                        
# 2026-04-11 12:48:39  0.00B 设置环境变量 LC_ALL
ENV LC_ALL=C.UTF-8
                        
# 2026-04-11 12:48:39  0.00B 设置环境变量 TZ
ENV TZ=America/Los_Angeles
                        
# 2023-11-10 13:52:16  2.45GB 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
                        
# 2023-11-10 13:52:16  0.00B 添加元数据标签
LABEL com.nvidia.cudnn.version=8.9.0.131
                        
# 2023-11-10 13:52:16  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2023-11-10 13:52:16  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2023-11-10 13:52:16  0.00B 设置环境变量 NV_CUDNN_PACKAGE_DEV
ENV NV_CUDNN_PACKAGE_DEV=libcudnn8-dev=8.9.0.131-1+cuda12.1
                        
# 2023-11-10 13:52:16  0.00B 设置环境变量 NV_CUDNN_PACKAGE
ENV NV_CUDNN_PACKAGE=libcudnn8=8.9.0.131-1+cuda12.1
                        
# 2023-11-10 13:52:16  0.00B 设置环境变量 NV_CUDNN_PACKAGE_NAME
ENV NV_CUDNN_PACKAGE_NAME=libcudnn8
                        
# 2023-11-10 13:52:16  0.00B 设置环境变量 NV_CUDNN_VERSION
ENV NV_CUDNN_VERSION=8.9.0.131
                        
# 2023-11-10 13:25:51  0.00B 设置环境变量 LIBRARY_PATH
ENV LIBRARY_PATH=/usr/local/cuda/lib64/stubs
                        
# 2023-11-10 13:25:51  385.69KB 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
                        
# 2023-11-10 13:25:51  4.79GB 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-cudart-dev-12-1=${NV_CUDA_CUDART_DEV_VERSION}     cuda-command-line-tools-12-1=${NV_CUDA_LIB_VERSION}     cuda-minimal-build-12-1=${NV_CUDA_LIB_VERSION}     cuda-libraries-dev-12-1=${NV_CUDA_LIB_VERSION}     cuda-nvml-dev-12-1=${NV_NVML_DEV_VERSION}     ${NV_NVPROF_DEV_PACKAGE}     ${NV_LIBNPP_DEV_PACKAGE}     libcusparse-dev-12-1=${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
                        
# 2023-11-10 13:25:51  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2023-11-10 13:25:51  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2023-11-10 13:25:51  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE
ENV NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.17.1-1+cuda12.1
                        
# 2023-11-10 13:25:51  0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.17.1-1
                        
# 2023-11-10 13:25:51  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE_VERSION
ENV NV_LIBNCCL_DEV_PACKAGE_VERSION=2.17.1-1
                        
# 2023-11-10 13:25:51  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE_NAME
ENV NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev
                        
# 2023-11-10 13:25:51  0.00B 设置环境变量 NV_NVPROF_DEV_PACKAGE
ENV NV_NVPROF_DEV_PACKAGE=cuda-nvprof-12-1=12.1.105-1
                        
# 2023-11-10 13:25:51  0.00B 设置环境变量 NV_NVPROF_VERSION
ENV NV_NVPROF_VERSION=12.1.105-1
                        
# 2023-11-10 13:25:51  0.00B 设置环境变量 NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE
ENV NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE=cuda-nsight-compute-12-1=12.1.1-1
                        
# 2023-11-10 13:25:51  0.00B 设置环境变量 NV_CUDA_NSIGHT_COMPUTE_VERSION
ENV NV_CUDA_NSIGHT_COMPUTE_VERSION=12.1.1-1
                        
# 2023-11-10 13:25:51  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_PACKAGE
ENV NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-12-1=12.1.3.1-1
                        
# 2023-11-10 13:25:51  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_PACKAGE_NAME
ENV NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-12-1
                        
# 2023-11-10 13:25:51  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_VERSION
ENV NV_LIBCUBLAS_DEV_VERSION=12.1.3.1-1
                        
# 2023-11-10 13:25:51  0.00B 设置环境变量 NV_LIBNPP_DEV_PACKAGE
ENV NV_LIBNPP_DEV_PACKAGE=libnpp-dev-12-1=12.1.0.40-1
                        
# 2023-11-10 13:25:51  0.00B 设置环境变量 NV_LIBNPP_DEV_VERSION
ENV NV_LIBNPP_DEV_VERSION=12.1.0.40-1
                        
# 2023-11-10 13:25:51  0.00B 设置环境变量 NV_LIBCUSPARSE_DEV_VERSION
ENV NV_LIBCUSPARSE_DEV_VERSION=12.1.0.106-1
                        
# 2023-11-10 13:25:51  0.00B 设置环境变量 NV_NVML_DEV_VERSION
ENV NV_NVML_DEV_VERSION=12.1.105-1
                        
# 2023-11-10 13:25:51  0.00B 设置环境变量 NV_CUDA_CUDART_DEV_VERSION
ENV NV_CUDA_CUDART_DEV_VERSION=12.1.105-1
                        
# 2023-11-10 13:25:51  0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=12.1.1-1
                        
# 2023-11-10 13:13:35  0.00B 配置容器启动时运行的命令
ENTRYPOINT ["/opt/nvidia/nvidia_entrypoint.sh"]
                        
# 2023-11-10 13:13:35  0.00B 设置环境变量 NVIDIA_PRODUCT_NAME
ENV NVIDIA_PRODUCT_NAME=CUDA
                        
# 2023-11-10 13:13:35  2.53KB 复制新文件或目录到容器中
COPY nvidia_entrypoint.sh /opt/nvidia/ # buildkit
                        
# 2023-11-10 13:13:35  3.06KB 复制新文件或目录到容器中
COPY entrypoint.d/ /opt/nvidia/entrypoint.d/ # buildkit
                        
# 2023-11-10 13:13:35  261.40KB 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
                        
# 2023-11-10 13:13:35  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-12-1=${NV_CUDA_LIB_VERSION}     ${NV_LIBNPP_PACKAGE}     cuda-nvtx-12-1=${NV_NVTX_VERSION}     libcusparse-12-1=${NV_LIBCUSPARSE_VERSION}     ${NV_LIBCUBLAS_PACKAGE}     ${NV_LIBNCCL_PACKAGE}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2023-11-10 13:13:35  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2023-11-10 13:13:35  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2023-11-10 13:13:35  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE
ENV NV_LIBNCCL_PACKAGE=libnccl2=2.17.1-1+cuda12.1
                        
# 2023-11-10 13:13:35  0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.17.1-1
                        
# 2023-11-10 13:13:35  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_VERSION
ENV NV_LIBNCCL_PACKAGE_VERSION=2.17.1-1
                        
# 2023-11-10 13:13:35  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_NAME
ENV NV_LIBNCCL_PACKAGE_NAME=libnccl2
                        
# 2023-11-10 13:13:35  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE
ENV NV_LIBCUBLAS_PACKAGE=libcublas-12-1=12.1.3.1-1
                        
# 2023-11-10 13:13:35  0.00B 设置环境变量 NV_LIBCUBLAS_VERSION
ENV NV_LIBCUBLAS_VERSION=12.1.3.1-1
                        
# 2023-11-10 13:13:35  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE_NAME
ENV NV_LIBCUBLAS_PACKAGE_NAME=libcublas-12-1
                        
# 2023-11-10 13:13:35  0.00B 设置环境变量 NV_LIBCUSPARSE_VERSION
ENV NV_LIBCUSPARSE_VERSION=12.1.0.106-1
                        
# 2023-11-10 13:13:35  0.00B 设置环境变量 NV_LIBNPP_PACKAGE
ENV NV_LIBNPP_PACKAGE=libnpp-12-1=12.1.0.40-1
                        
# 2023-11-10 13:13:35  0.00B 设置环境变量 NV_LIBNPP_VERSION
ENV NV_LIBNPP_VERSION=12.1.0.40-1
                        
# 2023-11-10 13:13:35  0.00B 设置环境变量 NV_NVTX_VERSION
ENV NV_NVTX_VERSION=12.1.105-1
                        
# 2023-11-10 13:13:35  0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=12.1.1-1
                        
# 2023-11-10 13:08:12  0.00B 设置环境变量 NVIDIA_DRIVER_CAPABILITIES
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
                        
# 2023-11-10 13:08:12  0.00B 设置环境变量 NVIDIA_VISIBLE_DEVICES
ENV NVIDIA_VISIBLE_DEVICES=all
                        
# 2023-11-10 13:08:12  17.29KB 复制新文件或目录到容器中
COPY NGC-DL-CONTAINER-LICENSE / # buildkit
                        
# 2023-11-10 13:08:12  0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64
                        
# 2023-11-10 13:08:12  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
                        
# 2023-11-10 13:08:12  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
                        
# 2023-11-10 13:08:11  149.59MB 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-12-1=${NV_CUDA_CUDART_VERSION}     ${NV_CUDA_COMPAT_PACKAGE}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2023-11-10 13:07:58  0.00B 设置环境变量 CUDA_VERSION
ENV CUDA_VERSION=12.1.1
                        
# 2023-11-10 13:07:58  10.56MB 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_1.0-1_all.deb &&     dpkg -i cuda-keyring_1.0-1_all.deb &&     apt-get purge --autoremove -y curl     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2023-11-10 13:07:58  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2023-11-10 13:07:58  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2023-11-10 13:07:58  0.00B 设置环境变量 NV_CUDA_COMPAT_PACKAGE
ENV NV_CUDA_COMPAT_PACKAGE=cuda-compat-12-1
                        
# 2023-11-10 13:07:58  0.00B 设置环境变量 NV_CUDA_CUDART_VERSION
ENV NV_CUDA_CUDART_VERSION=12.1.105-1
                        
# 2023-11-10 13:07:58  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
ENV NVIDIA_REQUIRE_CUDA=cuda>=12.1 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 brand=tesla,driver>=525,driver<526 brand=unknown,driver>=525,driver<526 brand=nvidia,driver>=525,driver<526 brand=nvidiartx,driver>=525,driver<526 brand=geforce,driver>=525,driver<526 brand=geforcertx,driver>=525,driver<526 brand=quadro,driver>=525,driver<526 brand=quadrortx,driver>=525,driver<526 brand=titan,driver>=525,driver<526 brand=titanrtx,driver>=525,driver<526
                        
# 2023-11-10 13:07:58  0.00B 设置环境变量 NVARCH
ENV NVARCH=x86_64
                        
# 2023-10-05 15:33:32  0.00B 
/bin/sh -c #(nop)  CMD ["/bin/bash"]
                        
# 2023-10-05 15:33:32  77.82MB 
/bin/sh -c #(nop) ADD file:63d5ab3ef0aab308c0e71cb67292c5467f60deafa9b0418cbb220affcd078444 in / 
                        
# 2023-10-05 15:33:30  0.00B 
/bin/sh -c #(nop)  LABEL org.opencontainers.image.version=22.04
                        
# 2023-10-05 15:33:30  0.00B 
/bin/sh -c #(nop)  LABEL org.opencontainers.image.ref.name=ubuntu
                        
# 2023-10-05 15:33:30  0.00B 
/bin/sh -c #(nop)  ARG LAUNCHPAD_BUILD_ARCH
                        
# 2023-10-05 15:33:30  0.00B 
/bin/sh -c #(nop)  ARG RELEASE

镜像信息

{
    "Id": "sha256:6f8c0fad3bdf4e54d88e83a91eadeaeb7a1e5117a84cee2da4f9e87bb771f65d",
    "RepoTags": [
        "rayproject/ray:2.55.0-py312-gpu",
        "swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/rayproject/ray:2.55.0-py312-gpu"
    ],
    "RepoDigests": [
        "rayproject/ray@sha256:37c69a80c34a926db0bdc600b5d7503b3e0c9b4ef536ca4bb3bfc3b3d8c96428",
        "swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/rayproject/ray@sha256:053e1665d7fc685b832abda2a2821f685e71d8b2151ae653240ae895c3e184df"
    ],
    "Parent": "",
    "Comment": "buildkit.dockerfile.v0",
    "Created": "2026-04-11T05:22:10.940945551Z",
    "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/nvidia/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=12.1 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 brand=tesla,driver\u003e=525,driver\u003c526 brand=unknown,driver\u003e=525,driver\u003c526 brand=nvidia,driver\u003e=525,driver\u003c526 brand=nvidiartx,driver\u003e=525,driver\u003c526 brand=geforce,driver\u003e=525,driver\u003c526 brand=geforcertx,driver\u003e=525,driver\u003c526 brand=quadro,driver\u003e=525,driver\u003c526 brand=quadrortx,driver\u003e=525,driver\u003c526 brand=titan,driver\u003e=525,driver\u003c526 brand=titanrtx,driver\u003e=525,driver\u003c526",
            "NV_CUDA_CUDART_VERSION=12.1.105-1",
            "NV_CUDA_COMPAT_PACKAGE=cuda-compat-12-1",
            "CUDA_VERSION=12.1.1",
            "LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64:/usr/local/nvidia/lib64",
            "NVIDIA_VISIBLE_DEVICES=all",
            "NVIDIA_DRIVER_CAPABILITIES=compute,utility",
            "NV_CUDA_LIB_VERSION=12.1.1-1",
            "NV_NVTX_VERSION=12.1.105-1",
            "NV_LIBNPP_VERSION=12.1.0.40-1",
            "NV_LIBNPP_PACKAGE=libnpp-12-1=12.1.0.40-1",
            "NV_LIBCUSPARSE_VERSION=12.1.0.106-1",
            "NV_LIBCUBLAS_PACKAGE_NAME=libcublas-12-1",
            "NV_LIBCUBLAS_VERSION=12.1.3.1-1",
            "NV_LIBCUBLAS_PACKAGE=libcublas-12-1=12.1.3.1-1",
            "NV_LIBNCCL_PACKAGE_NAME=libnccl2",
            "NV_LIBNCCL_PACKAGE_VERSION=2.17.1-1",
            "NCCL_VERSION=2.17.1-1",
            "NV_LIBNCCL_PACKAGE=libnccl2=2.17.1-1+cuda12.1",
            "NVIDIA_PRODUCT_NAME=CUDA",
            "NV_CUDA_CUDART_DEV_VERSION=12.1.105-1",
            "NV_NVML_DEV_VERSION=12.1.105-1",
            "NV_LIBCUSPARSE_DEV_VERSION=12.1.0.106-1",
            "NV_LIBNPP_DEV_VERSION=12.1.0.40-1",
            "NV_LIBNPP_DEV_PACKAGE=libnpp-dev-12-1=12.1.0.40-1",
            "NV_LIBCUBLAS_DEV_VERSION=12.1.3.1-1",
            "NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-12-1",
            "NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-12-1=12.1.3.1-1",
            "NV_CUDA_NSIGHT_COMPUTE_VERSION=12.1.1-1",
            "NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE=cuda-nsight-compute-12-1=12.1.1-1",
            "NV_NVPROF_VERSION=12.1.105-1",
            "NV_NVPROF_DEV_PACKAGE=cuda-nvprof-12-1=12.1.105-1",
            "NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev",
            "NV_LIBNCCL_DEV_PACKAGE_VERSION=2.17.1-1",
            "NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.17.1-1+cuda12.1",
            "LIBRARY_PATH=/usr/local/cuda/lib64/stubs",
            "NV_CUDNN_VERSION=8.9.0.131",
            "NV_CUDNN_PACKAGE_NAME=libcudnn8",
            "NV_CUDNN_PACKAGE=libcudnn8=8.9.0.131-1+cuda12.1",
            "NV_CUDNN_PACKAGE_DEV=libcudnn8-dev=8.9.0.131-1+cuda12.1",
            "TZ=America/Los_Angeles",
            "LC_ALL=C.UTF-8",
            "LANG=C.UTF-8",
            "HOME=/home/ray"
        ],
        "Cmd": [
            "/bin/bash"
        ],
        "ArgsEscaped": true,
        "Image": "",
        "Volumes": null,
        "WorkingDir": "/home/ray",
        "Entrypoint": [
            "/opt/nvidia/nvidia_entrypoint.sh"
        ],
        "OnBuild": null,
        "Labels": {
            "com.nvidia.cudnn.version": "8.9.0.131",
            "io.ray.ray-commit": "58af3fc5cad7e74001b3f89bffd9052a9e7aa2bb",
            "io.ray.ray-version": "2.55.0",
            "maintainer": "NVIDIA CORPORATION \u003ccudatools@nvidia.com\u003e",
            "org.opencontainers.image.ref.name": "ubuntu",
            "org.opencontainers.image.version": "22.04"
        },
        "Shell": [
            "/bin/bash",
            "-c"
        ]
    },
    "Architecture": "amd64",
    "Os": "linux",
    "Size": 11650510313,
    "GraphDriver": {
        "Data": {
            "LowerDir": "/var/lib/docker/overlay2/9a4893859a133e7c9e0cfaaf507140ee6b4c395f073cdce7058062f9a0a38100/diff:/var/lib/docker/overlay2/0d889c59e1d44921ca008057559b99c4a714541e34d0f6be41ecf9003be636e0/diff:/var/lib/docker/overlay2/ab833b37c6ec7eeba7b80ca6bfc4294acea8cfa99d26c44ea43377b11a5561bf/diff:/var/lib/docker/overlay2/29a4e500fbfbf1722bf24875a7da2bbdb9e3d274085b79fb4e7f904771a1d6a2/diff:/var/lib/docker/overlay2/979b78bd0cb3734d54ba2b072f454815f6a4a376650fd9739df19df859a293ec/diff:/var/lib/docker/overlay2/7a15203a5cf20d4309d27906681acd5a74bd06a1b14a224d2225b5b65f5375ff/diff:/var/lib/docker/overlay2/f0c57777ea5ff23290cb04b5071b0efb5d71935eae495b34e8168808e6ff3252/diff:/var/lib/docker/overlay2/f4d16c20ed7960fd3c7fce52ced86c72278c32c6b00f6d13bcdb18c66a0eaf06/diff:/var/lib/docker/overlay2/6667b970405d6d09728ed2dcabf94a2e52332e31ffbd8657bb822ef56ee33482/diff:/var/lib/docker/overlay2/014421638e7a6e7b4e47cc95b2c7db41adbf3577d093353bc5e40db413586366/diff:/var/lib/docker/overlay2/7380c8fb7f04d38f7cac58efa5f902162374c97acf4a422c1946071f440ced8c/diff:/var/lib/docker/overlay2/4a6354f2a1ad5386b72a8f6dbc672b80c727ce4c2c1e2fbc0f6d7c2bc17fe353/diff:/var/lib/docker/overlay2/a04e84abb15db04e71160a1839949b7eca74d4a8e364e7e59c432ac80500ae25/diff:/var/lib/docker/overlay2/66d9cfcb87ceb9e0f7bc0a941c2f7570322d653076a19c90233b40410d5b9ed3/diff:/var/lib/docker/overlay2/32fcdc9e79b2ee9c883ffe40d3fd5f6fd8fe5c1fef39e5bd2f56e00d6a459660/diff:/var/lib/docker/overlay2/66c2e99991fd8d4db184b5c96d3ef291dc387620af9215047bf6b33dbe8f1da8/diff:/var/lib/docker/overlay2/4a4bd69653f9cf2dd77e2e6eedd02499075e684f274c706e1ecb5acd44cc6b02/diff:/var/lib/docker/overlay2/8c846210766e2b81057f11a92212184a95c1da4ee877cb30824070f29d2da94e/diff:/var/lib/docker/overlay2/f84cf31bd574c1d03fff1ed8b18ba8de5f23ecfbf0afd4046b10ac286598884f/diff:/var/lib/docker/overlay2/b8ae3ae22cafcecbf540633c0588b79f3f9eb98cc2315516ec73b71fffa6040a/diff",
            "MergedDir": "/var/lib/docker/overlay2/051a8b4c8a344571fca36eb58051516d88903c17dedbf44228d5fdf0fe53e158/merged",
            "UpperDir": "/var/lib/docker/overlay2/051a8b4c8a344571fca36eb58051516d88903c17dedbf44228d5fdf0fe53e158/diff",
            "WorkDir": "/var/lib/docker/overlay2/051a8b4c8a344571fca36eb58051516d88903c17dedbf44228d5fdf0fe53e158/work"
        },
        "Name": "overlay2"
    },
    "RootFS": {
        "Type": "layers",
        "Layers": [
            "sha256:256d88da41857db513b95b50ba9a9b28491b58c954e25477d5dad8abb465430b",
            "sha256:566cd9dd29d693cf0360da8a73391b843bb6ac8f11b4148acf69c4dc79fa87c5",
            "sha256:6ec2b659c9ab00e2b0fc0acd056577e609cc28649650ec7068b81686f6d1a996",
            "sha256:8afeff4e91d72f3de9232ffc0803f70236e316c27b23ee003e6d47fbfcb6e1c4",
            "sha256:bea30ebbe84377ed36503599c2087cd6bda6f4c96cb59525d238d4a00cf902d3",
            "sha256:b15b1df4adac82b2b46124c743a32d5e982cb6b5ee8a3c04949f809abf8962c9",
            "sha256:83ecbf43a888c43f43b0cd9ec7cf551770790c7aeab17f9536b8820db2c5d45d",
            "sha256:83687aeafbbf74a164a51590ffa36c46e9c41ce4ba3eae9daba1d381c64e5f4b",
            "sha256:3416903c2cc4c9f83472b397741f30365f53543862b03ff5727b42b1a2f938cb",
            "sha256:24e1e08aaa60ea10f478c1b68d9444b8ea74bff76e2547712984b5136e79018e",
            "sha256:7aee75a70a2ff35d4990fab501a025afa498f416cb726ace747ccd7fad6500d4",
            "sha256:0f7c883f1a4f4710753cfa1185d8e60584e41f04fe1693bd8c3ee6700b29c7f3",
            "sha256:e3da1d60e142bd1bd685cba9403bec6b5211ed3371ed08ecfc4b71d3855842ed",
            "sha256:5ba37f9b34a38a148507ec2803dd7599c883219e90e283c139f2d9392c8f1288",
            "sha256:5f70bf18a086007016e948b04aed3b82103a36bea41755b6cddfaf10ace3c6ef",
            "sha256:8ea233f547c94e6b4fcaff71e80f849c3648f34cf4f6542e452387000bac8120",
            "sha256:003a29152dc2efa84d688330af4f57886c2cac13138a2bda3fb2f128f83b4e77",
            "sha256:dfbca6ef2a2c9928fb156193ff887d9a76c5bd329b8a7c486b675b855f26ee65",
            "sha256:5f70bf18a086007016e948b04aed3b82103a36bea41755b6cddfaf10ace3c6ef",
            "sha256:38e519d5181cd010b7e346ce8c8d4908c1f3ea9bbd585b53881c3b88557543f9",
            "sha256:a60200931feb955de17c6adb19783f6d3fe88469d3b11e804cf49b9374f71e2f"
        ]
    },
    "Metadata": {
        "LastTagTime": "2026-07-23T01:25:22.555651978+08:00"
    }
}

更多版本

docker.io/rayproject/ray:2.9.0

linux/amd64 docker.io2.20GB2024-07-17 10:33

1744

docker.io/rayproject/ray-ml:2.30.0-py310-gpu

linux/amd64 docker.io21.88GB2024-09-27 00:30

960

docker.io/rayproject/ray:nightly-gpu

linux/amd64 docker.io11.57GB2024-11-21 02:01