docker.io/rayproject/ray:nightly-gpu linux/amd64

docker.io/rayproject/ray:nightly-gpu - 国内下载镜像源 浏览次数:11
_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。
源镜像 docker.io/rayproject/ray:nightly-gpu
国内镜像 swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/rayproject/ray:nightly-gpu
镜像ID sha256:2d8d39e0243c8653ff81f921bbcb089c695e41044957b314ddc5531ab7b35972
镜像TAG nightly-gpu
大小 11.57GB
镜像源 docker.io
项目信息 Docker-Hub主页 🚀项目TAG 🚀
CMD
启动入口 /opt/nvidia/nvidia_entrypoint.sh
工作目录 /home/ray
OS/平台 linux/amd64
浏览量 11 次
贡献者
镜像创建 2024-11-20T06:29:58.263078015Z
同步时间 2024-11-21 02:01
更新时间 2024-11-21 13:41
环境变量
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 NVARCH=x86_64 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 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 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
镜像标签
8.9.0.131: com.nvidia.cudnn.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 查看Trivy扫描报告

系统OS: ubuntu 22.04 扫描引擎: Trivy 扫描时间: 2024-11-21 02:05

低危漏洞:142 中危漏洞:657 高危漏洞:2 严重漏洞:0

Docker拉取命令 无权限下载?点我修复

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

Containerd拉取命令

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

Shell快速替换命令

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

镜像历史

大小 创建时间 层信息
3.67KB 2024-11-20 14:29:58 RUN |3 WHEEL_PATH=.whl/ray-3.0.0.dev0-cp39-cp39-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
862.12MB 2024-11-20 14:29:57 RUN |3 WHEEL_PATH=.whl/ray-3.0.0.dev0-cp39-cp39-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
95.30MB 2024-11-20 14:29:11 COPY .whl .whl # buildkit
66.83MB 2024-11-20 14:29:10 COPY .whl/ray-3.0.0.dev0-cp39-cp39-manylinux2014_x86_64.whl . # buildkit
0.00B 2024-11-20 14:29:10 ARG CONSTRAINTS_FILE=requirements_compiled.txt
0.00B 2024-11-20 14:29:10 ARG FIND_LINKS_PATH=.whl
0.00B 2024-11-20 14:29:10 ARG WHEEL_PATH
0.00B 2024-11-20 01:20:58 WORKDIR /home/ray
747.07MB 2024-11-20 01:20:58 RUN |7 BASE_IMAGE=nvidia/cuda:12.1.1-cudnn8-devel-ubuntu22.04 AUTOSCALER=autoscaler DEBIAN_FRONTEND=noninteractive PYTHON_VERSION=3.9 HOSTTYPE=x86_64 RAY_UID=1000 RAY_GID=100 /bin/bash -c /dev/pipes/EOF # buildkit
0.00B 2024-11-20 01:20:03 SHELL [/bin/bash -c]
59.55KB 2024-11-20 01:20:03 COPY python/requirements_compiled.txt /home/ray/requirements_compiled.txt # buildkit
0.00B 2024-11-20 01:20:03 ENV HOME=/home/ray
0.00B 2024-11-20 01:20:03 USER 1000
306.76MB 2024-11-20 01:20:03 RUN |7 BASE_IMAGE=nvidia/cuda:12.1.1-cudnn8-devel-ubuntu22.04 AUTOSCALER=autoscaler DEBIAN_FRONTEND=noninteractive PYTHON_VERSION=3.9 HOSTTYPE=x86_64 RAY_UID=1000 RAY_GID=100 /bin/sh -c /dev/pipes/EOF # buildkit
0.00B 2024-11-20 01:20:03 ARG RAY_GID=100
0.00B 2024-11-20 01:20:03 ARG RAY_UID=1000
0.00B 2024-11-20 01:20:03 ARG HOSTTYPE=x86_64
0.00B 2024-11-20 01:20:03 ARG PYTHON_VERSION=3.9
0.00B 2024-11-20 01:20:03 ARG DEBIAN_FRONTEND=noninteractive
0.00B 2024-11-20 01:20:03 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
0.00B 2024-11-20 01:20:03 ENV LANG=C.UTF-8
0.00B 2024-11-20 01:20:03 ENV LC_ALL=C.UTF-8
0.00B 2024-11-20 01:20:03 ENV TZ=America/Los_Angeles
0.00B 2024-11-20 01:20:03 ARG AUTOSCALER=autoscaler
0.00B 2024-11-20 01:20:03 ARG BASE_IMAGE
2.45GB 2023-11-10 13:52:16 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
0.00B 2023-11-10 13:52:16 LABEL com.nvidia.cudnn.version=8.9.0.131
0.00B 2023-11-10 13:52:16 LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
0.00B 2023-11-10 13:52:16 ARG TARGETARCH
0.00B 2023-11-10 13:52:16 ENV NV_CUDNN_PACKAGE_DEV=libcudnn8-dev=8.9.0.131-1+cuda12.1
0.00B 2023-11-10 13:52:16 ENV NV_CUDNN_PACKAGE=libcudnn8=8.9.0.131-1+cuda12.1
0.00B 2023-11-10 13:52:16 ENV NV_CUDNN_PACKAGE_NAME=libcudnn8
0.00B 2023-11-10 13:52:16 ENV NV_CUDNN_VERSION=8.9.0.131
0.00B 2023-11-10 13:25:51 ENV LIBRARY_PATH=/usr/local/cuda/lib64/stubs
385.69KB 2023-11-10 13:25:51 RUN |1 TARGETARCH=amd64 /bin/sh -c apt-mark hold ${NV_LIBCUBLAS_DEV_PACKAGE_NAME} ${NV_LIBNCCL_DEV_PACKAGE_NAME} # buildkit
4.79GB 2023-11-10 13:25:51 RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends cuda-cudart-dev-12-1=${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
0.00B 2023-11-10 13:25:51 LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
0.00B 2023-11-10 13:25:51 ARG TARGETARCH
0.00B 2023-11-10 13:25:51 ENV NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.17.1-1+cuda12.1
0.00B 2023-11-10 13:25:51 ENV NCCL_VERSION=2.17.1-1
0.00B 2023-11-10 13:25:51 ENV NV_LIBNCCL_DEV_PACKAGE_VERSION=2.17.1-1
0.00B 2023-11-10 13:25:51 ENV NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev
0.00B 2023-11-10 13:25:51 ENV NV_NVPROF_DEV_PACKAGE=cuda-nvprof-12-1=12.1.105-1
0.00B 2023-11-10 13:25:51 ENV NV_NVPROF_VERSION=12.1.105-1
0.00B 2023-11-10 13:25:51 ENV NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE=cuda-nsight-compute-12-1=12.1.1-1
0.00B 2023-11-10 13:25:51 ENV NV_CUDA_NSIGHT_COMPUTE_VERSION=12.1.1-1
0.00B 2023-11-10 13:25:51 ENV NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-12-1=12.1.3.1-1
0.00B 2023-11-10 13:25:51 ENV NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-12-1
0.00B 2023-11-10 13:25:51 ENV NV_LIBCUBLAS_DEV_VERSION=12.1.3.1-1
0.00B 2023-11-10 13:25:51 ENV NV_LIBNPP_DEV_PACKAGE=libnpp-dev-12-1=12.1.0.40-1
0.00B 2023-11-10 13:25:51 ENV NV_LIBNPP_DEV_VERSION=12.1.0.40-1
0.00B 2023-11-10 13:25:51 ENV NV_LIBCUSPARSE_DEV_VERSION=12.1.0.106-1
0.00B 2023-11-10 13:25:51 ENV NV_NVML_DEV_VERSION=12.1.105-1
0.00B 2023-11-10 13:25:51 ENV NV_CUDA_CUDART_DEV_VERSION=12.1.105-1
0.00B 2023-11-10 13:25:51 ENV NV_CUDA_LIB_VERSION=12.1.1-1
0.00B 2023-11-10 13:13:35 ENTRYPOINT ["/opt/nvidia/nvidia_entrypoint.sh"]
0.00B 2023-11-10 13:13:35 ENV NVIDIA_PRODUCT_NAME=CUDA
2.53KB 2023-11-10 13:13:35 COPY nvidia_entrypoint.sh /opt/nvidia/ # buildkit
3.06KB 2023-11-10 13:13:35 COPY entrypoint.d/ /opt/nvidia/entrypoint.d/ # buildkit
261.40KB 2023-11-10 13:13:35 RUN |1 TARGETARCH=amd64 /bin/sh -c apt-mark hold ${NV_LIBCUBLAS_PACKAGE_NAME} ${NV_LIBNCCL_PACKAGE_NAME} # buildkit
2.01GB 2023-11-10 13:13:35 RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends cuda-libraries-12-1=${NV_CUDA_LIB_VERSION} ${NV_LIBNPP_PACKAGE} cuda-nvtx-12-1=${NV_NVTX_VERSION} libcusparse-12-1=${NV_LIBCUSPARSE_VERSION} ${NV_LIBCUBLAS_PACKAGE} ${NV_LIBNCCL_PACKAGE} && rm -rf /var/lib/apt/lists/* # buildkit
0.00B 2023-11-10 13:13:35 LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
0.00B 2023-11-10 13:13:35 ARG TARGETARCH
0.00B 2023-11-10 13:13:35 ENV NV_LIBNCCL_PACKAGE=libnccl2=2.17.1-1+cuda12.1
0.00B 2023-11-10 13:13:35 ENV NCCL_VERSION=2.17.1-1
0.00B 2023-11-10 13:13:35 ENV NV_LIBNCCL_PACKAGE_VERSION=2.17.1-1
0.00B 2023-11-10 13:13:35 ENV NV_LIBNCCL_PACKAGE_NAME=libnccl2
0.00B 2023-11-10 13:13:35 ENV NV_LIBCUBLAS_PACKAGE=libcublas-12-1=12.1.3.1-1
0.00B 2023-11-10 13:13:35 ENV NV_LIBCUBLAS_VERSION=12.1.3.1-1
0.00B 2023-11-10 13:13:35 ENV NV_LIBCUBLAS_PACKAGE_NAME=libcublas-12-1
0.00B 2023-11-10 13:13:35 ENV NV_LIBCUSPARSE_VERSION=12.1.0.106-1
0.00B 2023-11-10 13:13:35 ENV NV_LIBNPP_PACKAGE=libnpp-12-1=12.1.0.40-1
0.00B 2023-11-10 13:13:35 ENV NV_LIBNPP_VERSION=12.1.0.40-1
0.00B 2023-11-10 13:13:35 ENV NV_NVTX_VERSION=12.1.105-1
0.00B 2023-11-10 13:13:35 ENV NV_CUDA_LIB_VERSION=12.1.1-1
0.00B 2023-11-10 13:08:12 ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
0.00B 2023-11-10 13:08:12 ENV NVIDIA_VISIBLE_DEVICES=all
17.29KB 2023-11-10 13:08:12 COPY NGC-DL-CONTAINER-LICENSE / # buildkit
0.00B 2023-11-10 13:08:12 ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64
0.00B 2023-11-10 13:08:12 ENV PATH=/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
46.00B 2023-11-10 13:08:12 RUN |1 TARGETARCH=amd64 /bin/sh -c echo "/usr/local/nvidia/lib" >> /etc/ld.so.conf.d/nvidia.conf && echo "/usr/local/nvidia/lib64" >> /etc/ld.so.conf.d/nvidia.conf # buildkit
149.59MB 2023-11-10 13:08:11 RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends cuda-cudart-12-1=${NV_CUDA_CUDART_VERSION} ${NV_CUDA_COMPAT_PACKAGE} && rm -rf /var/lib/apt/lists/* # buildkit
0.00B 2023-11-10 13:07:58 ENV CUDA_VERSION=12.1.1
10.56MB 2023-11-10 13:07:58 RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends gnupg2 curl ca-certificates && curl -fsSLO https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/${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
0.00B 2023-11-10 13:07:58 LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
0.00B 2023-11-10 13:07:58 ARG TARGETARCH
0.00B 2023-11-10 13:07:58 ENV NV_CUDA_COMPAT_PACKAGE=cuda-compat-12-1
0.00B 2023-11-10 13:07:58 ENV NV_CUDA_CUDART_VERSION=12.1.105-1
0.00B 2023-11-10 13:07:58 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
0.00B 2023-11-10 13:07:58 ENV NVARCH=x86_64
0.00B 2023-10-05 15:33:32 /bin/sh -c #(nop) CMD ["/bin/bash"]
77.82MB 2023-10-05 15:33:32 /bin/sh -c #(nop) ADD file:63d5ab3ef0aab308c0e71cb67292c5467f60deafa9b0418cbb220affcd078444 in /
0.00B 2023-10-05 15:33:30 /bin/sh -c #(nop) LABEL org.opencontainers.image.version=22.04
0.00B 2023-10-05 15:33:30 /bin/sh -c #(nop) LABEL org.opencontainers.image.ref.name=ubuntu
0.00B 2023-10-05 15:33:30 /bin/sh -c #(nop) ARG LAUNCHPAD_BUILD_ARCH
0.00B 2023-10-05 15:33:30 /bin/sh -c #(nop) ARG RELEASE

镜像信息

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    "Id": "sha256:2d8d39e0243c8653ff81f921bbcb089c695e41044957b314ddc5531ab7b35972",
    "RepoTags": [
        "rayproject/ray:nightly-gpu",
        "swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/rayproject/ray:nightly-gpu"
    ],
    "RepoDigests": [
        "rayproject/ray@sha256:5254b21ee9b9f36929785f01f5e16169c6fdaff5662606dfb50791f3d4c130f2",
        "swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/rayproject/ray@sha256:5254b21ee9b9f36929785f01f5e16169c6fdaff5662606dfb50791f3d4c130f2"
    ],
    "Parent": "",
    "Comment": "buildkit.dockerfile.v0",
    "Created": "2024-11-20T06:29:58.263078015Z",
    "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",
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}

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