docker.io/rayproject/ray:2.50.1-py312-cpu linux/amd64

docker.io/rayproject/ray:2.50.1-py312-cpu - 国内下载镜像源 浏览次数:21
_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:2.50.1-py312-cpu
国内镜像 swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/rayproject/ray:2.50.1-py312-cpu
镜像ID sha256:8493acfc7fddf4f17915929f254f2b6e979d7116d08924cb1d384349b2c5fa4d
镜像TAG 2.50.1-py312-cpu
大小 2.18GB
镜像源 docker.io
项目信息 Docker-Hub主页 🚀项目TAG 🚀
CMD /bin/bash
启动入口
工作目录 /home/ray
OS/平台 linux/amd64
浏览量 21 次
贡献者 fr*******r@163.com
镜像创建 2025-10-16T04:02:23.05746111Z
同步时间 2025-10-21 15:22
更新时间 2025-10-22 10:28
环境变量
PATH=/home/ray/anaconda3/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/nvidia/bin TZ=America/Los_Angeles LC_ALL=C.UTF-8 LANG=C.UTF-8 LD_LIBRARY_PATH=:/usr/local/nvidia/lib64 HOME=/home/ray
镜像标签
7cf6817996f5304b5c808453a997fc1570dcde25: io.ray.ray-commit 2.50.1: io.ray.ray-version ubuntu: org.opencontainers.image.ref.name 22.04: org.opencontainers.image.version

Docker拉取命令

docker pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/rayproject/ray:2.50.1-py312-cpu
docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/rayproject/ray:2.50.1-py312-cpu  docker.io/rayproject/ray:2.50.1-py312-cpu

Containerd拉取命令

ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/rayproject/ray:2.50.1-py312-cpu
ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/rayproject/ray:2.50.1-py312-cpu  docker.io/rayproject/ray:2.50.1-py312-cpu

Shell快速替换命令

sed -i 's#rayproject/ray:2.50.1-py312-cpu#swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/rayproject/ray:2.50.1-py312-cpu#' 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:2.50.1-py312-cpu && docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/rayproject/ray:2.50.1-py312-cpu  docker.io/rayproject/ray:2.50.1-py312-cpu'

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:2.50.1-py312-cpu && ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/rayproject/ray:2.50.1-py312-cpu  docker.io/rayproject/ray:2.50.1-py312-cpu'

镜像构建历史


# 2025-10-16 12:02:23  19.60KB 执行命令并创建新的镜像层
RUN |3 WHEEL_PATH=.whl/ray-2.50.1-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
                        
# 2025-10-16 12:02:22  878.13MB 执行命令并创建新的镜像层
RUN |3 WHEEL_PATH=.whl/ray-2.50.1-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
                        
# 2025-10-16 12:01:44  86.12MB 复制新文件或目录到容器中
COPY .whl .whl # buildkit
                        
# 2025-10-16 12:01:43  71.13MB 复制新文件或目录到容器中
COPY .whl/ray-2.50.1-cp312-cp312-manylinux2014_x86_64.whl . # buildkit
                        
# 2025-10-16 12:01:43  0.00B 定义构建参数
ARG CONSTRAINTS_FILE=requirements_compiled.txt
                        
# 2025-10-16 12:01:43  0.00B 定义构建参数
ARG FIND_LINKS_PATH=.whl
                        
# 2025-10-16 12:01:43  0.00B 定义构建参数
ARG WHEEL_PATH
                        
# 2025-10-12 17:26:51  0.00B 设置工作目录为/home/ray
WORKDIR /home/ray
                        
# 2025-10-12 17:26:51  618.72MB 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/bash -c /dev/pipes/EOF # buildkit
                        
# 2025-10-12 17:26:07  0.00B 
SHELL [/bin/bash -c]
                        
# 2025-10-12 17:26:07  61.27KB 复制新文件或目录到容器中
COPY python/requirements_compiled.txt /home/ray/requirements_compiled.txt # buildkit
                        
# 2025-10-12 17:26:07  0.00B 设置环境变量 HOME
ENV HOME=/home/ray
                        
# 2025-10-12 17:26:07  0.00B 指定运行容器时使用的用户
USER 1000
                        
# 2025-10-12 17:26:07  445.06MB 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
                        
# 2025-10-12 17:26:07  0.00B 定义构建参数
ARG RAY_GID=100
                        
# 2025-10-12 17:26:07  0.00B 定义构建参数
ARG RAY_UID=1000
                        
# 2025-10-12 17:26:07  0.00B 定义构建参数
ARG PYTHON_VERSION=3.9
                        
# 2025-10-12 17:26:07  0.00B 定义构建参数
ARG DEBIAN_FRONTEND=noninteractive
                        
# 2025-10-12 17:26:07  0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=:/usr/local/nvidia/lib64
                        
# 2025-10-12 17:26:07  0.00B 设置环境变量 PATH
ENV PATH=/home/ray/anaconda3/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/nvidia/bin
                        
# 2025-10-12 17:26:07  0.00B 设置环境变量 LANG
ENV LANG=C.UTF-8
                        
# 2025-10-12 17:26:07  0.00B 设置环境变量 LC_ALL
ENV LC_ALL=C.UTF-8
                        
# 2025-10-12 17:26:07  0.00B 设置环境变量 TZ
ENV TZ=America/Los_Angeles
                        
# 2025-10-01 15:05:10  0.00B 
/bin/sh -c #(nop)  CMD ["/bin/bash"]
                        
# 2025-10-01 15:05:09  77.87MB 
/bin/sh -c #(nop) ADD file:32d41b6329e8f89fa4ac92ef97c04b7cfd5e90fb74e1509c3e27d7c91195b7c7 in / 
                        
# 2025-10-01 15:05:07  0.00B 
/bin/sh -c #(nop)  LABEL org.opencontainers.image.version=22.04
                        
# 2025-10-01 15:05:07  0.00B 
/bin/sh -c #(nop)  LABEL org.opencontainers.image.ref.name=ubuntu
                        
# 2025-10-01 15:05:07  0.00B 
/bin/sh -c #(nop)  ARG LAUNCHPAD_BUILD_ARCH
                        
# 2025-10-01 15:05:07  0.00B 
/bin/sh -c #(nop)  ARG RELEASE
                        
                    

镜像信息

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更多版本

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docker.io/rayproject/ray:2.46.0

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

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docker.io/rayproject/ray:2.46.0-py39-cpu

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linux/amd64 docker.io11.38GB2025-10-04 00:39
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docker.io/rayproject/ray:2.50.1-py312-cpu

linux/amd64 docker.io2.18GB2025-10-21 15:22
20

docker.io/rayproject/ray:2.50.1-py312-cu128

linux/amd64 docker.io12.52GB2025-10-22 01:01
10