docker.io/tensorflow/tensorflow:latest-gpu-jupyter linux/amd64

docker.io/tensorflow/tensorflow:latest-gpu-jupyter - 国内下载镜像源浏览次数:60

TensorFlow Docker 镜像

这是一个由 Google 维护的 Docker 镜像，包含 TensorFlow 框架，用于机器学习和深度学习。它提供了一个预先配置的环境，可以轻松地运行 TensorFlow 代码，并包含必要的依赖项和库。

该镜像提供多种版本的 TensorFlow，以及其他工具和库，例如 CUDA 和 cuDNN，用于 GPU 加速。

使用该镜像，您可以快速启动一个 TensorFlow 环境，无需手动安装所有必要的依赖项。它适用于开发、测试和部署 TensorFlow 模型。

您可以通过以下命令拉取该镜像：

docker pull docker.io/tensorflow/tensorflow

源镜像	docker.io/tensorflow/tensorflow:latest-gpu-jupyter
国内镜像	swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/tensorflow/tensorflow:latest-gpu-jupyter
镜像ID	sha256:29afa62f886808e8f3a6bb4e67297c51e4c1f8aed5420deff25553a1e5482f89
镜像TAG	latest-gpu-jupyter
大小	7.87GB
镜像源	docker.io
项目信息	Docker-Hub主页 🚀项目TAG 🚀
CMD	bash -c source /etc/bash.bashrc && jupyter notebook --notebook-dir=/tf --ip 0.0.0.0 --no-browser --allow-root
启动入口
工作目录	/tf
OS/平台	linux/amd64
浏览量	60 次
贡献者	28*******5@qq.com
镜像创建	2025-03-12T04:00:54.628599582Z
同步时间	2025-04-29 01:19
更新时间	2025-05-22 15:52

开放端口

8888/tcp

环境变量

PATH=/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>=12.3 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 brand=tesla,driver>=535,driver<536 brand=unknown,driver>=535,driver<536 brand=nvidia,driver>=535,driver<536 brand=nvidiartx,driver>=535,driver<536 brand=geforce,driver>=535,driver<536 brand=geforcertx,driver>=535,driver<536 brand=quadro,driver>=535,driver<536 brand=quadrortx,driver>=535,driver<536 brand=titan,driver>=535,driver<536 brand=titanrtx,driver>=535,driver<536 NV_CUDA_CUDART_VERSION=12.3.52-1 NV_CUDA_COMPAT_PACKAGE=cuda-compat-12-3 CUDA_VERSION=12.3.0 LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64 NVIDIA_VISIBLE_DEVICES=all NVIDIA_DRIVER_CAPABILITIES=compute,utility DEBIAN_FRONTEND=noninteractive LANG=C.UTF-8

镜像标签

NVIDIA CORPORATION <cudatools@nvidia.com>: maintainer ubuntu: org.opencontainers.image.ref.name 22.04: org.opencontainers.image.version

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无权限下载?点我修复生成Docker Run命令

Docker拉取命令

docker pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/tensorflow/tensorflow:latest-gpu-jupyter
docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/tensorflow/tensorflow:latest-gpu-jupyter  docker.io/tensorflow/tensorflow:latest-gpu-jupyter

Containerd拉取命令

ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/tensorflow/tensorflow:latest-gpu-jupyter
ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/tensorflow/tensorflow:latest-gpu-jupyter  docker.io/tensorflow/tensorflow:latest-gpu-jupyter

Shell快速替换命令

sed -i 's#tensorflow/tensorflow:latest-gpu-jupyter#swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/tensorflow/tensorflow:latest-gpu-jupyter#' 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/tensorflow/tensorflow:latest-gpu-jupyter && docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/tensorflow/tensorflow:latest-gpu-jupyter  docker.io/tensorflow/tensorflow:latest-gpu-jupyter'

Ansible快速分发-Containerd

#ansible k8s -m shell -a 'ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/tensorflow/tensorflow:latest-gpu-jupyter && ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/tensorflow/tensorflow:latest-gpu-jupyter  docker.io/tensorflow/tensorflow:latest-gpu-jupyter'

镜像构建历史


# 2025-03-12 12:00:54  0.00B 设置默认要执行的命令
CMD ["bash" "-c" "source /etc/bash.bashrc && jupyter notebook --notebook-dir=/tf --ip 0.0.0.0 --no-browser --allow-root"]
                        
# 2025-03-12 12:00:54  0.00B 声明容器运行时监听的端口
EXPOSE map[8888/tcp:{}]
                        
# 2025-03-12 12:00:54  0.00B 设置工作目录为/tf
WORKDIR /tf
                        
# 2025-03-12 12:00:54  69.00B 复制新文件或目录到容器中
COPY jupyter.readme.md /tf/tensorflow-tutorials/README.md # buildkit
                        
# 2025-03-12 12:00:54  78.62MB 执行命令并创建新的镜像层
RUN |2 PYTHON_VERSION=python3.11 TENSORFLOW_PACKAGE=tensorflow==2.19.0 /bin/sh -c /setup.jupyter.sh # buildkit
                        
# 2025-03-12 12:00:44  293.98MB 执行命令并创建新的镜像层
RUN |2 PYTHON_VERSION=python3.11 TENSORFLOW_PACKAGE=tensorflow==2.19.0 /bin/sh -c python3 -m pip install --no-cache-dir -r /jupyter.requirements.txt -U # buildkit
                        
# 2025-03-12 12:00:27  994.00B 复制新文件或目录到容器中
COPY setup.jupyter.sh /setup.jupyter.sh # buildkit
                        
# 2025-03-12 12:00:27  40.00B 复制新文件或目录到容器中
COPY jupyter.requirements.txt /jupyter.requirements.txt # buildkit
                        
# 2025-03-12 11:59:38  1.92KB 执行命令并创建新的镜像层
RUN |2 PYTHON_VERSION=python3.11 TENSORFLOW_PACKAGE=tensorflow==2.19.0 /bin/sh -c chmod a+rwx /etc/bash.bashrc # buildkit
                        
# 2025-03-12 11:59:38  1.92KB 复制新文件或目录到容器中
COPY bashrc /etc/bash.bashrc # buildkit
                        
# 2025-03-12 11:59:38  29.81KB 执行命令并创建新的镜像层
RUN |2 PYTHON_VERSION=python3.11 TENSORFLOW_PACKAGE=tensorflow==2.19.0 /bin/sh -c /setup.cuda.sh # buildkit
                        
# 2025-03-12 11:59:37  1.31KB 复制新文件或目录到容器中
COPY setup.cuda.sh /setup.cuda.sh # buildkit
                        
# 2025-03-12 11:59:37  2.09GB 执行命令并创建新的镜像层
RUN |2 PYTHON_VERSION=python3.11 TENSORFLOW_PACKAGE=tensorflow==2.19.0 /bin/sh -c pip install --no-cache-dir ${TENSORFLOW_PACKAGE} # buildkit
                        
# 2025-03-12 11:59:01  104.93MB 执行命令并创建新的镜像层
RUN |2 PYTHON_VERSION=python3.11 TENSORFLOW_PACKAGE=tensorflow==2.19.0 /bin/sh -c /setup.python.sh $PYTHON_VERSION /gpu.requirements.txt # buildkit
                        
# 2025-03-12 11:54:15  11.00B 复制新文件或目录到容器中
COPY gpu.requirements.txt /gpu.requirements.txt # buildkit
                        
# 2025-03-12 11:54:15  1.79KB 复制新文件或目录到容器中
COPY setup.python.sh /setup.python.sh # buildkit
                        
# 2025-03-12 11:54:15  0.00B 定义构建参数
ARG TENSORFLOW_PACKAGE=tensorflow==2.19.0
                        
# 2025-03-12 11:54:15  0.00B 定义构建参数
ARG PYTHON_VERSION=python3.11
                        
# 2025-03-12 11:54:15  4.86GB 执行命令并创建新的镜像层
RUN /bin/sh -c /setup.packages.sh /gpu.packages.txt # buildkit
                        
# 2025-03-12 11:50:46  186.11MB 执行命令并创建新的镜像层
RUN /bin/sh -c /setup.sources.sh # buildkit
                        
# 2025-03-12 11:50:13  527.00B 复制新文件或目录到容器中
COPY gpu.packages.txt /gpu.packages.txt # buildkit
                        
# 2025-03-12 11:50:13  1.18KB 复制新文件或目录到容器中
COPY setup.packages.sh /setup.packages.sh # buildkit
                        
# 2025-03-12 11:50:13  1.53KB 复制新文件或目录到容器中
COPY setup.sources.sh /setup.sources.sh # buildkit
                        
# 2025-03-12 11:50:13  0.00B 设置环境变量 LANG
ENV LANG=C.UTF-8
                        
# 2025-03-12 11:50:13  0.00B 设置环境变量 DEBIAN_FRONTEND
ENV DEBIAN_FRONTEND=noninteractive
                        
# 2023-11-09 10:19:48  0.00B 设置环境变量 NVIDIA_DRIVER_CAPABILITIES
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
                        
# 2023-11-09 10:19:48  0.00B 设置环境变量 NVIDIA_VISIBLE_DEVICES
ENV NVIDIA_VISIBLE_DEVICES=all
                        
# 2023-11-09 10:19:48  17.29KB 复制新文件或目录到容器中
COPY NGC-DL-CONTAINER-LICENSE / # buildkit
                        
# 2023-11-09 10:19:48  0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64
                        
# 2023-11-09 10:19:48  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
                        
# 2023-11-09 10:19:48  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
                        
# 2023-11-09 10:19:48  154.88MB 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-12-3=${NV_CUDA_CUDART_VERSION}     ${NV_CUDA_COMPAT_PACKAGE}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2023-11-09 10:19:39  0.00B 设置环境变量 CUDA_VERSION
ENV CUDA_VERSION=12.3.0
                        
# 2023-11-09 10:19:39  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
                        
# 2023-11-09 10:19:39  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2023-11-09 10:19:39  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2023-11-09 10:19:39  0.00B 设置环境变量 NV_CUDA_COMPAT_PACKAGE
ENV NV_CUDA_COMPAT_PACKAGE=cuda-compat-12-3
                        
# 2023-11-09 10:19:39  0.00B 设置环境变量 NV_CUDA_CUDART_VERSION
ENV NV_CUDA_CUDART_VERSION=12.3.52-1
                        
# 2023-11-09 10:19:39  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
ENV NVIDIA_REQUIRE_CUDA=cuda>=12.3 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 brand=tesla,driver>=535,driver<536 brand=unknown,driver>=535,driver<536 brand=nvidia,driver>=535,driver<536 brand=nvidiartx,driver>=535,driver<536 brand=geforce,driver>=535,driver<536 brand=geforcertx,driver>=535,driver<536 brand=quadro,driver>=535,driver<536 brand=quadrortx,driver>=535,driver<536 brand=titan,driver>=535,driver<536 brand=titanrtx,driver>=535,driver<536
                        
# 2023-11-09 10:19:39  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": "sha256:29afa62f886808e8f3a6bb4e67297c51e4c1f8aed5420deff25553a1e5482f89",
    "RepoTags": [
        "tensorflow/tensorflow:latest-gpu-jupyter",
        "swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/tensorflow/tensorflow:latest-gpu-jupyter"
    ],
    "RepoDigests": [
        "tensorflow/tensorflow@sha256:5e13bcb08570ceab2ff5978463b8fb3cde12e21a6d781e222cc7b2a37bd5f1a9",
        "swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/tensorflow/tensorflow@sha256:a5abd3109b44638ea037dcf8305ca6122e9f8fb6e017159f7c74e3b614ee1dd1"
    ],
    "Parent": "",
    "Comment": "buildkit.dockerfile.v0",
    "Created": "2025-03-12T04:00:54.628599582Z",
    "Container": "",
    "ContainerConfig": null,
    "DockerVersion": "",
    "Author": "",
    "Config": {
        "Hostname": "",
        "Domainname": "",
        "User": "",
        "AttachStdin": false,
        "AttachStdout": false,
        "AttachStderr": false,
        "ExposedPorts": {
            "8888/tcp": {}
        },
        "Tty": false,
        "OpenStdin": false,
        "StdinOnce": false,
        "Env": [
            "PATH=/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=12.3 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 brand=tesla,driver\u003e=535,driver\u003c536 brand=unknown,driver\u003e=535,driver\u003c536 brand=nvidia,driver\u003e=535,driver\u003c536 brand=nvidiartx,driver\u003e=535,driver\u003c536 brand=geforce,driver\u003e=535,driver\u003c536 brand=geforcertx,driver\u003e=535,driver\u003c536 brand=quadro,driver\u003e=535,driver\u003c536 brand=quadrortx,driver\u003e=535,driver\u003c536 brand=titan,driver\u003e=535,driver\u003c536 brand=titanrtx,driver\u003e=535,driver\u003c536",
            "NV_CUDA_CUDART_VERSION=12.3.52-1",
            "NV_CUDA_COMPAT_PACKAGE=cuda-compat-12-3",
            "CUDA_VERSION=12.3.0",
            "LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64",
            "NVIDIA_VISIBLE_DEVICES=all",
            "NVIDIA_DRIVER_CAPABILITIES=compute,utility",
            "DEBIAN_FRONTEND=noninteractive",
            "LANG=C.UTF-8"
        ],
        "Cmd": [
            "bash",
            "-c",
            "source /etc/bash.bashrc \u0026\u0026 jupyter notebook --notebook-dir=/tf --ip 0.0.0.0 --no-browser --allow-root"
        ],
        "ArgsEscaped": true,
        "Image": "",
        "Volumes": null,
        "WorkingDir": "/tf",
        "Entrypoint": null,
        "OnBuild": null,
        "Labels": {
            "maintainer": "NVIDIA CORPORATION \u003ccudatools@nvidia.com\u003e",
            "org.opencontainers.image.ref.name": "ubuntu",
            "org.opencontainers.image.version": "22.04"
        }
    },
    "Architecture": "amd64",
    "Os": "linux",
    "Size": 7865625945,
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}

更多版本

docker.io/tensorflow/tensorflow:2.18.0rc1-jupyter

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