docker.io/paddlepaddle/paddle:2.6.2-gpu-cuda11.2-cudnn8.2-trt8.0 linux/amd64

docker.io/paddlepaddle/paddle:2.6.2-gpu-cuda11.2-cudnn8.2-trt8.0 - 国内下载镜像源 浏览次数:6

PaddlePaddle是中国最大的开源深度学习框架。它可以实现各种常见的机器学习算法,并支持多种编程语言,如Python、Java和C++。该镜像包含了PaddlePaddle的所有依赖包和预建环境,使您能够直接在容器中运行PaddlePaddle应用程序。

源镜像 docker.io/paddlepaddle/paddle:2.6.2-gpu-cuda11.2-cudnn8.2-trt8.0
国内镜像 swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/paddlepaddle/paddle:2.6.2-gpu-cuda11.2-cudnn8.2-trt8.0
镜像ID sha256:66decea5506638fee0db8162e26cae3f2fbb65cd9783bb1503f44dbb3a66ac38
镜像TAG 2.6.2-gpu-cuda11.2-cudnn8.2-trt8.0
大小 21.56GB
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
OS/平台 linux/amd64
浏览量 6 次
贡献者 20******6@qq.com
镜像创建 2024-09-13T06:47:11.762262098Z
同步时间 2025-06-19 14:18
更新时间 2025-06-20 02:33
开放端口
22/tcp
环境变量
PATH=/home/cmake-3.18.0-Linux-x86_64/bin:/usr/local/gcc-8.2/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/go/bin:/root/gopath/bin NVARCH=x86_64 NVIDIA_REQUIRE_CUDA=cuda>=11.2 brand=tesla,driver>=418,driver<419 brand=tesla,driver>=450,driver<451 NV_CUDA_CUDART_VERSION=11.2.152-1 NV_CUDA_COMPAT_PACKAGE=cuda-compat-11-2 CUDA_VERSION=11.2.2 LD_LIBRARY_PATH=/usr/local/TensorRT-8.0.3.4/lib:/usr/local/cuda-11.2/targets/x86_64-linux/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64 NVIDIA_VISIBLE_DEVICES=all NVIDIA_DRIVER_CAPABILITIES=compute,utility NV_CUDA_LIB_VERSION=11.2.2-1 NV_NVTX_VERSION=11.2.152-1 NV_LIBNPP_VERSION=11.3.2.152-1 NV_LIBNPP_PACKAGE=libnpp-11-2=11.3.2.152-1 NV_LIBCUSPARSE_VERSION=11.4.1.1152-1 NV_LIBCUBLAS_PACKAGE_NAME=libcublas-11-2 NV_LIBCUBLAS_VERSION=11.4.1.1043-1 NV_LIBCUBLAS_PACKAGE=libcublas-11-2=11.4.1.1043-1 NV_LIBNCCL_PACKAGE_NAME=libnccl2 NV_LIBNCCL_PACKAGE_VERSION=2.8.4-1 NCCL_VERSION=2.8.4-1 NV_LIBNCCL_PACKAGE=libnccl2=2.8.4-1+cuda11.2 NVIDIA_PRODUCT_NAME=CUDA NV_CUDA_CUDART_DEV_VERSION=11.2.152-1 NV_NVML_DEV_VERSION=11.2.152-1 NV_LIBCUSPARSE_DEV_VERSION=11.4.1.1152-1 NV_LIBNPP_DEV_VERSION=11.3.2.152-1 NV_LIBNPP_DEV_PACKAGE=libnpp-dev-11-2=11.3.2.152-1 NV_LIBCUBLAS_DEV_VERSION=11.4.1.1043-1 NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-11-2 NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-11-2=11.4.1.1043-1 NV_CUDA_NSIGHT_COMPUTE_VERSION=11.2.2-1 NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE=cuda-nsight-compute-11-2=11.2.2-1 NV_NVPROF_VERSION=11.2.152-1 NV_NVPROF_DEV_PACKAGE=cuda-nvprof-11-2=11.2.152-1 NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev NV_LIBNCCL_DEV_PACKAGE_VERSION=2.8.4-1 NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.8.4-1+cuda11.2 LIBRARY_PATH=/usr/local/cuda/lib64/stubs NV_CUDNN_VERSION=8.1.1.33 NV_CUDNN_PACKAGE_NAME=libcudnn8 NV_CUDNN_PACKAGE=libcudnn8=8.1.1.33-1+cuda11.2 NV_CUDNN_PACKAGE_DEV=libcudnn8-dev=8.1.1.33-1+cuda11.2 WITH_GPU=ON WITH_AVX=ON DEBIAN_FRONTEND=noninteractive HOME=/root CUDNN_VERSION=8.2.1 GOROOT=/usr/local/go GOPATH=/root/gopath
镜像标签
8.1.1.33: com.nvidia.cudnn.version NVIDIA CORPORATION <cudatools@nvidia.com>: maintainer ubuntu: org.opencontainers.image.ref.name 20.04: org.opencontainers.image.version

Docker拉取命令

docker pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/paddlepaddle/paddle:2.6.2-gpu-cuda11.2-cudnn8.2-trt8.0
docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/paddlepaddle/paddle:2.6.2-gpu-cuda11.2-cudnn8.2-trt8.0  docker.io/paddlepaddle/paddle:2.6.2-gpu-cuda11.2-cudnn8.2-trt8.0

Containerd拉取命令

ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/paddlepaddle/paddle:2.6.2-gpu-cuda11.2-cudnn8.2-trt8.0
ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/paddlepaddle/paddle:2.6.2-gpu-cuda11.2-cudnn8.2-trt8.0  docker.io/paddlepaddle/paddle:2.6.2-gpu-cuda11.2-cudnn8.2-trt8.0

Shell快速替换命令

sed -i 's#paddlepaddle/paddle:2.6.2-gpu-cuda11.2-cudnn8.2-trt8.0#swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/paddlepaddle/paddle:2.6.2-gpu-cuda11.2-cudnn8.2-trt8.0#' 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/paddlepaddle/paddle:2.6.2-gpu-cuda11.2-cudnn8.2-trt8.0 && docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/paddlepaddle/paddle:2.6.2-gpu-cuda11.2-cudnn8.2-trt8.0  docker.io/paddlepaddle/paddle:2.6.2-gpu-cuda11.2-cudnn8.2-trt8.0'

Ansible快速分发-Containerd

#ansible k8s -m shell -a 'ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/paddlepaddle/paddle:2.6.2-gpu-cuda11.2-cudnn8.2-trt8.0 && ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/paddlepaddle/paddle:2.6.2-gpu-cuda11.2-cudnn8.2-trt8.0  docker.io/paddlepaddle/paddle:2.6.2-gpu-cuda11.2-cudnn8.2-trt8.0'

镜像构建历史


# 2024-09-13 14:47:11  52.32KB 
/bin/sh -c ldconfig
                        
# 2024-09-13 14:47:06  0.00B 
/bin/sh -c #(nop)  ENV LD_LIBRARY_PATH=/usr/local/TensorRT-8.0.3.4/lib:/usr/local/cuda-11.2/targets/x86_64-linux/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64
                        
# 2024-09-13 14:47:03  3.32GB 
/bin/sh -c python -m pip install https://paddle-whl.bj.bcebos.com/stable/cu112/paddlepaddle-gpu/paddlepaddle_gpu-2.6.2.post112-cp310-cp310-linux_x86_64.whl
                        
# 2023-11-14 14:17:03  0.00B 声明容器运行时监听的端口
EXPOSE map[22/tcp:{}]
                        
# 2023-11-14 14:17:03  754.26MB 执行命令并创建新的镜像层
RUN |2 WITH_GPU=ON WITH_AVX=ON /bin/sh -c wget https://paddle-ci.cdn.bcebos.com/clang+llvm-3.8.0-x86_64-linux-gnu-ubuntu-16.04.tar.xz &&     tar xf clang+llvm-3.8.0-x86_64-linux-gnu-ubuntu-16.04.tar.xz && cd clang+llvm-3.8.0-x86_64-linux-gnu-ubuntu-16.04 &&     cp -rn * /usr/local && cd .. && rm -rf clang+llvm-3.8.0-x86_64-linux-gnu-ubuntu-16.04 && rm -rf clang+llvm-3.8.0-x86_64-linux-gnu-ubuntu-16.04.tar.xz # buildkit
                        
# 2023-11-14 14:16:38  46.76MB 执行命令并创建新的镜像层
RUN |2 WITH_GPU=ON WITH_AVX=ON /bin/sh -c wget -q https://paddle-ci.gz.bcebos.com/ccache-4.8.2.tar.gz &&     tar xf ccache-4.8.2.tar.gz && mkdir /usr/local/ccache-4.8.2 && cd ccache-4.8.2 &&     mkdir build && cd build &&     cmake -DCMAKE_BUILD_TYPE=Release -DCMAKE_INSTALL_PREFIX=/usr/local/ccache-4.8.2 .. &&     make -j8 && make install &&     ln -s /usr/local/ccache-4.8.2/bin/ccache /usr/local/bin/ccache &&     cd ../../ && rm -rf ccache-4.8.2.tar.gz # buildkit
                        
# 2023-11-14 14:15:38  88.53MB 执行命令并创建新的镜像层
RUN |2 WITH_GPU=ON WITH_AVX=ON /bin/sh -c pip3.10 --no-cache-dir install -r /root/requirements.txt # buildkit
                        
# 2023-11-14 14:15:01  164.00B 复制新文件或目录到容器中
COPY ./python/requirements.txt /root/ # buildkit
                        
# 2023-11-14 14:15:01  44.00B 执行命令并创建新的镜像层
RUN |2 WITH_GPU=ON WITH_AVX=ON /bin/sh -c rm -f /usr/local/bin/pip && ln -s /usr/local/bin/pip3.10 /usr/local/bin/pip &&     rm -f /usr/local/bin/pip3 && ln -s /usr/local/bin/pip3.10 /usr/local/bin/pip3 # buildkit
                        
# 2023-11-14 14:15:01  6.19MB 执行命令并创建新的镜像层
RUN |2 WITH_GPU=ON WITH_AVX=ON /bin/sh -c localedef -i en_US -f UTF-8 en_US.UTF-8 # buildkit
                        
# 2023-11-14 14:14:59  649.00B 执行命令并创建新的镜像层
RUN |2 WITH_GPU=ON WITH_AVX=ON /bin/sh -c git config --global credential.helper store # buildkit
                        
# 2023-11-14 14:14:59  9.10MB 执行命令并创建新的镜像层
RUN |2 WITH_GPU=ON WITH_AVX=ON /bin/sh -c apt-get install -y golang-glide # buildkit
                        
# 2023-11-14 14:14:51  0.00B 设置环境变量 PATH
ENV PATH=/home/cmake-3.18.0-Linux-x86_64/bin:/usr/local/gcc-8.2/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/go/bin:/root/gopath/bin
                        
# 2023-11-14 14:14:51  0.00B 设置环境变量 GOROOT GOPATH
ENV GOROOT=/usr/local/go GOPATH=/root/gopath
                        
# 2023-11-14 14:14:51  407.78MB 执行命令并创建新的镜像层
RUN |2 WITH_GPU=ON WITH_AVX=ON /bin/sh -c wget --no-check-certificate -qO- https://paddle-ci.gz.bcebos.com/go1.17.2.linux-amd64.tar.gz |     tar -xz -C /usr/local &&     mkdir /root/gopath &&     mkdir /root/gopath/bin &&     mkdir /root/gopath/src # buildkit
                        
# 2023-11-14 14:14:40  140.48MB 执行命令并创建新的镜像层
RUN |2 WITH_GPU=ON WITH_AVX=ON /bin/sh -c wget -q https://ftp.gnu.org/gnu/binutils/binutils-2.33.1.tar.gz &&     tar -xzf binutils-2.33.1.tar.gz &&     cd binutils-2.33.1 &&     ./configure && make -j && make install && cd .. && rm -rf binutils-2.33.1 binutils-2.33.1.tar.gz # buildkit
                        
# 2023-11-14 14:03:56  0.00B 执行命令并创建新的镜像层
RUN |2 WITH_GPU=ON WITH_AVX=ON /bin/sh -c rm setuptools-68.2.2.tar.gz pip-23.3.1.tar.gz &&     rm -r setuptools-68.2.2 pip-23.3.1 # buildkit
                        
# 2023-11-14 11:20:20  0.00B 设置工作目录为/home
WORKDIR /home
                        
# 2023-11-14 11:20:20  23.36MB 执行命令并创建新的镜像层
RUN |2 WITH_GPU=ON WITH_AVX=ON /bin/sh -c python3.10 setup.py install # buildkit
                        
# 2023-11-14 11:20:16  0.00B 设置工作目录为/home/pip-23.3.1
WORKDIR /home/pip-23.3.1
                        
# 2023-11-14 11:20:16  9.91MB 执行命令并创建新的镜像层
RUN |2 WITH_GPU=ON WITH_AVX=ON /bin/sh -c wget https://files.pythonhosted.org/packages/1f/7f/4da15e07ccd11c84c1ccc8f6e24288d5e76c99441bf80e315b33542db951/pip-23.3.1.tar.gz && tar -zxf pip-23.3.1.tar.gz # buildkit
                        
# 2023-11-14 11:20:10  0.00B 设置工作目录为/home
WORKDIR /home
                        
# 2023-11-14 11:20:10  10.89MB 执行命令并创建新的镜像层
RUN |2 WITH_GPU=ON WITH_AVX=ON /bin/sh -c python3.10 setup.py build && python3.10 setup.py install # buildkit
                        
# 2023-11-14 11:20:07  0.00B 设置工作目录为/home/setuptools-68.2.2
WORKDIR /home/setuptools-68.2.2
                        
# 2023-11-14 11:20:07  8.86MB 执行命令并创建新的镜像层
RUN |2 WITH_GPU=ON WITH_AVX=ON /bin/sh -c wget https://files.pythonhosted.org/packages/ef/cc/93f7213b2ab5ed383f98ce8020e632ef256b406b8569606c3f160ed8e1c9/setuptools-68.2.2.tar.gz && tar xf setuptools-68.2.2.tar.gz # buildkit
                        
# 2023-11-14 11:20:00  0.00B 设置工作目录为/home
WORKDIR /home
                        
# 2023-11-14 11:20:00  56.96MB 执行命令并创建新的镜像层
RUN |2 WITH_GPU=ON WITH_AVX=ON /bin/sh -c apt-get update &&   apt-get install -y python3.10 python3.10-dev python3.10-distutils &&   apt-get install python-is-python3 &&   rm /usr/bin/python && ln -s /usr/bin/python3.10 /usr/bin/python &&   rm /usr/bin/python3 && ln -s /usr/bin/python3.10 /usr/bin/python3 # buildkit
                        
# 2023-11-14 10:59:18  0.00B 设置环境变量 PATH
ENV PATH=/home/cmake-3.18.0-Linux-x86_64/bin:/usr/local/gcc-8.2/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
                        
# 2023-11-14 10:59:18  112.87MB 执行命令并创建新的镜像层
RUN |2 WITH_GPU=ON WITH_AVX=ON /bin/sh -c wget -q https://cmake.org/files/v3.18/cmake-3.18.0-Linux-x86_64.tar.gz && tar -zxvf cmake-3.18.0-Linux-x86_64.tar.gz && rm cmake-3.18.0-Linux-x86_64.tar.gz # buildkit
                        
# 2023-11-14 10:50:22  0.00B 设置工作目录为/home
WORKDIR /home
                        
# 2023-11-14 10:50:22  0.00B 执行命令并创建新的镜像层
RUN |2 WITH_GPU=ON WITH_AVX=ON /bin/sh -c rm -rf /build_script # buildkit
                        
# 2023-11-14 10:50:21  0.00B 设置环境变量 CUDNN_VERSION
ENV CUDNN_VERSION=8.2.1
                        
# 2023-11-14 10:50:21  4.01GB 执行命令并创建新的镜像层
RUN |2 WITH_GPU=ON WITH_AVX=ON /bin/sh -c bash /build_scripts/install_cudnn.sh cudnn821 # buildkit
                        
# 2023-11-14 10:47:41  0.00B 设置环境变量 PATH
ENV PATH=/usr/local/gcc-8.2/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
                        
# 2023-11-14 10:47:41  26.00B 执行命令并创建新的镜像层
RUN |2 WITH_GPU=ON WITH_AVX=ON /bin/sh -c ln -s /usr/local/gcc-8.2/bin/g++ /usr/bin/g++ # buildkit
                        
# 2023-11-14 10:47:41  26.00B 执行命令并创建新的镜像层
RUN |2 WITH_GPU=ON WITH_AVX=ON /bin/sh -c ln -s /usr/local/gcc-8.2/bin/gcc /usr/bin/gcc # buildkit
                        
# 2023-11-14 10:47:41  26.00B 执行命令并创建新的镜像层
RUN |2 WITH_GPU=ON WITH_AVX=ON /bin/sh -c ln -s /usr/local/gcc-8.2/bin/g++ /usr/local/bin/g++ # buildkit
                        
# 2023-11-14 10:47:41  26.00B 执行命令并创建新的镜像层
RUN |2 WITH_GPU=ON WITH_AVX=ON /bin/sh -c ln -s /usr/local/gcc-8.2/bin/gcc /usr/local/bin/gcc # buildkit
                        
# 2023-11-14 10:47:40  2.32MB 执行命令并创建新的镜像层
RUN |2 WITH_GPU=ON WITH_AVX=ON /bin/sh -c cp gcc gcc.bak && cp g++ g++.bak && rm gcc && rm g++ # buildkit
                        
# 2023-11-14 10:47:40  1.54GB 执行命令并创建新的镜像层
RUN |2 WITH_GPU=ON WITH_AVX=ON /bin/sh -c bash /build_scripts/install_gcc.sh gcc82 # buildkit
                        
# 2023-11-14 10:04:01  3.63MB 执行命令并创建新的镜像层
RUN |2 WITH_GPU=ON WITH_AVX=ON /bin/sh -c bash /build_scripts/install_patchelf.sh # buildkit
                        
# 2023-11-14 10:03:38  2.78GB 执行命令并创建新的镜像层
RUN |2 WITH_GPU=ON WITH_AVX=ON /bin/sh -c bash /build_scripts/install_trt.sh trt8034 # buildkit
                        
# 2023-11-14 10:03:00  37.26KB 复制新文件或目录到容器中
COPY tools/dockerfile/build_scripts /build_scripts # buildkit
                        
# 2023-11-14 10:03:00  0.00B 设置工作目录为/usr/bin
WORKDIR /usr/bin
                        
# 2023-11-14 10:03:00  504.49MB 执行命令并创建新的镜像层
RUN |2 WITH_GPU=ON WITH_AVX=ON /bin/sh -c apt-get update --allow-unauthenticated &&   apt-get install -y software-properties-common &&   add-apt-repository ppa:deadsnakes/ppa &&   apt-get update &&   apt-get install -y curl wget vim git unzip unrar tar xz-utils libssl-dev bzip2 gzip     coreutils ntp language-pack-zh-hans libsm6 libxext6 libxrender-dev libgl1-mesa-glx     bison graphviz libjpeg-dev zlib1g-dev automake locales swig net-tools libtool kmod # buildkit
                        
# 2023-11-14 09:56:06  0.00B 执行命令并创建新的镜像层
RUN |2 WITH_GPU=ON WITH_AVX=ON /bin/sh -c apt-key adv --fetch-keys https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu2004/x86_64/3bf863cc.pub # buildkit
                        
# 2023-11-14 09:56:05  0.00B 执行命令并创建新的镜像层
RUN |2 WITH_GPU=ON WITH_AVX=ON /bin/sh -c rm /etc/apt/sources.list.d/* # buildkit
                        
# 2023-11-14 09:56:05  0.00B 执行命令并创建新的镜像层
RUN |2 WITH_GPU=ON WITH_AVX=ON /bin/sh -c apt-key del 7fa2af80 # buildkit
                        
# 2023-11-14 09:56:04  0.00B 执行命令并创建新的镜像层
RUN |2 WITH_GPU=ON WITH_AVX=ON /bin/sh -c chmod 777 /tmp # buildkit
                        
# 2023-11-14 09:56:04  1.29KB 复制新文件或目录到容器中
COPY paddle/scripts/docker/root/ /root/ # buildkit
                        
# 2023-11-14 09:56:04  0.00B 设置环境变量 HOME
ENV HOME=/root
                        
# 2023-11-14 09:56:04  0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/cuda-11.2/targets/x86_64-linux/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64
                        
# 2023-11-14 09:56:04  0.00B 设置环境变量 DEBIAN_FRONTEND
ENV DEBIAN_FRONTEND=noninteractive
                        
# 2023-11-14 09:56:04  0.00B 设置环境变量 WITH_AVX
ENV WITH_AVX=ON
                        
# 2023-11-14 09:56:04  0.00B 设置环境变量 WITH_GPU
ENV WITH_GPU=ON
                        
# 2023-11-14 09:56:04  0.00B 定义构建参数
ARG WITH_AVX
                        
# 2023-11-14 09:56:04  0.00B 定义构建参数
ARG WITH_GPU
                        
# 2023-11-14 09:56:04  0.00B 
MAINTAINER PaddlePaddle Authors <paddle-dev@baidu.com>
                        
# 2023-11-10 16:55:54  2.82GB 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 16:55:54  0.00B 添加元数据标签
LABEL com.nvidia.cudnn.version=8.1.1.33
                        
# 2023-11-10 16:55:54  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2023-11-10 16:55:54  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2023-11-10 16:55:54  0.00B 设置环境变量 NV_CUDNN_PACKAGE_DEV
ENV NV_CUDNN_PACKAGE_DEV=libcudnn8-dev=8.1.1.33-1+cuda11.2
                        
# 2023-11-10 16:55:54  0.00B 设置环境变量 NV_CUDNN_PACKAGE
ENV NV_CUDNN_PACKAGE=libcudnn8=8.1.1.33-1+cuda11.2
                        
# 2023-11-10 16:55:54  0.00B 设置环境变量 NV_CUDNN_PACKAGE_NAME
ENV NV_CUDNN_PACKAGE_NAME=libcudnn8
                        
# 2023-11-10 16:55:54  0.00B 设置环境变量 NV_CUDNN_VERSION
ENV NV_CUDNN_VERSION=8.1.1.33
                        
# 2023-11-10 16:35:20  0.00B 设置环境变量 LIBRARY_PATH
ENV LIBRARY_PATH=/usr/local/cuda/lib64/stubs
                        
# 2023-11-10 16:35:20  369.15KB 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 16:35:19  2.99GB 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     libtinfo5 libncursesw5     cuda-cudart-dev-11-2=${NV_CUDA_CUDART_DEV_VERSION}     cuda-command-line-tools-11-2=${NV_CUDA_LIB_VERSION}     cuda-minimal-build-11-2=${NV_CUDA_LIB_VERSION}     cuda-libraries-dev-11-2=${NV_CUDA_LIB_VERSION}     cuda-nvml-dev-11-2=${NV_NVML_DEV_VERSION}     ${NV_NVPROF_DEV_PACKAGE}     ${NV_LIBNPP_DEV_PACKAGE}     libcusparse-dev-11-2=${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 16:35:19  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2023-11-10 16:35:19  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2023-11-10 16:35:19  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE
ENV NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.8.4-1+cuda11.2
                        
# 2023-11-10 16:35:19  0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.8.4-1
                        
# 2023-11-10 16:35:19  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE_VERSION
ENV NV_LIBNCCL_DEV_PACKAGE_VERSION=2.8.4-1
                        
# 2023-11-10 16:35:19  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE_NAME
ENV NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev
                        
# 2023-11-10 16:35:19  0.00B 设置环境变量 NV_NVPROF_DEV_PACKAGE
ENV NV_NVPROF_DEV_PACKAGE=cuda-nvprof-11-2=11.2.152-1
                        
# 2023-11-10 16:35:19  0.00B 设置环境变量 NV_NVPROF_VERSION
ENV NV_NVPROF_VERSION=11.2.152-1
                        
# 2023-11-10 16:35:19  0.00B 设置环境变量 NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE
ENV NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE=cuda-nsight-compute-11-2=11.2.2-1
                        
# 2023-11-10 16:35:19  0.00B 设置环境变量 NV_CUDA_NSIGHT_COMPUTE_VERSION
ENV NV_CUDA_NSIGHT_COMPUTE_VERSION=11.2.2-1
                        
# 2023-11-10 16:35:19  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_PACKAGE
ENV NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-11-2=11.4.1.1043-1
                        
# 2023-11-10 16:35:19  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_PACKAGE_NAME
ENV NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-11-2
                        
# 2023-11-10 16:35:19  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_VERSION
ENV NV_LIBCUBLAS_DEV_VERSION=11.4.1.1043-1
                        
# 2023-11-10 16:35:19  0.00B 设置环境变量 NV_LIBNPP_DEV_PACKAGE
ENV NV_LIBNPP_DEV_PACKAGE=libnpp-dev-11-2=11.3.2.152-1
                        
# 2023-11-10 16:35:19  0.00B 设置环境变量 NV_LIBNPP_DEV_VERSION
ENV NV_LIBNPP_DEV_VERSION=11.3.2.152-1
                        
# 2023-11-10 16:35:19  0.00B 设置环境变量 NV_LIBCUSPARSE_DEV_VERSION
ENV NV_LIBCUSPARSE_DEV_VERSION=11.4.1.1152-1
                        
# 2023-11-10 16:35:19  0.00B 设置环境变量 NV_NVML_DEV_VERSION
ENV NV_NVML_DEV_VERSION=11.2.152-1
                        
# 2023-11-10 16:35:19  0.00B 设置环境变量 NV_CUDA_CUDART_DEV_VERSION
ENV NV_CUDA_CUDART_DEV_VERSION=11.2.152-1
                        
# 2023-11-10 16:35:19  0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=11.2.2-1
                        
# 2023-11-10 16:26:24  0.00B 配置容器启动时运行的命令
ENTRYPOINT ["/opt/nvidia/nvidia_entrypoint.sh"]
                        
# 2023-11-10 16:26:24  0.00B 设置环境变量 NVIDIA_PRODUCT_NAME
ENV NVIDIA_PRODUCT_NAME=CUDA
                        
# 2023-11-10 16:26:24  2.53KB 复制新文件或目录到容器中
COPY nvidia_entrypoint.sh /opt/nvidia/ # buildkit
                        
# 2023-11-10 16:26:24  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 16:26:24  252.27KB 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 16:26:23  1.79GB 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-libraries-11-2=${NV_CUDA_LIB_VERSION}     ${NV_LIBNPP_PACKAGE}     cuda-nvtx-11-2=${NV_NVTX_VERSION}     libcusparse-11-2=${NV_LIBCUSPARSE_VERSION}     ${NV_LIBCUBLAS_PACKAGE}     ${NV_LIBNCCL_PACKAGE}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2023-11-10 16:26:23  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2023-11-10 16:26:23  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2023-11-10 16:26:23  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE
ENV NV_LIBNCCL_PACKAGE=libnccl2=2.8.4-1+cuda11.2
                        
# 2023-11-10 16:26:23  0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.8.4-1
                        
# 2023-11-10 16:26:23  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_VERSION
ENV NV_LIBNCCL_PACKAGE_VERSION=2.8.4-1
                        
# 2023-11-10 16:26:23  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_NAME
ENV NV_LIBNCCL_PACKAGE_NAME=libnccl2
                        
# 2023-11-10 16:26:23  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE
ENV NV_LIBCUBLAS_PACKAGE=libcublas-11-2=11.4.1.1043-1
                        
# 2023-11-10 16:26:23  0.00B 设置环境变量 NV_LIBCUBLAS_VERSION
ENV NV_LIBCUBLAS_VERSION=11.4.1.1043-1
                        
# 2023-11-10 16:26:23  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE_NAME
ENV NV_LIBCUBLAS_PACKAGE_NAME=libcublas-11-2
                        
# 2023-11-10 16:26:23  0.00B 设置环境变量 NV_LIBCUSPARSE_VERSION
ENV NV_LIBCUSPARSE_VERSION=11.4.1.1152-1
                        
# 2023-11-10 16:26:23  0.00B 设置环境变量 NV_LIBNPP_PACKAGE
ENV NV_LIBNPP_PACKAGE=libnpp-11-2=11.3.2.152-1
                        
# 2023-11-10 16:26:23  0.00B 设置环境变量 NV_LIBNPP_VERSION
ENV NV_LIBNPP_VERSION=11.3.2.152-1
                        
# 2023-11-10 16:26:23  0.00B 设置环境变量 NV_NVTX_VERSION
ENV NV_NVTX_VERSION=11.2.152-1
                        
# 2023-11-10 16:26:23  0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=11.2.2-1
                        
# 2023-11-10 16:19:37  0.00B 设置环境变量 NVIDIA_DRIVER_CAPABILITIES
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
                        
# 2023-11-10 16:19:37  0.00B 设置环境变量 NVIDIA_VISIBLE_DEVICES
ENV NVIDIA_VISIBLE_DEVICES=all
                        
# 2023-11-10 16:19:37  17.29KB 复制新文件或目录到容器中
COPY NGC-DL-CONTAINER-LICENSE / # buildkit
                        
# 2023-11-10 16:19:37  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 16:19:37  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 16:19:37  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 16:19:37  33.47MB 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-11-2=${NV_CUDA_CUDART_VERSION}     ${NV_CUDA_COMPAT_PACKAGE}     && ln -s cuda-11.2 /usr/local/cuda     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2023-11-10 16:19:26  0.00B 设置环境变量 CUDA_VERSION
ENV CUDA_VERSION=11.2.2
                        
# 2023-11-10 16:19:26  18.32MB 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 -fsSL https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/${NVARCH}/3bf863cc.pub | apt-key add - &&     echo "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/${NVARCH} /" > /etc/apt/sources.list.d/cuda.list &&     apt-get purge --autoremove -y curl     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2023-11-10 16:19:26  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2023-11-10 16:19:26  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2023-11-10 16:19:26  0.00B 设置环境变量 NV_CUDA_COMPAT_PACKAGE
ENV NV_CUDA_COMPAT_PACKAGE=cuda-compat-11-2
                        
# 2023-11-10 16:19:26  0.00B 设置环境变量 NV_CUDA_CUDART_VERSION
ENV NV_CUDA_CUDART_VERSION=11.2.152-1
                        
# 2023-11-10 16:19:26  0.00B 设置环境变量 NVIDIA_REQUIRE_CUDA brand brand
ENV NVIDIA_REQUIRE_CUDA=cuda>=11.2 brand=tesla,driver>=418,driver<419 brand=tesla,driver>=450,driver<451
                        
# 2023-11-10 16:19:26  0.00B 设置环境变量 NVARCH
ENV NVARCH=x86_64
                        
# 2023-10-03 18:45:52  0.00B 
/bin/sh -c #(nop)  CMD ["/bin/bash"]
                        
# 2023-10-03 18:45:51  72.79MB 
/bin/sh -c #(nop) ADD file:4809da414c2d478b4d991cbdaa2df457f2b3d07d0ff6cf673f09a66f90833e81 in / 
                        
# 2023-10-03 18:45:50  0.00B 
/bin/sh -c #(nop)  LABEL org.opencontainers.image.version=20.04
                        
# 2023-10-03 18:45:50  0.00B 
/bin/sh -c #(nop)  LABEL org.opencontainers.image.ref.name=ubuntu
                        
# 2023-10-03 18:45:50  0.00B 
/bin/sh -c #(nop)  ARG LAUNCHPAD_BUILD_ARCH
                        
# 2023-10-03 18:45:50  0.00B 
/bin/sh -c #(nop)  ARG RELEASE
                        
                    

镜像信息

{
    "Id": "sha256:66decea5506638fee0db8162e26cae3f2fbb65cd9783bb1503f44dbb3a66ac38",
    "RepoTags": [
        "paddlepaddle/paddle:2.6.2-gpu-cuda11.2-cudnn8.2-trt8.0",
        "swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/paddlepaddle/paddle:2.6.2-gpu-cuda11.2-cudnn8.2-trt8.0"
    ],
    "RepoDigests": [
        "paddlepaddle/paddle@sha256:22d8c86d8c487b79cda55193425b6ba19557e3c8167e620a29bf077358969a0d",
        "swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/paddlepaddle/paddle@sha256:fb24ab479c5085c3afe9418e6f1e252f54aa814e49631318a0ead3576c9978e2"
    ],
    "Parent": "",
    "Comment": "",
    "Created": "2024-09-13T06:47:11.762262098Z",
    "Container": "",
    "ContainerConfig": null,
    "DockerVersion": "20.10.23",
    "Author": "",
    "Config": {
        "Hostname": "",
        "Domainname": "",
        "User": "",
        "AttachStdin": false,
        "AttachStdout": false,
        "AttachStderr": false,
        "ExposedPorts": {
            "22/tcp": {}
        },
        "Tty": false,
        "OpenStdin": false,
        "StdinOnce": false,
        "Env": [
            "PATH=/home/cmake-3.18.0-Linux-x86_64/bin:/usr/local/gcc-8.2/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/go/bin:/root/gopath/bin",
            "NVARCH=x86_64",
            "NVIDIA_REQUIRE_CUDA=cuda\u003e=11.2 brand=tesla,driver\u003e=418,driver\u003c419 brand=tesla,driver\u003e=450,driver\u003c451",
            "NV_CUDA_CUDART_VERSION=11.2.152-1",
            "NV_CUDA_COMPAT_PACKAGE=cuda-compat-11-2",
            "CUDA_VERSION=11.2.2",
            "LD_LIBRARY_PATH=/usr/local/TensorRT-8.0.3.4/lib:/usr/local/cuda-11.2/targets/x86_64-linux/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64",
            "NVIDIA_VISIBLE_DEVICES=all",
            "NVIDIA_DRIVER_CAPABILITIES=compute,utility",
            "NV_CUDA_LIB_VERSION=11.2.2-1",
            "NV_NVTX_VERSION=11.2.152-1",
            "NV_LIBNPP_VERSION=11.3.2.152-1",
            "NV_LIBNPP_PACKAGE=libnpp-11-2=11.3.2.152-1",
            "NV_LIBCUSPARSE_VERSION=11.4.1.1152-1",
            "NV_LIBCUBLAS_PACKAGE_NAME=libcublas-11-2",
            "NV_LIBCUBLAS_VERSION=11.4.1.1043-1",
            "NV_LIBCUBLAS_PACKAGE=libcublas-11-2=11.4.1.1043-1",
            "NV_LIBNCCL_PACKAGE_NAME=libnccl2",
            "NV_LIBNCCL_PACKAGE_VERSION=2.8.4-1",
            "NCCL_VERSION=2.8.4-1",
            "NV_LIBNCCL_PACKAGE=libnccl2=2.8.4-1+cuda11.2",
            "NVIDIA_PRODUCT_NAME=CUDA",
            "NV_CUDA_CUDART_DEV_VERSION=11.2.152-1",
            "NV_NVML_DEV_VERSION=11.2.152-1",
            "NV_LIBCUSPARSE_DEV_VERSION=11.4.1.1152-1",
            "NV_LIBNPP_DEV_VERSION=11.3.2.152-1",
            "NV_LIBNPP_DEV_PACKAGE=libnpp-dev-11-2=11.3.2.152-1",
            "NV_LIBCUBLAS_DEV_VERSION=11.4.1.1043-1",
            "NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-11-2",
            "NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-11-2=11.4.1.1043-1",
            "NV_CUDA_NSIGHT_COMPUTE_VERSION=11.2.2-1",
            "NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE=cuda-nsight-compute-11-2=11.2.2-1",
            "NV_NVPROF_VERSION=11.2.152-1",
            "NV_NVPROF_DEV_PACKAGE=cuda-nvprof-11-2=11.2.152-1",
            "NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev",
            "NV_LIBNCCL_DEV_PACKAGE_VERSION=2.8.4-1",
            "NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.8.4-1+cuda11.2",
            "LIBRARY_PATH=/usr/local/cuda/lib64/stubs",
            "NV_CUDNN_VERSION=8.1.1.33",
            "NV_CUDNN_PACKAGE_NAME=libcudnn8",
            "NV_CUDNN_PACKAGE=libcudnn8=8.1.1.33-1+cuda11.2",
            "NV_CUDNN_PACKAGE_DEV=libcudnn8-dev=8.1.1.33-1+cuda11.2",
            "WITH_GPU=ON",
            "WITH_AVX=ON",
            "DEBIAN_FRONTEND=noninteractive",
            "HOME=/root",
            "CUDNN_VERSION=8.2.1",
            "GOROOT=/usr/local/go",
            "GOPATH=/root/gopath"
        ],
        "Cmd": null,
        "Image": "sha256:d2174be2418445f7bb9ae66b14de8c2c1391c0f3a02030c5734242560084b704",
        "Volumes": null,
        "WorkingDir": "/home",
        "Entrypoint": [
            "/opt/nvidia/nvidia_entrypoint.sh"
        ],
        "OnBuild": null,
        "Labels": {
            "com.nvidia.cudnn.version": "8.1.1.33",
            "maintainer": "NVIDIA CORPORATION \u003ccudatools@nvidia.com\u003e",
            "org.opencontainers.image.ref.name": "ubuntu",
            "org.opencontainers.image.version": "20.04"
        }
    },
    "Architecture": "amd64",
    "Os": "linux",
    "Size": 21561476735,
    "GraphDriver": {
        "Data": {
            "LowerDir": "/var/lib/docker/overlay2/2523c017b04ade9d984590684f43043c35a0428f1ae1d46c3ace1278d45d3335/diff:/var/lib/docker/overlay2/6e9d2fbf11f09ea73b08ef42e63812918797a05871f6085f1bbd9ac69442a929/diff:/var/lib/docker/overlay2/950bfa6038d3d63ca12681c14aa1beac6ae236994615e1f186948425a8b59e38/diff:/var/lib/docker/overlay2/b9fd8f903a41a4793315f1ebf3270ec1be36642f4bbf7c3db78fd0f3a6374fea/diff:/var/lib/docker/overlay2/a6f47ffb2bdd46829cc5bd4b555495eec9b1a2f41365fd89e75b92c4f1073074/diff:/var/lib/docker/overlay2/44ed543332c18039fbee6df11a5da69c20cc2b45ab4ea495d431dd8ee4a20e8a/diff:/var/lib/docker/overlay2/2eae7c3c6a6d778b99496ea5faf26a5e1efc1637f6aee5b319f8a1eed28fda0e/diff:/var/lib/docker/overlay2/8e40f379d4b01c6ed045e8739f99df083a1cab93751b9dbf591cd9b859dfbbc2/diff:/var/lib/docker/overlay2/a303ac3cc29d143e53b28b7b31505ddb04310a90cf4becbedbc40da82360dad8/diff:/var/lib/docker/overlay2/275448b87179846ceec004f7bffd0abb530953088b1cdca8563d167ca8f512c3/diff:/var/lib/docker/overlay2/9d142e291b39a684a348cebf6b76023c4c35924aa714f4b176d5be9427721f48/diff:/var/lib/docker/overlay2/55eb3cf7de32971f20126dd38636630aeb99fc822ab4f553125c0bddf47cfd3b/diff:/var/lib/docker/overlay2/e7f51d7bde8ad3a1c46203792d5aa2188c9db4b0af60485007db7fef323deaef/diff:/var/lib/docker/overlay2/07092527c36461dcf4c4c151e1cea7b41b9a29cfd4cbfb3e5fd60790cb13c41b/diff:/var/lib/docker/overlay2/f19198ed719f193202b2e7a74d040975c8da29ac30d89dbb02bee6af8157149b/diff:/var/lib/docker/overlay2/982437c7e6012e251c17c713e4e69ba6221f343aa00def78ddcde9dc2c36be62/diff:/var/lib/docker/overlay2/e10950b66f8813c7a0af8beeb819e4544fb973ac041e59ed88f5756a2efd4395/diff:/var/lib/docker/overlay2/475ccbb24bf7c17b2a5f24455f968ec3a19e7099f2d82eeae489e22fff71eb73/diff:/var/lib/docker/overlay2/28b3d822d95d2f33a386651d64a319d6395955d05b31ff9139beb7537953e3bd/diff:/var/lib/docker/overlay2/aa59f5316cd145ea3d870b63e09a26945a4c23796b06d4093c8cd8bd66273120/diff:/var/lib/docker/overlay2/998690b1d7f0b6aa105910506e61727d0c91cac8fda8fa484bdb104713d51084/diff:/var/lib/docker/overlay2/d1f438d941bf19941d9ad780e94adbdc89b7671cebe5741e894a2671c418b940/diff:/var/lib/docker/overlay2/a8a3cc53cabf69cea2ab584570890d4a8c15ffbe304c42e86e394cb3de89d684/diff:/var/lib/docker/overlay2/fb9b3fe64d6164e9f9d815a7c15a5462b0d1c24640ae06f96a898b867c3ad522/diff:/var/lib/docker/overlay2/32ff081591050032ca24368a3a4f26816cef1a4222f8c6e4aca8349f7f78a9d9/diff:/var/lib/docker/overlay2/379c99d238eb5fd29c99c65cc8a2a1f5d8f8674ead589fb26cc01f3609627ac6/diff:/var/lib/docker/overlay2/6103cb58b7bb95ca6070c5f5bf36e1af7648717cfded4623f49ae70e28846494/diff:/var/lib/docker/overlay2/b5d9df86040324beffd246521de8898bfcad62833a5182059d41efd3256328fd/diff:/var/lib/docker/overlay2/383f03c72fb0cb747303f7f1603382ab0f633c8e67489b3db77361f400dd91df/diff:/var/lib/docker/overlay2/59e47cf7679f275fced49b8b58c97642f734ff1a51ae657465c59abcd379a232/diff:/var/lib/docker/overlay2/d118cb308e100fa50c9b7466f5c7ee7561ba66526444602cfcf12750ac7fc2c0/diff:/var/lib/docker/overlay2/f949c3c553bbd83540a3ab15199d4392d106facedb4e5618a01157803a1f7be4/diff:/var/lib/docker/overlay2/145acd103bc52d4798b973b677639ba1075b993f6aafd75549e3cf8085df23e5/diff:/var/lib/docker/overlay2/c35d739f72e70519720469224483b1558f41940f6e2202c96e33363a5cee3ade/diff:/var/lib/docker/overlay2/5c5278990f19c87b1c84453f061b01ee3f6e2a2b4fabfed73edfa5248abc4431/diff:/var/lib/docker/overlay2/6e2f7fd9a2bc0474aa6faeb922b18611bf0319aefbc66b9f4afe734867fa33fb/diff:/var/lib/docker/overlay2/dc6673e549ae1584ffcf54647444a9e8d8f1fb7b4af0f3fbd718e1283212e647/diff:/var/lib/docker/overlay2/2c741a95e3358360a5aacfdf3f7804827e5756b22269a1a56ab230eb623da749/diff:/var/lib/docker/overlay2/efe11e4e784093bc53e0574019268d58baccdd2e3465eb2256997ac659be200d/diff:/var/lib/docker/overlay2/5166ada19c8222546ed42daf69573579b7212b902df29a45c27234e9435ea760/diff:/var/lib/docker/overlay2/57ee216478b775b2a34edbfde788d1463ea52a345bdfca5b7e3ed2f63ac2a543/diff:/var/lib/docker/overlay2/2db4c5c498592a4cb99dccf89bd503713b4982b77a4761b27c9a6a79274d8ce4/diff:/var/lib/docker/overlay2/24ef3a9fa3c50be1beaede0400f5d9a1d8ab6f8d9d2647d903002e643f0bcb5b/diff:/var/lib/docker/overlay2/af6943d2238a6b7cc5f1e557e72b5f39210d7511a22fd03de2a161b73879ffe8/diff:/var/lib/docker/overlay2/e9cd4a31a2d4fad93878b74389b2278989ea90615c48a6513dc4462ba8b941b9/diff:/var/lib/docker/overlay2/07ab00b574011a0ce316f0e1d48d4651ad7c94893b3af5538a66f046e8170477/diff:/var/lib/docker/overlay2/06122d4faf8bedd0309ccd4eab8a4f173b20acf12299bb14bd2f835ce5b0c8ef/diff:/var/lib/docker/overlay2/934f428d745a97fd766614d72d4877cc3d176e7e98770196b29adb1a4ce00ad5/diff:/var/lib/docker/overlay2/1a7d553e552b942ec21c095cbade0c3854decc86e8c78fca4156204f3b1cbd71/diff:/var/lib/docker/overlay2/baccd7fc18640ba753fcfa035a746376417a5e7e9c1cc4503fce61e47ba33ef6/diff:/var/lib/docker/overlay2/eb99094116671b39705302896af964f5cb76d7458e70d8b232289141dbe18646/diff:/var/lib/docker/overlay2/c058e27652ce7a0932991ddfb622230d0c58a4f1cb2d763f72203157d76b7b92/diff:/var/lib/docker/overlay2/6b648108dee455bb25fc5949f9e6d954dd2903a159343545b7826e8913d41395/diff:/var/lib/docker/overlay2/5408abd3ec726f4d055e10fddd8f488a8839c8a355fe1fb064cdc9fee660e07b/diff",
            "MergedDir": "/var/lib/docker/overlay2/472670a6d129730a223d7eb22c2a284d5e914cc797a88b9c1435f2c62aa4de6d/merged",
            "UpperDir": "/var/lib/docker/overlay2/472670a6d129730a223d7eb22c2a284d5e914cc797a88b9c1435f2c62aa4de6d/diff",
            "WorkDir": "/var/lib/docker/overlay2/472670a6d129730a223d7eb22c2a284d5e914cc797a88b9c1435f2c62aa4de6d/work"
        },
        "Name": "overlay2"
    },
    "RootFS": {
        "Type": "layers",
        "Layers": [
            "sha256:6c3e7df31590f02f10cb71fc4eb27653e9b428df2e6e5421a455b062bd2e39f9",
            "sha256:0f24c57a5268042cb3f0936f887f3ccf4b611544462bf94079172ad437ed7c15",
            "sha256:3d25fa2df354fa0854b58fc8af1650027ac93100a94a40419e2016bb347d5ea8",
            "sha256:3c2c7e06674129a4db57ba759ae0e3dc2452f3328a49b6f28e821910aced10bd",
            "sha256:0474cd91a62def9929de8b4191091ecd734f618909e00ea954e4e12d4e5efb5c",
            "sha256:546e449b5cad3efe43ff64b23b4c19c9de27d4a8d9c15a25b7033a7d39cea1a9",
            "sha256:f93b61aec5c6e717eb1fce8a0745a80fbf03c4b8f1df0235c4818d0cb812e188",
            "sha256:af64f49c62d80cafa5dd7f9bc6ac2ffcf049592005f6884cd502f615e6d4c1bf",
            "sha256:f30d3beff47e2db71037a1948e4bbacf48dfbc534e76868a17559cf38fea1109",
            "sha256:0477603eb2df2c988eaf92a1212189f4a74f34e24f33c78054b75741ec272f60",
            "sha256:8426b709a1a7f76a2300c5eb27d150e930d7d0c9a2d352da2d4867b890cfb6c9",
            "sha256:4a60c1983a7eaa795ec72c01145898cde32ef07523a892ad209f974903d6cd34",
            "sha256:d8228ec51107ad52300f085f40efdc250485cdab64860c2b642bca214ed0c116",
            "sha256:1a637586bab3853c083160605a091efd610a1b086cfe1b29d9195cc393038f03",
            "sha256:5f70bf18a086007016e948b04aed3b82103a36bea41755b6cddfaf10ace3c6ef",
            "sha256:c78c48740afc75c26a9ae5e3cfa3c3917bb3ea87ee4103aae00c85444c4e7786",
            "sha256:5f70bf18a086007016e948b04aed3b82103a36bea41755b6cddfaf10ace3c6ef",
            "sha256:ef6d97026f42106e599ba8f7093812123e0ce7db9962bfcf7ed42186c4627211",
            "sha256:5f70bf18a086007016e948b04aed3b82103a36bea41755b6cddfaf10ace3c6ef",
            "sha256:f451fadf8281af07da534850b79aac96282b705a1af3c92961a3fe46ed3504c8",
            "sha256:98187ed393de85d59f52037f5a3a2b18003302d0acfae8ab9af750e4d31cba0b",
            "sha256:23b2781858f6c20e955f3cd7f9bcc0a8d41b122afff86c3ac0cead5f52eeb263",
            "sha256:f3c104582b959a3f1c19d7ece0fa9d242668995fe3431869c62dab3d8dfa6b6e",
            "sha256:2ad5a59ce9ee77376c8bd8236fe76e354b9d7f1723a8ec214a2e95d401fa0d53",
            "sha256:373cdb7ba0a16d4615fc4a4255c8286b4348e76201d226dcaaaf1e6bd00c158e",
            "sha256:cb1d97ca62e1d8d39d70f4fb2793a03cdda386a7a8cac60e8d8a117edd9e43d8",
            "sha256:99d8be57a97a21cb55e4fdff1fd6c1a4912426e5c55d29be85061e4024b6e489",
            "sha256:dbfb2f258a569d10c7c753ff07f0c9e9d6ce2c55317079b8e449a60dcceca435",
            "sha256:d0ac3f25ef78f3ac52a070c63ab5b48a43118efe11319cd05593a16d586157dc",
            "sha256:5f70bf18a086007016e948b04aed3b82103a36bea41755b6cddfaf10ace3c6ef",
            "sha256:5f70bf18a086007016e948b04aed3b82103a36bea41755b6cddfaf10ace3c6ef",
            "sha256:008cfef16f89450b6c91fd45563db5e7e24d95bd6f1cd862d99157d49aa057de",
            "sha256:81bf0fd6e7cdfe277e5794f2c4822ab455f67e14e2c60b5dc655309b19536f8a",
            "sha256:5f70bf18a086007016e948b04aed3b82103a36bea41755b6cddfaf10ace3c6ef",
            "sha256:738254c3295b686486fb55d8424c454390bddb455ca7f8e0607800fe5fb1d7ab",
            "sha256:5f70bf18a086007016e948b04aed3b82103a36bea41755b6cddfaf10ace3c6ef",
            "sha256:a5a6c86f7e1edf25e7a11f9dcc297ef72317c8522c676e714bfda189a9ecb308",
            "sha256:5f70bf18a086007016e948b04aed3b82103a36bea41755b6cddfaf10ace3c6ef",
            "sha256:33be463f0f050251d5700f654fe81e85fdcca1f54d9ef46cdcfafc2903141aa8",
            "sha256:5f70bf18a086007016e948b04aed3b82103a36bea41755b6cddfaf10ace3c6ef",
            "sha256:a683405ffa488fc3db1f9e98f8954a3ae47ea27de4a0e2947b0b6c5f1c7413f1",
            "sha256:5f70bf18a086007016e948b04aed3b82103a36bea41755b6cddfaf10ace3c6ef",
            "sha256:505ef27b5d1403e38e137846c44e0c18fd876ff4530182448648ddc109fb70b9",
            "sha256:311a7bfaf652eaba9665b8fa0f4a89fafcd0f7c5ed96d9368931e8217005fe6b",
            "sha256:f49c1d5a2bd78c064fa7cc91c89bd4f6c1e6c508a433d8a04c67787beced70c8",
            "sha256:c3a101a17acf7435a958571c6ba5196792e7ecd60c0a6ab8dfbb22af740ce287",
            "sha256:195343ac4a55d2617896534937694088a1e8dd15d5a481450ba2af75851a869d",
            "sha256:a0ddee68a15a791a13a8b420659bf656c2d59411ccdf674c9814c183c09c6296",
            "sha256:b16d17fe0bd98cba64b79e4fc09501fa89f31f0587b93c653a42a16564b32c78",
            "sha256:c0f9c9022a850419f1d80a3b8d4e747787c7f9ac31a34273f87f90de336f41ae",
            "sha256:4fea412a061ea8d1437c9eea50c285d99ac8826002858fe9a207bd9c3c33f718",
            "sha256:a848820db570c15beebff1bb8455ad839dd70b1abeb28ff26457c8d79b633b94",
            "sha256:c28b708e1e1ce407e2a8ba6359771102b1a706b479a6483214575544e1795ed3",
            "sha256:b10a76ecc81e4d78ec2d7c156f8b44bcec774b0aaa20f38a66fb300fa84250af",
            "sha256:7e5a1a4921b968a13c8fd3cf080510ffe53219462926511d98fa32224ca1829b"
        ]
    },
    "Metadata": {
        "LastTagTime": "2025-06-19T14:02:04.224254311+08:00"
    }
}

更多版本

docker.io/paddlepaddle/paddle:2.4.1-gpu-cuda11.7-cudnn8.4-trt8.4

linux/amd64 docker.io17.30GB2024-10-11 19:56
261

docker.io/paddlepaddle/paddle:2.5.0-gpu-cuda12.0-cudnn8.9-trt8.6

linux/amd64 docker.io22.04GB2025-01-17 01:39
210
186

docker.io/paddlepaddle/paddle:2.6.1

linux/amd64 docker.io4.66GB2025-04-13 21:10
191

docker.io/paddlepaddle/paddle:2.2.2-gpu-cuda10.2-cudnn7

linux/amd64 docker.io9.38GB2025-05-29 16:34
49

docker.io/paddlepaddle/paddle:2.6.2-gpu-cuda11.2-cudnn8.2-trt8.0

linux/amd64 docker.io21.56GB2025-06-19 14:18
5

docker.io/paddlepaddle/paddle:2.6.2-gpu-cuda11.7-cudnn8.4-trt8.4

linux/amd64 docker.io21.14GB2025-06-19 14:58
4

docker.io/paddlepaddle/paddle:2.6.2-gpu-cuda12.0-cudnn8.9-trt8.6

linux/amd64 docker.io34.04GB2025-06-20 02:33
2

docker.io/paddlepaddle/paddle:3.0.0-gpu-cuda12.6-cudnn9.5-trt10.5

linux/amd64 docker.io43.07GB2025-06-20 04:33
1

docker.io/paddlepaddle/paddle:3.0.0-gpu-cuda11.8-cudnn8.9-trt8.6

linux/amd64 docker.io30.76GB2025-06-20 05:04
1