docker.io/pytorch/pytorch:1.13.0-cuda11.6-cudnn8-devel linux/amd64

docker.io/pytorch/pytorch:1.13.0-cuda11.6-cudnn8-devel - 国内下载镜像源 浏览次数:15 安全受验证的发布者-Pytorch

PyTorch是一个深度学习框架,旨在简化机器学习算法的实现和部署。该镜像提供了一个基于Python 3.x的环境,可以用于快速启动和测试PyTorch项目。

源镜像 docker.io/pytorch/pytorch:1.13.0-cuda11.6-cudnn8-devel
国内镜像 swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:1.13.0-cuda11.6-cudnn8-devel
镜像ID sha256:632278b723126cc8119ed651bdf5614dcc3460976b3f513d43ae33ed839dc94b
镜像TAG 1.13.0-cuda11.6-cudnn8-devel
大小 18.57GB
镜像源 docker.io
项目信息 Docker-Hub主页 🚀项目TAG 🚀
CMD bash
启动入口
工作目录 /workspace
OS/平台 linux/amd64
浏览量 15 次
贡献者 29******3@qq.com
镜像创建 2022-10-28T10:13:08.371420506-07:00
同步时间 2025-11-10 00:45
更新时间 2025-11-10 13:47
环境变量
PATH=/opt/conda/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>=11.6 brand=tesla,driver>=418,driver<419 brand=tesla,driver>=450,driver<451 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 NV_CUDA_CUDART_VERSION=11.6.55-1 NV_CUDA_COMPAT_PACKAGE=cuda-compat-11-6 CUDA_VERSION=11.6.2 LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64 NVIDIA_VISIBLE_DEVICES=all NVIDIA_DRIVER_CAPABILITIES=compute,utility NV_CUDA_LIB_VERSION=11.6.2-1 NV_NVTX_VERSION=11.6.124-1 NV_LIBNPP_VERSION=11.6.3.124-1 NV_LIBNPP_PACKAGE=libnpp-11-6=11.6.3.124-1 NV_LIBCUSPARSE_VERSION=11.7.2.124-1 NV_LIBCUBLAS_PACKAGE_NAME=libcublas-11-6 NV_LIBCUBLAS_VERSION=11.9.2.110-1 NV_LIBCUBLAS_PACKAGE=libcublas-11-6=11.9.2.110-1 NV_LIBNCCL_PACKAGE_NAME=libnccl2 NV_LIBNCCL_PACKAGE_VERSION=2.12.10-1 NCCL_VERSION=2.12.10-1 NV_LIBNCCL_PACKAGE=libnccl2=2.12.10-1+cuda11.6 NV_CUDA_CUDART_DEV_VERSION=11.6.55-1 NV_NVML_DEV_VERSION=11.6.55-1 NV_LIBCUSPARSE_DEV_VERSION=11.7.2.124-1 NV_LIBNPP_DEV_VERSION=11.6.3.124-1 NV_LIBNPP_DEV_PACKAGE=libnpp-dev-11-6=11.6.3.124-1 NV_LIBCUBLAS_DEV_VERSION=11.9.2.110-1 NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-11-6 NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-11-6=11.9.2.110-1 NV_NVPROF_VERSION=11.6.124-1 NV_NVPROF_DEV_PACKAGE=cuda-nvprof-11-6=11.6.124-1 NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev NV_LIBNCCL_DEV_PACKAGE_VERSION=2.12.10-1 NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.12.10-1+cuda11.6 LIBRARY_PATH=/usr/local/cuda/lib64/stubs NV_CUDNN_VERSION=8.4.0.27 NV_CUDNN_PACKAGE_NAME=libcudnn8 NV_CUDNN_PACKAGE=libcudnn8=8.4.0.27-1+cuda11.6 NV_CUDNN_PACKAGE_DEV=libcudnn8-dev=8.4.0.27-1+cuda11.6 PYTORCH_VERSION=v1.13.0
镜像标签
8.4.0.27: com.nvidia.cudnn.version nvidia_driver: com.nvidia.volumes.needed NVIDIA CORPORATION <cudatools@nvidia.com>: maintainer

Docker拉取命令

docker pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:1.13.0-cuda11.6-cudnn8-devel
docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:1.13.0-cuda11.6-cudnn8-devel  docker.io/pytorch/pytorch:1.13.0-cuda11.6-cudnn8-devel

Containerd拉取命令

ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:1.13.0-cuda11.6-cudnn8-devel
ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:1.13.0-cuda11.6-cudnn8-devel  docker.io/pytorch/pytorch:1.13.0-cuda11.6-cudnn8-devel

Shell快速替换命令

sed -i 's#pytorch/pytorch:1.13.0-cuda11.6-cudnn8-devel#swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:1.13.0-cuda11.6-cudnn8-devel#' 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/pytorch/pytorch:1.13.0-cuda11.6-cudnn8-devel && docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:1.13.0-cuda11.6-cudnn8-devel  docker.io/pytorch/pytorch:1.13.0-cuda11.6-cudnn8-devel'

Ansible快速分发-Containerd

#ansible k8s -m shell -a 'ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:1.13.0-cuda11.6-cudnn8-devel && ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:1.13.0-cuda11.6-cudnn8-devel  docker.io/pytorch/pytorch:1.13.0-cuda11.6-cudnn8-devel'

镜像构建历史


# 2022-10-29 01:13:08  0.00B 设置工作目录为/workspace
WORKDIR /workspace
                        
# 2022-10-29 01:13:07  0.00B 设置环境变量 PYTORCH_VERSION
ENV PYTORCH_VERSION=v1.13.0
                        
# 2022-10-29 01:13:07  0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64
                        
# 2022-10-29 01:13:07  0.00B 设置环境变量 NVIDIA_DRIVER_CAPABILITIES
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
                        
# 2022-10-29 01:13:07  0.00B 设置环境变量 NVIDIA_VISIBLE_DEVICES
ENV NVIDIA_VISIBLE_DEVICES=all
                        
# 2022-10-29 01:13:07  0.00B 设置环境变量 PATH
ENV PATH=/opt/conda/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
                        
# 2022-10-29 01:13:07  10.91GB 复制新文件或目录到容器中
COPY /opt/conda /opt/conda # buildkit
                        
# 2022-10-29 00:56:10  2.99MB 执行命令并创建新的镜像层
RUN |1 PYTORCH_VERSION=v1.13.0 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends         ca-certificates         libjpeg-dev         libpng-dev &&     rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2022-10-29 00:56:10  0.00B 添加元数据标签
LABEL com.nvidia.volumes.needed=nvidia_driver
                        
# 2022-10-29 00:56:10  0.00B 定义构建参数
ARG PYTORCH_VERSION
                        
# 2022-10-28 11:32:39  2.81GB 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
                        
# 2022-10-28 11:32:39  0.00B 添加元数据标签
LABEL com.nvidia.cudnn.version=8.4.0.27
                        
# 2022-10-28 11:32:39  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2022-10-28 11:32:39  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2022-10-28 11:32:39  0.00B 设置环境变量 NV_CUDNN_PACKAGE_DEV
ENV NV_CUDNN_PACKAGE_DEV=libcudnn8-dev=8.4.0.27-1+cuda11.6
                        
# 2022-10-28 11:32:39  0.00B 设置环境变量 NV_CUDNN_PACKAGE
ENV NV_CUDNN_PACKAGE=libcudnn8=8.4.0.27-1+cuda11.6
                        
# 2022-10-28 11:32:39  0.00B 设置环境变量 NV_CUDNN_PACKAGE_NAME
ENV NV_CUDNN_PACKAGE_NAME=libcudnn8
                        
# 2022-10-28 11:32:39  0.00B 设置环境变量 NV_CUDNN_VERSION
ENV NV_CUDNN_VERSION=8.4.0.27
                        
# 2022-10-28 07:20:17  0.00B 设置环境变量 LIBRARY_PATH
ENV LIBRARY_PATH=/usr/local/cuda/lib64/stubs
                        
# 2022-10-28 07:20:17  371.24KB 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
                        
# 2022-10-28 07:20:16  2.81GB 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-11-6=${NV_CUDA_CUDART_DEV_VERSION}     cuda-command-line-tools-11-6=${NV_CUDA_LIB_VERSION}     cuda-minimal-build-11-6=${NV_CUDA_LIB_VERSION}     cuda-libraries-dev-11-6=${NV_CUDA_LIB_VERSION}     cuda-nvml-dev-11-6=${NV_NVML_DEV_VERSION}     ${NV_NVPROF_DEV_PACKAGE}     ${NV_LIBNPP_DEV_PACKAGE}     libcusparse-dev-11-6=${NV_LIBCUSPARSE_DEV_VERSION}     ${NV_LIBCUBLAS_DEV_PACKAGE}     ${NV_LIBNCCL_DEV_PACKAGE}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2022-10-28 07:20:16  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2022-10-28 07:20:16  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2022-10-28 07:20:16  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE
ENV NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.12.10-1+cuda11.6
                        
# 2022-10-28 07:20:16  0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.12.10-1
                        
# 2022-10-28 07:20:16  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE_VERSION
ENV NV_LIBNCCL_DEV_PACKAGE_VERSION=2.12.10-1
                        
# 2022-10-28 07:20:16  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE_NAME
ENV NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev
                        
# 2022-10-28 07:20:16  0.00B 设置环境变量 NV_NVPROF_DEV_PACKAGE
ENV NV_NVPROF_DEV_PACKAGE=cuda-nvprof-11-6=11.6.124-1
                        
# 2022-10-28 07:20:16  0.00B 设置环境变量 NV_NVPROF_VERSION
ENV NV_NVPROF_VERSION=11.6.124-1
                        
# 2022-10-28 07:20:16  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_PACKAGE
ENV NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-11-6=11.9.2.110-1
                        
# 2022-10-28 07:20:16  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_PACKAGE_NAME
ENV NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-11-6
                        
# 2022-10-28 07:20:16  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_VERSION
ENV NV_LIBCUBLAS_DEV_VERSION=11.9.2.110-1
                        
# 2022-10-28 07:20:16  0.00B 设置环境变量 NV_LIBNPP_DEV_PACKAGE
ENV NV_LIBNPP_DEV_PACKAGE=libnpp-dev-11-6=11.6.3.124-1
                        
# 2022-10-28 07:20:16  0.00B 设置环境变量 NV_LIBNPP_DEV_VERSION
ENV NV_LIBNPP_DEV_VERSION=11.6.3.124-1
                        
# 2022-10-28 07:20:16  0.00B 设置环境变量 NV_LIBCUSPARSE_DEV_VERSION
ENV NV_LIBCUSPARSE_DEV_VERSION=11.7.2.124-1
                        
# 2022-10-28 07:20:16  0.00B 设置环境变量 NV_NVML_DEV_VERSION
ENV NV_NVML_DEV_VERSION=11.6.55-1
                        
# 2022-10-28 07:20:16  0.00B 设置环境变量 NV_CUDA_CUDART_DEV_VERSION
ENV NV_CUDA_CUDART_DEV_VERSION=11.6.55-1
                        
# 2022-10-28 07:20:16  0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=11.6.2-1
                        
# 2022-10-28 07:10:11  258.48KB 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
                        
# 2022-10-28 07:10:11  1.89GB 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-11-6=${NV_CUDA_LIB_VERSION}     ${NV_LIBNPP_PACKAGE}     cuda-nvtx-11-6=${NV_NVTX_VERSION}     libcusparse-11-6=${NV_LIBCUSPARSE_VERSION}     ${NV_LIBCUBLAS_PACKAGE}     ${NV_LIBNCCL_PACKAGE}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2022-10-28 07:10:11  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2022-10-28 07:10:11  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2022-10-28 07:10:11  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE
ENV NV_LIBNCCL_PACKAGE=libnccl2=2.12.10-1+cuda11.6
                        
# 2022-10-28 07:10:11  0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.12.10-1
                        
# 2022-10-28 07:10:11  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_VERSION
ENV NV_LIBNCCL_PACKAGE_VERSION=2.12.10-1
                        
# 2022-10-28 07:10:11  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_NAME
ENV NV_LIBNCCL_PACKAGE_NAME=libnccl2
                        
# 2022-10-28 07:10:11  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE
ENV NV_LIBCUBLAS_PACKAGE=libcublas-11-6=11.9.2.110-1
                        
# 2022-10-28 07:10:11  0.00B 设置环境变量 NV_LIBCUBLAS_VERSION
ENV NV_LIBCUBLAS_VERSION=11.9.2.110-1
                        
# 2022-10-28 07:10:11  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE_NAME
ENV NV_LIBCUBLAS_PACKAGE_NAME=libcublas-11-6
                        
# 2022-10-28 07:10:11  0.00B 设置环境变量 NV_LIBCUSPARSE_VERSION
ENV NV_LIBCUSPARSE_VERSION=11.7.2.124-1
                        
# 2022-10-28 07:10:11  0.00B 设置环境变量 NV_LIBNPP_PACKAGE
ENV NV_LIBNPP_PACKAGE=libnpp-11-6=11.6.3.124-1
                        
# 2022-10-28 07:10:11  0.00B 设置环境变量 NV_LIBNPP_VERSION
ENV NV_LIBNPP_VERSION=11.6.3.124-1
                        
# 2022-10-28 07:10:11  0.00B 设置环境变量 NV_NVTX_VERSION
ENV NV_NVTX_VERSION=11.6.124-1
                        
# 2022-10-28 07:10:11  0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=11.6.2-1
                        
# 2022-10-28 07:05:16  0.00B 设置环境变量 NVIDIA_DRIVER_CAPABILITIES
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
                        
# 2022-10-28 07:05:16  0.00B 设置环境变量 NVIDIA_VISIBLE_DEVICES
ENV NVIDIA_VISIBLE_DEVICES=all
                        
# 2022-10-28 07:05:16  16.05KB 复制新文件或目录到容器中
COPY NGC-DL-CONTAINER-LICENSE / # buildkit
                        
# 2022-10-28 07:05:16  0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64
                        
# 2022-10-28 07:05:16  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
                        
# 2022-10-28 07:05:16  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
                        
# 2022-10-28 07:05:16  62.89MB 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-11-6=${NV_CUDA_CUDART_VERSION}     ${NV_CUDA_COMPAT_PACKAGE}     && ln -s cuda-11.6 /usr/local/cuda &&     rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2022-10-28 07:05:02  0.00B 设置环境变量 CUDA_VERSION
ENV CUDA_VERSION=11.6.2
                        
# 2022-10-28 07:05:02  16.54MB 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/ubuntu1804/${NVARCH}/3bf863cc.pub | apt-key add - &&     echo "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/${NVARCH} /" > /etc/apt/sources.list.d/cuda.list &&     apt-get purge --autoremove -y curl     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2022-10-28 07:05:02  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2022-10-28 07:05:02  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2022-10-28 07:05:02  0.00B 设置环境变量 NV_CUDA_COMPAT_PACKAGE
ENV NV_CUDA_COMPAT_PACKAGE=cuda-compat-11-6
                        
# 2022-10-28 07:05:02  0.00B 设置环境变量 NV_CUDA_CUDART_VERSION
ENV NV_CUDA_CUDART_VERSION=11.6.55-1
                        
# 2022-10-28 07:05:02  0.00B 设置环境变量 NVIDIA_REQUIRE_CUDA brand brand brand brand brand brand brand brand brand brand brand brand
ENV NVIDIA_REQUIRE_CUDA=cuda>=11.6 brand=tesla,driver>=418,driver<419 brand=tesla,driver>=450,driver<451 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
                        
# 2022-10-28 07:05:02  0.00B 设置环境变量 NVARCH
ENV NVARCH=x86_64
                        
# 2022-10-25 09:53:28  0.00B 
/bin/sh -c #(nop)  CMD ["bash"]
                        
# 2022-10-25 09:53:28  63.15MB 
/bin/sh -c #(nop) ADD file:fc5d658c47ede58827812b75a311353be776e41e2dd339b8906839527c9b5247 in / 
                        
                    

镜像信息

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    "Id": "sha256:632278b723126cc8119ed651bdf5614dcc3460976b3f513d43ae33ed839dc94b",
    "RepoTags": [
        "pytorch/pytorch:1.13.0-cuda11.6-cudnn8-devel",
        "swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch:1.13.0-cuda11.6-cudnn8-devel"
    ],
    "RepoDigests": [
        "pytorch/pytorch@sha256:d98a1b1f61166875882e5a3ffa63bdef89c3349ceca1954dda415c5cd67e06a0",
        "swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pytorch/pytorch@sha256:d98a1b1f61166875882e5a3ffa63bdef89c3349ceca1954dda415c5cd67e06a0"
    ],
    "Parent": "",
    "Comment": "buildkit.dockerfile.v0",
    "Created": "2022-10-28T10:13:08.371420506-07:00",
    "Container": "",
    "ContainerConfig": null,
    "DockerVersion": "",
    "Author": "",
    "Config": {
        "Hostname": "",
        "Domainname": "",
        "User": "",
        "AttachStdin": false,
        "AttachStdout": false,
        "AttachStderr": false,
        "Tty": false,
        "OpenStdin": false,
        "StdinOnce": false,
        "Env": [
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}

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