docker.io/xprobe/xinference:v3.3.0 - 镜像下载

docker.io/xprobe/xinference:v3.3.0

linux/amd64 docker.io

XinInference 是一个基于 Docker 的容器镜像，旨在提供一个简单、易用的机器学习推断环境。该镜像包含了 TensorFlow、PyTorch 和 scikit-learn 等常见的深度学习框架，可以用来快速 prototyping 和开发机器学习模型。

浏览次数

13.68GB

镜像大小

国内镜像

swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/xprobe/xinference:v3.3.0

源镜像

docker.io/xprobe/xinference:v3.3.0

镜像ID

sha256:618ea479d4e65e732379298c77d6481e20c5e05c68b114c717d6ef9cb82f3b68

镜像 TAG

v3.3.0

镜像大小

13.68GB

平台架构

linux/amd64

镜像源

docker.io

项目信息

Hub 主页所有 TAG

CMD

/bin/bash

启动入口

工作目录

/opt/inference

OS/平台

linux/amd64

镜像创建

2026-08-30T12:35:03.973699374Z

同步时间

2026-09-11 00:57

浏览量

31 次

贡献者

⚙️ 环境变量 36

Key	Value
`PATH=/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin`	`0`
`NVARCH=x86_64`	`1`
NVIDIA_REQUIRE_CUDA=cuda>=13.0 brand=unknown,driver>=535,driver<536 brand=grid,driver>=535,driver<536 brand=tesla,driver>=535,driver<536 brand=nvidia,driver>=535,driver<536 brand=quadro,driver>=535,driver<536 brand=quadrortx,driver>=535,driver<536 brand=nvidiartx,driver>=535,driver<536 brand=vapps,driver>=535,driver<536 brand=vpc,driver>=535,driver<536 brand=vcs,driver>=535,driver<536 brand=vws,driver>=535,driver<536 brand=cloudgaming,driver>=535,driver<536 brand=unknown,driver>=550,driver<551 brand=grid,driver>=550,driver<551 brand=tesla,driver>=550,driver<551 brand=nvidia,driver>=550,driver<551 brand=quadro,driver>=550,driver<551 brand=quadrortx,driver>=550,driver<551 brand=nvidiartx,driver>=550,driver<551 brand=vapps,driver>=550,driver<551 brand=vpc,driver>=550,driver<551 brand=vcs,driver>=550,driver<551 brand=vws,driver>=550,driver<551 brand=cloudgaming,driver>=550,driver<551 brand=unknown,driver>=565,driver<566 brand=grid,driver>=565,driver<566 brand=tesla,driver>=565,driver<566 brand=nvidia,driver>=565,driver<566 brand=quadro,driver>=565,driver<566 brand=quadrortx,driver>=565,driver<566 brand=nvidiartx,driver>=565,driver<566 brand=vapps,driver>=565,driver<566 brand=vpc,driver>=565,driver<566 brand=vcs,driver>=565,driver<566 brand=vws,driver>=565,driver<566 brand=cloudgaming,driver>=565,driver<566 brand=unknown,driver>=570,driver<571 brand=grid,driver>=570,driver<571 brand=tesla,driver>=570,driver<571 brand=nvidia,driver>=570,driver<571 brand=quadro,driver>=570,driver<571 brand=quadrortx,driver>=570,driver<571 brand=nvidiartx,driver>=570,driver<571 brand=vapps,driver>=570,driver<571 brand=vpc,driver>=570,driver<571 brand=vcs,driver>=570,driver<571 brand=vws,driver>=570,driver<571 brand=cloudgaming,driver>=570,driver<571 brand=unknown,driver>=575,driver<576 brand=grid,driver>=575,driver<576 brand=tesla,driver>=575,driver<576 brand=nvidia,driver>=575,driver<576 brand=quadro,driver>=575,driver<576 brand=quadrortx,driver>=575,driver<576 brand=nvidiartx,driver>=575,driver<576 brand=vapps,driver>=575,driver<576 brand=vpc,driver>=575,driver<576 brand=vcs,driver>=575,driver<576 brand=vws,driver>=575,driver<576 brand=cloudgaming,driver>=575,driver<576	`2`
`NV_CUDA_CUDART_VERSION=13.0.96-1`	`3`
`CUDA_VERSION=13.0.2`	`4`
`LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64:/usr/local/cuda/lib64`	`5`
`NVIDIA_VISIBLE_DEVICES=all`	`6`
`NVIDIA_DRIVER_CAPABILITIES=compute,utility`	`7`
`NV_CUDA_LIB_VERSION=13.0.2-1`	`8`
`NV_NVTX_VERSION=13.0.85-1`	`9`
`NV_LIBNPP_VERSION=13.0.1.2-1`	`10`
`NV_LIBNPP_PACKAGE=libnpp-13-0=13.0.1.2-1`	`11`
`NV_LIBCUSPARSE_VERSION=12.6.3.3-1`	`12`
`NV_LIBCUBLAS_PACKAGE_NAME=libcublas-13-0`	`13`
`NV_LIBCUBLAS_VERSION=13.1.0.3-1`	`14`
`NV_LIBCUBLAS_PACKAGE=libcublas-13-0=13.1.0.3-1`	`15`
`NV_LIBNCCL_PACKAGE_NAME=libnccl2`	`16`
`NV_LIBNCCL_PACKAGE_VERSION=2.28.3-1`	`17`
`NCCL_VERSION=2.28.3-1`	`18`
`NV_LIBNCCL_PACKAGE=libnccl2=2.28.3-1+cuda13.0`	`19`
`NVIDIA_PRODUCT_NAME=CUDA`	`20`
`NV_CUDA_CUDART_DEV_VERSION=13.0.96-1`	`21`
`NV_NVML_DEV_VERSION=13.0.87-1`	`22`
`NV_LIBCUSPARSE_DEV_VERSION=12.6.3.3-1`	`23`
`NV_LIBNPP_DEV_VERSION=13.0.1.2-1`	`24`
`NV_LIBNPP_DEV_PACKAGE=libnpp-dev-13-0=13.0.1.2-1`	`25`
`NV_LIBCUBLAS_DEV_VERSION=13.1.0.3-1`	`26`
`NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-13-0`	`27`
`NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-13-0=13.1.0.3-1`	`28`
`NV_CUDA_NSIGHT_COMPUTE_VERSION=13.0.2-1`	`29`
`NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE=cuda-nsight-compute-13-0=13.0.2-1`	`30`
`NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev`	`31`
`NV_LIBNCCL_DEV_PACKAGE_VERSION=2.28.3-1`	`32`
`NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.28.3-1+cuda13.0`	`33`
`LIBRARY_PATH=/usr/local/cuda/lib64/stubs`	`34`
`DEBIAN_FRONTEND=noninteractive`	`35`

🏷️ 镜像标签 3

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

🛡️ 镜像安全扫描

ubuntu 22.04 Trivy 2026-09-11 00:59 查看完整报告

560

低危 LOW

4772

中危 MEDIUM

406

高危 HIGH

严重 CRITICAL

受影响目标 (6)

docker.io/xprobe/xinference:v3.3.0 (ubuntu 22.04) ubuntu Node.js node-pkg Python python-pkg opt/nvidia/nsight-compute/2025.3.1/host/target-linux-x64/plugins/efa_metrics/nic_sampler gobinary usr/local/bin/uv rustbinary usr/local/bin/uvx rustbinary

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无权限下载？点我修复生成 Docker Run 命令生成 Kubernetes YAML

Docker拉取命令

docker pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/xprobe/xinference:v3.3.0
docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/xprobe/xinference:v3.3.0  docker.io/xprobe/xinference:v3.3.0

Containerd拉取命令

ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/xprobe/xinference:v3.3.0
ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/xprobe/xinference:v3.3.0  docker.io/xprobe/xinference:v3.3.0

Shell快速替换命令

sed -i 's#xprobe/xinference:v3.3.0#swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/xprobe/xinference:v3.3.0#' 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/xprobe/xinference:v3.3.0 && docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/xprobe/xinference:v3.3.0  docker.io/xprobe/xinference:v3.3.0'

Ansible快速分发-Containerd

#ansible k8s -m shell -a 'ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/xprobe/xinference:v3.3.0 && ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/xprobe/xinference:v3.3.0  docker.io/xprobe/xinference:v3.3.0'

镜像构建历史


# 2026-08-30 20:35:03  0.00B 设置默认要执行的命令
CMD ["/bin/bash"]
                        
# 2026-08-30 20:35:03  0.00B 配置容器启动时运行的命令
ENTRYPOINT []
                        
# 2026-08-30 20:35:03  191.69MB 执行命令并创建新的镜像层
RUN |2 PIP_INDEX=https://pypi.org/simple TORCH_INDEX=https://download.pytorch.org/whl/cu130 /bin/sh -c NO_WEB_UI=1 uv pip install --system --no-deps --reinstall "." # buildkit
                        
# 2026-08-30 20:34:54  5.76MB 复制新文件或目录到容器中
COPY /opt/inference/xinference/ui/web/dist /opt/inference/xinference/ui/web/dist # buildkit
                        
# 2026-08-30 20:34:54  195.96MB 复制新文件或目录到容器中
COPY . /opt/inference # buildkit
                        
# 2026-08-30 20:34:51  401.50MB 执行命令并创建新的镜像层
RUN |2 PIP_INDEX=https://pypi.org/simple TORCH_INDEX=https://download.pytorch.org/whl/cu130 /bin/sh -c touch README.md &&     pip install -i "$PIP_INDEX" uv &&     XINFERENCE_SKIP_MODEL_SPEC_VALIDATION=1 NO_WEB_UI=1       uv pip install --system --index-url "$PIP_INDEX"       --extra-index-url "$TORCH_INDEX" --index-strategy unsafe-best-match       --constraint /opt/requirements-runtime.txt       ".[otel]" transformers accelerate # buildkit
                        
# 2026-08-30 20:34:44  1.61KB 复制新文件或目录到容器中
COPY xinference/__init__.py ./xinference/ # buildkit
                        
# 2026-08-30 20:34:44  19.82KB 复制新文件或目录到容器中
COPY pyproject.toml build_backend.py build_web.py ./ # buildkit
                        
# 2026-08-30 20:34:44  0.00B 设置工作目录为/opt/inference
WORKDIR /opt/inference
                        
# 2026-08-30 20:34:44  5.02GB 执行命令并创建新的镜像层
RUN |2 PIP_INDEX=https://pypi.org/simple TORCH_INDEX=https://download.pytorch.org/whl/cu130 /bin/sh -c pip install -i "$PIP_INDEX" --upgrade pip "setuptools<82" wheel &&     pip install --constraint /opt/requirements-runtime.txt       torch torchvision torchaudio torchcodec --index-url "$TORCH_INDEX" &&     pip install --constraint /opt/requirements-runtime.txt       -i "$PIP_INDEX" numpy pandas # buildkit
                        
# 2026-08-30 20:33:41  489.00B 复制新文件或目录到容器中
COPY xinference/deploy/docker/requirements-runtime.txt /opt/requirements-runtime.txt # buildkit
                        
# 2026-08-30 20:33:41  515.17MB 执行命令并创建新的镜像层
RUN |2 PIP_INDEX=https://pypi.org/simple TORCH_INDEX=https://download.pytorch.org/whl/cu130 /bin/sh -c apt-get update &&     apt-get install -y --no-install-recommends ca-certificates curl gnupg &&     curl -fsSL "https://keyserver.ubuntu.com/pks/lookup?op=get&search=0xF23C5A6CF475977595C89F51BA6932366A755776"       | gpg --dearmor -o /usr/share/keyrings/deadsnakes.gpg &&     echo "deb [signed-by=/usr/share/keyrings/deadsnakes.gpg] https://ppa.launchpadcontent.net/deadsnakes/ppa/ubuntu jammy main"       > /etc/apt/sources.list.d/deadsnakes.list &&     apt-get update &&     apt-get install -y --no-install-recommends       python3.12 python3.12-dev python3.12-venv       build-essential ninja-build git procps       ffmpeg libsndfile1 libgl1 libglib2.0-0 &&     ln -sf /usr/bin/python3.12 /usr/local/bin/python3 &&     ln -sf /usr/bin/python3.12 /usr/local/bin/python &&     curl -sS https://bootstrap.pypa.io/get-pip.py | python3 &&     apt-get clean && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2026-08-30 20:33:41  0.00B 设置环境变量 DEBIAN_FRONTEND
ENV DEBIAN_FRONTEND=noninteractive
                        
# 2026-08-30 20:33:41  0.00B 定义构建参数
ARG TORCH_INDEX=https://download.pytorch.org/whl/cu130
                        
# 2026-08-30 20:33:41  0.00B 定义构建参数
ARG PIP_INDEX=https://pypi.org/simple
                        
# 2025-10-11 01:02:53  0.00B 设置环境变量 LIBRARY_PATH
ENV LIBRARY_PATH=/usr/local/cuda/lib64/stubs
                        
# 2025-10-11 01:02:53  390.91KB 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
                        
# 2025-10-11 01:02:53  4.82GB 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     cuda-cudart-dev-13-0=${NV_CUDA_CUDART_DEV_VERSION}     cuda-command-line-tools-13-0=${NV_CUDA_LIB_VERSION}     cuda-minimal-build-13-0=${NV_CUDA_LIB_VERSION}     cuda-libraries-dev-13-0=${NV_CUDA_LIB_VERSION}     cuda-nvml-dev-13-0=${NV_NVML_DEV_VERSION}     ${NV_LIBNPP_DEV_PACKAGE}     libcusparse-dev-13-0=${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
                        
# 2025-10-11 01:02:53  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2025-10-11 01:02:53  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2025-10-11 01:02:53  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE
ENV NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.28.3-1+cuda13.0
                        
# 2025-10-11 01:02:53  0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.28.3-1
                        
# 2025-10-11 01:02:53  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE_VERSION
ENV NV_LIBNCCL_DEV_PACKAGE_VERSION=2.28.3-1
                        
# 2025-10-11 01:02:53  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE_NAME
ENV NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev
                        
# 2025-10-11 01:02:53  0.00B 设置环境变量 NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE
ENV NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE=cuda-nsight-compute-13-0=13.0.2-1
                        
# 2025-10-11 01:02:53  0.00B 设置环境变量 NV_CUDA_NSIGHT_COMPUTE_VERSION
ENV NV_CUDA_NSIGHT_COMPUTE_VERSION=13.0.2-1
                        
# 2025-10-11 01:02:53  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_PACKAGE
ENV NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-13-0=13.1.0.3-1
                        
# 2025-10-11 01:02:53  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_PACKAGE_NAME
ENV NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-13-0
                        
# 2025-10-11 01:02:53  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_VERSION
ENV NV_LIBCUBLAS_DEV_VERSION=13.1.0.3-1
                        
# 2025-10-11 01:02:53  0.00B 设置环境变量 NV_LIBNPP_DEV_PACKAGE
ENV NV_LIBNPP_DEV_PACKAGE=libnpp-dev-13-0=13.0.1.2-1
                        
# 2025-10-11 01:02:53  0.00B 设置环境变量 NV_LIBNPP_DEV_VERSION
ENV NV_LIBNPP_DEV_VERSION=13.0.1.2-1
                        
# 2025-10-11 01:02:53  0.00B 设置环境变量 NV_LIBCUSPARSE_DEV_VERSION
ENV NV_LIBCUSPARSE_DEV_VERSION=12.6.3.3-1
                        
# 2025-10-11 01:02:53  0.00B 设置环境变量 NV_NVML_DEV_VERSION
ENV NV_NVML_DEV_VERSION=13.0.87-1
                        
# 2025-10-11 01:02:53  0.00B 设置环境变量 NV_CUDA_CUDART_DEV_VERSION
ENV NV_CUDA_CUDART_DEV_VERSION=13.0.96-1
                        
# 2025-10-11 01:02:53  0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=13.0.2-1
                        
# 2025-10-11 00:53:39  0.00B 配置容器启动时运行的命令
ENTRYPOINT ["/opt/nvidia/nvidia_entrypoint.sh"]
                        
# 2025-10-11 00:53:39  0.00B 设置环境变量 NVIDIA_PRODUCT_NAME
ENV NVIDIA_PRODUCT_NAME=CUDA
                        
# 2025-10-11 00:53:39  2.53KB 复制新文件或目录到容器中
COPY nvidia_entrypoint.sh /opt/nvidia/ # buildkit
                        
# 2025-10-11 00:53:39  3.06KB 复制新文件或目录到容器中
COPY entrypoint.d/ /opt/nvidia/entrypoint.d/ # buildkit
                        
# 2025-10-11 00:53:39  263.08KB 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
                        
# 2025-10-11 00:53:39  2.12GB 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-13-0=${NV_CUDA_LIB_VERSION}     ${NV_LIBNPP_PACKAGE}     cuda-nvtx-13-0=${NV_NVTX_VERSION}     libcusparse-13-0=${NV_LIBCUSPARSE_VERSION}     ${NV_LIBCUBLAS_PACKAGE}     ${NV_LIBNCCL_PACKAGE}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2025-10-11 00:53:39  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2025-10-11 00:53:39  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2025-10-11 00:53:39  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE
ENV NV_LIBNCCL_PACKAGE=libnccl2=2.28.3-1+cuda13.0
                        
# 2025-10-11 00:53:39  0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.28.3-1
                        
# 2025-10-11 00:53:39  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_VERSION
ENV NV_LIBNCCL_PACKAGE_VERSION=2.28.3-1
                        
# 2025-10-11 00:53:39  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_NAME
ENV NV_LIBNCCL_PACKAGE_NAME=libnccl2
                        
# 2025-10-11 00:53:39  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE
ENV NV_LIBCUBLAS_PACKAGE=libcublas-13-0=13.1.0.3-1
                        
# 2025-10-11 00:53:39  0.00B 设置环境变量 NV_LIBCUBLAS_VERSION
ENV NV_LIBCUBLAS_VERSION=13.1.0.3-1
                        
# 2025-10-11 00:53:39  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE_NAME
ENV NV_LIBCUBLAS_PACKAGE_NAME=libcublas-13-0
                        
# 2025-10-11 00:53:39  0.00B 设置环境变量 NV_LIBCUSPARSE_VERSION
ENV NV_LIBCUSPARSE_VERSION=12.6.3.3-1
                        
# 2025-10-11 00:53:39  0.00B 设置环境变量 NV_LIBNPP_PACKAGE
ENV NV_LIBNPP_PACKAGE=libnpp-13-0=13.0.1.2-1
                        
# 2025-10-11 00:53:39  0.00B 设置环境变量 NV_LIBNPP_VERSION
ENV NV_LIBNPP_VERSION=13.0.1.2-1
                        
# 2025-10-11 00:53:39  0.00B 设置环境变量 NV_NVTX_VERSION
ENV NV_NVTX_VERSION=13.0.85-1
                        
# 2025-10-11 00:53:39  0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=13.0.2-1
                        
# 2025-10-11 00:48:27  0.00B 设置环境变量 NVIDIA_DRIVER_CAPABILITIES
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
                        
# 2025-10-11 00:48:27  0.00B 设置环境变量 NVIDIA_VISIBLE_DEVICES
ENV NVIDIA_VISIBLE_DEVICES=all
                        
# 2025-10-11 00:48:27  17.29KB 复制新文件或目录到容器中
COPY NGC-DL-CONTAINER-LICENSE / # buildkit
                        
# 2025-10-11 00:48:27  0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64:/usr/local/cuda/lib64
                        
# 2025-10-11 00:48:27  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
                        
# 2025-10-11 00:48:27  22.00B 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c echo "/usr/local/cuda/lib64" >> /etc/ld.so.conf.d/nvidia.conf # buildkit
                        
# 2025-10-11 00:48:27  322.88MB 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-13-0=${NV_CUDA_CUDART_VERSION}     cuda-compat-13-0     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2025-10-11 00:48:05  0.00B 设置环境变量 CUDA_VERSION
ENV CUDA_VERSION=13.0.2
                        
# 2025-10-11 00:48:05  10.60MB 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_1.1-1_all.deb &&     dpkg -i cuda-keyring_1.1-1_all.deb &&     apt-get purge --autoremove -y curl     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2025-10-11 00:48:05  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2025-10-11 00:48:05  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2025-10-11 00:48:05  0.00B 设置环境变量 NV_CUDA_CUDART_VERSION
ENV NV_CUDA_CUDART_VERSION=13.0.96-1
                        
# 2025-10-11 00:48:05  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 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>=13.0 brand=unknown,driver>=535,driver<536 brand=grid,driver>=535,driver<536 brand=tesla,driver>=535,driver<536 brand=nvidia,driver>=535,driver<536 brand=quadro,driver>=535,driver<536 brand=quadrortx,driver>=535,driver<536 brand=nvidiartx,driver>=535,driver<536 brand=vapps,driver>=535,driver<536 brand=vpc,driver>=535,driver<536 brand=vcs,driver>=535,driver<536 brand=vws,driver>=535,driver<536 brand=cloudgaming,driver>=535,driver<536 brand=unknown,driver>=550,driver<551 brand=grid,driver>=550,driver<551 brand=tesla,driver>=550,driver<551 brand=nvidia,driver>=550,driver<551 brand=quadro,driver>=550,driver<551 brand=quadrortx,driver>=550,driver<551 brand=nvidiartx,driver>=550,driver<551 brand=vapps,driver>=550,driver<551 brand=vpc,driver>=550,driver<551 brand=vcs,driver>=550,driver<551 brand=vws,driver>=550,driver<551 brand=cloudgaming,driver>=550,driver<551 brand=unknown,driver>=565,driver<566 brand=grid,driver>=565,driver<566 brand=tesla,driver>=565,driver<566 brand=nvidia,driver>=565,driver<566 brand=quadro,driver>=565,driver<566 brand=quadrortx,driver>=565,driver<566 brand=nvidiartx,driver>=565,driver<566 brand=vapps,driver>=565,driver<566 brand=vpc,driver>=565,driver<566 brand=vcs,driver>=565,driver<566 brand=vws,driver>=565,driver<566 brand=cloudgaming,driver>=565,driver<566 brand=unknown,driver>=570,driver<571 brand=grid,driver>=570,driver<571 brand=tesla,driver>=570,driver<571 brand=nvidia,driver>=570,driver<571 brand=quadro,driver>=570,driver<571 brand=quadrortx,driver>=570,driver<571 brand=nvidiartx,driver>=570,driver<571 brand=vapps,driver>=570,driver<571 brand=vpc,driver>=570,driver<571 brand=vcs,driver>=570,driver<571 brand=vws,driver>=570,driver<571 brand=cloudgaming,driver>=570,driver<571 brand=unknown,driver>=575,driver<576 brand=grid,driver>=575,driver<576 brand=tesla,driver>=575,driver<576 brand=nvidia,driver>=575,driver<576 brand=quadro,driver>=575,driver<576 brand=quadrortx,driver>=575,driver<576 brand=nvidiartx,driver>=575,driver<576 brand=vapps,driver>=575,driver<576 brand=vpc,driver>=575,driver<576 brand=vcs,driver>=575,driver<576 brand=vws,driver>=575,driver<576 brand=cloudgaming,driver>=575,driver<576
                        
# 2025-10-11 00:48:05  0.00B 设置环境变量 NVARCH
ENV NVARCH=x86_64
                        
# 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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    "RepoDigests": [
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    "Parent": "",
    "Comment": "buildkit.dockerfile.v0",
    "Created": "2026-08-30T12:35:03.973699374Z",
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    "ContainerConfig": null,
    "DockerVersion": "",
    "Author": "",
    "Config": {
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        "Domainname": "",
        "User": "",
        "AttachStdin": false,
        "AttachStdout": false,
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        "OpenStdin": false,
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        "Env": [
            "PATH=/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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