docker.io/openmmlab/lmdeploy:v0.6.3.post1-cu12 linux/amd64

docker.io/openmmlab/lmdeploy:v0.6.3.post1-cu12 - 国内下载镜像源浏览次数:116

镜像描述：

lmdeploy

LM Deploy

LM Deploy 是 OpenMMLab 开发的用于模型部署和在线服务构建的工具。它提供了一个简洁易用的界面，帮助用户快速搭建和部署机器学习模型，包括图像分类、检测、分割等任务。在这个镜像中，你可以找到 LM Deploy 的相关组件和配置，以便你在自己的环境中使用和扩展它。

源镜像	docker.io/openmmlab/lmdeploy:v0.6.3.post1-cu12
国内镜像	swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/openmmlab/lmdeploy:v0.6.3.post1-cu12
镜像ID	sha256:c609d08df93290dd4c7cd1bc77bfa56d0263d96c8f2cb7f24bcef1908b3b7398
镜像TAG	v0.6.3.post1-cu12
大小	16.08GB
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	/opt/lmdeploy
OS/平台	linux/amd64
浏览量	116 次
贡献者
镜像创建	2024-11-26T09:30:55.940036652Z
同步时间	2024-11-30 00:20
更新时间	2025-02-22 01:09

环境变量

PATH=/opt/lmdeploy/install/bin:/opt/py3/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/openmpi/bin NVARCH=x86_64 NVIDIA_REQUIRE_CUDA=cuda>=12.4 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=12.4.127-1 NV_CUDA_COMPAT_PACKAGE=cuda-compat-12-4 CUDA_VERSION=12.4.1 LD_LIBRARY_PATH=/opt/lmdeploy/install/lib:/usr/local/nccl/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64:/usr/local/openmpi/lib NVIDIA_VISIBLE_DEVICES=all NVIDIA_DRIVER_CAPABILITIES=compute,utility NV_CUDA_LIB_VERSION=12.4.1-1 NV_NVTX_VERSION=12.4.127-1 NV_LIBNPP_VERSION=12.2.5.30-1 NV_LIBNPP_PACKAGE=libnpp-12-4=12.2.5.30-1 NV_LIBCUSPARSE_VERSION=12.3.1.170-1 NV_LIBCUBLAS_PACKAGE_NAME=libcublas-12-4 NV_LIBCUBLAS_VERSION=12.4.5.8-1 NV_LIBCUBLAS_PACKAGE=libcublas-12-4=12.4.5.8-1 NV_LIBNCCL_PACKAGE_NAME=libnccl2 NV_LIBNCCL_PACKAGE_VERSION=2.21.5-1 NCCL_VERSION=2.21.5-1 NV_LIBNCCL_PACKAGE=libnccl2=2.21.5-1+cuda12.4 NVIDIA_PRODUCT_NAME=CUDA NV_CUDA_CUDART_DEV_VERSION=12.4.127-1 NV_NVML_DEV_VERSION=12.4.127-1 NV_LIBCUSPARSE_DEV_VERSION=12.3.1.170-1 NV_LIBNPP_DEV_VERSION=12.2.5.30-1 NV_LIBNPP_DEV_PACKAGE=libnpp-dev-12-4=12.2.5.30-1 NV_LIBCUBLAS_DEV_VERSION=12.4.5.8-1 NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-12-4 NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-12-4=12.4.5.8-1 NV_CUDA_NSIGHT_COMPUTE_VERSION=12.4.1-1 NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE=cuda-nsight-compute-12-4=12.4.1-1 NV_NVPROF_VERSION=12.4.127-1 NV_NVPROF_DEV_PACKAGE=cuda-nvprof-12-4=12.4.127-1 NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev NV_LIBNCCL_DEV_PACKAGE_VERSION=2.21.5-1 NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.21.5-1+cuda12.4 LIBRARY_PATH=/usr/local/cuda/lib64/stubs CUDA_VERSION_SHORT=cu121 NCCL_LAUNCH_MODE=GROUP TRITON_PTXAS_PATH=/usr/local/cuda/bin/ptxas

镜像标签

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

镜像安全扫描查看Trivy扫描报告

系统OS: ubuntu 22.04 扫描引擎: Trivy 扫描时间: 2024-11-30 00:25

低危漏洞:192

中危漏洞:1586

高危漏洞:29

严重漏洞:0

docker.io/openmmlab/lmdeploy:v0.6.3.post1-cu12 (ubuntu 22.04) (ubuntu)

Node.js (node-pkg)

Python (python-pkg)

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Docker拉取命令无权限下载?点我修复

docker pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/openmmlab/lmdeploy:v0.6.3.post1-cu12
docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/openmmlab/lmdeploy:v0.6.3.post1-cu12  docker.io/openmmlab/lmdeploy:v0.6.3.post1-cu12

Containerd拉取命令

ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/openmmlab/lmdeploy:v0.6.3.post1-cu12
ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/openmmlab/lmdeploy:v0.6.3.post1-cu12  docker.io/openmmlab/lmdeploy:v0.6.3.post1-cu12

Shell快速替换命令

sed -i 's#openmmlab/lmdeploy:v0.6.3.post1-cu12#swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/openmmlab/lmdeploy:v0.6.3.post1-cu12#' 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/openmmlab/lmdeploy:v0.6.3.post1-cu12 && docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/openmmlab/lmdeploy:v0.6.3.post1-cu12  docker.io/openmmlab/lmdeploy:v0.6.3.post1-cu12'

Ansible快速分发-Containerd

#ansible k8s -m shell -a 'ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/openmmlab/lmdeploy:v0.6.3.post1-cu12 && ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/openmmlab/lmdeploy:v0.6.3.post1-cu12  docker.io/openmmlab/lmdeploy:v0.6.3.post1-cu12'

镜像构建历史


# 2024-11-26 17:30:55  0.00B 设置环境变量 TRITON_PTXAS_PATH
ENV TRITON_PTXAS_PATH=/usr/local/cuda/bin/ptxas
                        
# 2024-11-26 17:30:55  0.00B 设置环境变量 PATH
ENV PATH=/opt/lmdeploy/install/bin:/opt/py3/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/openmpi/bin
                        
# 2024-11-26 17:30:55  0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/opt/lmdeploy/install/lib:/usr/local/nccl/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64:/usr/local/openmpi/lib
                        
# 2024-11-26 17:30:55  0.00B 执行命令并创建新的镜像层
RUN |3 PYTHON_VERSION=3.10 TORCH_VERSION=2.3.0 TORCHVISION_VERSION=0.18.0 /bin/sh -c if [ "$CUDA_VERSION_SHORT" = "cu118" ]; then python3 -m pip uninstall -y nvidia-nccl-cu11 ; fi # buildkit
                        
# 2024-11-26 17:30:55  2.02GB 执行命令并创建新的镜像层
RUN |3 PYTHON_VERSION=3.10 TORCH_VERSION=2.3.0 TORCHVISION_VERSION=0.18.0 /bin/sh -c cd /opt/lmdeploy &&    python3 -m pip install -r requirements.txt &&    mkdir -p build && cd build &&    sh ../generate.sh &&    ninja -j$(nproc) && ninja install &&    cd .. &&    python3 -m pip install -e . &&    rm -rf build # buildkit
                        
# 2024-11-26 17:18:20  0.00B 设置工作目录为/opt/lmdeploy
WORKDIR /opt/lmdeploy
                        
# 2024-11-26 17:18:20  7.84MB 复制新文件或目录到容器中
COPY . /opt/lmdeploy # buildkit
                        
# 2024-11-26 17:18:20  0.00B 设置环境变量 NCCL_LAUNCH_MODE
ENV NCCL_LAUNCH_MODE=GROUP
                        
# 2024-11-26 17:18:20  5.27GB 执行命令并创建新的镜像层
RUN |3 PYTHON_VERSION=3.10 TORCH_VERSION=2.3.0 TORCHVISION_VERSION=0.18.0 /bin/sh -c python3 -m pip install --upgrade pip setuptools==69.5.1 &&    python3 -m pip install torch==${TORCH_VERSION} torchvision==${TORCHVISION_VERSION} --index-url https://download.pytorch.org/whl/${CUDA_VERSION_SHORT} &&    python3 -m pip install cmake packaging wheel # buildkit
                        
# 2024-11-26 17:17:00  0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/nccl/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64:/usr/local/openmpi/lib
                        
# 2024-11-26 17:17:00  0.00B 执行命令并创建新的镜像层
RUN |3 PYTHON_VERSION=3.10 TORCH_VERSION=2.3.0 TORCHVISION_VERSION=0.18.0 /bin/sh -c if [ "$CUDA_VERSION_SHORT" = "cu118" ]; then     git clone --depth=1 --branch v2.22.3-1 https://github.com/NVIDIA/nccl.git &&    cd nccl && make -j$(nproc) src.build &&    mv build/include/* /usr/local/include &&    mkdir -p /usr/local/nccl/lib &&    mv build/lib/lib* /usr/local/nccl/lib/ &&    cd .. && rm -rf nccl ;     fi # buildkit
                        
# 2024-11-26 17:16:59  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/openmpi/lib
                        
# 2024-11-26 17:16:59  0.00B 设置环境变量 PATH
ENV PATH=/opt/py3/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/openmpi/bin
                        
# 2024-11-26 17:16:59  12.72MB 执行命令并创建新的镜像层
RUN |3 PYTHON_VERSION=3.10 TORCH_VERSION=2.3.0 TORCHVISION_VERSION=0.18.0 /bin/sh -c wget https://download.open-mpi.org/release/open-mpi/v4.1/openmpi-4.1.5.tar.gz &&    tar xf openmpi-4.1.5.tar.gz && cd openmpi-4.1.5 && ./configure --prefix=/usr/local/openmpi &&    make -j$(nproc) && make install && cd .. && rm -rf openmpi-4.1.5* # buildkit
                        
# 2024-11-26 17:11:53  0.00B 设置环境变量 PATH
ENV PATH=/opt/py3/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
                        
# 2024-11-26 17:11:53  1.50GB 执行命令并创建新的镜像层
RUN |3 PYTHON_VERSION=3.10 TORCH_VERSION=2.3.0 TORCHVISION_VERSION=0.18.0 /bin/sh -c apt-get update -y && apt-get install -y software-properties-common wget vim git curl &&    curl https://sh.rustup.rs -sSf | sh -s -- -y &&    add-apt-repository ppa:deadsnakes/ppa -y && apt-get update -y && apt-get install -y --no-install-recommends     ninja-build rapidjson-dev libgoogle-glog-dev gdb python${PYTHON_VERSION} python${PYTHON_VERSION}-dev python${PYTHON_VERSION}-venv     && apt-get clean -y && rm -rf /var/lib/apt/lists/* && cd /opt && python3 -m venv py3 # buildkit
                        
# 2024-11-26 17:11:53  0.00B 定义构建参数
ARG TORCHVISION_VERSION=0.18.0
                        
# 2024-11-26 17:11:53  0.00B 定义构建参数
ARG TORCH_VERSION=2.3.0
                        
# 2024-11-26 17:11:53  0.00B 定义构建参数
ARG PYTHON_VERSION=3.10
                        
# 2024-11-26 17:11:53  0.00B 设置环境变量 CUDA_VERSION_SHORT
ENV CUDA_VERSION_SHORT=cu121
                        
# 2024-04-23 07:54:42  0.00B 设置环境变量 LIBRARY_PATH
ENV LIBRARY_PATH=/usr/local/cuda/lib64/stubs
                        
# 2024-04-23 07:54:42  389.87KB 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
                        
# 2024-04-23 07:54:41  4.98GB 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-12-4=${NV_CUDA_CUDART_DEV_VERSION}     cuda-command-line-tools-12-4=${NV_CUDA_LIB_VERSION}     cuda-minimal-build-12-4=${NV_CUDA_LIB_VERSION}     cuda-libraries-dev-12-4=${NV_CUDA_LIB_VERSION}     cuda-nvml-dev-12-4=${NV_NVML_DEV_VERSION}     ${NV_NVPROF_DEV_PACKAGE}     ${NV_LIBNPP_DEV_PACKAGE}     libcusparse-dev-12-4=${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
                        
# 2024-04-23 07:54:41  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2024-04-23 07:54:41  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2024-04-23 07:54:41  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE
ENV NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.21.5-1+cuda12.4
                        
# 2024-04-23 07:54:41  0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.21.5-1
                        
# 2024-04-23 07:54:41  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE_VERSION
ENV NV_LIBNCCL_DEV_PACKAGE_VERSION=2.21.5-1
                        
# 2024-04-23 07:54:41  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE_NAME
ENV NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev
                        
# 2024-04-23 07:54:41  0.00B 设置环境变量 NV_NVPROF_DEV_PACKAGE
ENV NV_NVPROF_DEV_PACKAGE=cuda-nvprof-12-4=12.4.127-1
                        
# 2024-04-23 07:54:41  0.00B 设置环境变量 NV_NVPROF_VERSION
ENV NV_NVPROF_VERSION=12.4.127-1
                        
# 2024-04-23 07:54:41  0.00B 设置环境变量 NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE
ENV NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE=cuda-nsight-compute-12-4=12.4.1-1
                        
# 2024-04-23 07:54:41  0.00B 设置环境变量 NV_CUDA_NSIGHT_COMPUTE_VERSION
ENV NV_CUDA_NSIGHT_COMPUTE_VERSION=12.4.1-1
                        
# 2024-04-23 07:54:41  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_PACKAGE
ENV NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-12-4=12.4.5.8-1
                        
# 2024-04-23 07:54:41  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_PACKAGE_NAME
ENV NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-12-4
                        
# 2024-04-23 07:54:41  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_VERSION
ENV NV_LIBCUBLAS_DEV_VERSION=12.4.5.8-1
                        
# 2024-04-23 07:54:41  0.00B 设置环境变量 NV_LIBNPP_DEV_PACKAGE
ENV NV_LIBNPP_DEV_PACKAGE=libnpp-dev-12-4=12.2.5.30-1
                        
# 2024-04-23 07:54:41  0.00B 设置环境变量 NV_LIBNPP_DEV_VERSION
ENV NV_LIBNPP_DEV_VERSION=12.2.5.30-1
                        
# 2024-04-23 07:54:41  0.00B 设置环境变量 NV_LIBCUSPARSE_DEV_VERSION
ENV NV_LIBCUSPARSE_DEV_VERSION=12.3.1.170-1
                        
# 2024-04-23 07:54:41  0.00B 设置环境变量 NV_NVML_DEV_VERSION
ENV NV_NVML_DEV_VERSION=12.4.127-1
                        
# 2024-04-23 07:54:41  0.00B 设置环境变量 NV_CUDA_CUDART_DEV_VERSION
ENV NV_CUDA_CUDART_DEV_VERSION=12.4.127-1
                        
# 2024-04-23 07:54:41  0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=12.4.1-1
                        
# 2024-04-23 07:46:26  0.00B 配置容器启动时运行的命令
ENTRYPOINT ["/opt/nvidia/nvidia_entrypoint.sh"]
                        
# 2024-04-23 07:46:26  0.00B 设置环境变量 NVIDIA_PRODUCT_NAME
ENV NVIDIA_PRODUCT_NAME=CUDA
                        
# 2024-04-23 07:46:26  2.53KB 复制新文件或目录到容器中
COPY nvidia_entrypoint.sh /opt/nvidia/ # buildkit
                        
# 2024-04-23 07:46:26  3.06KB 复制新文件或目录到容器中
COPY entrypoint.d/ /opt/nvidia/entrypoint.d/ # buildkit
                        
# 2024-04-23 07:46:26  263.02KB 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
                        
# 2024-04-23 07:46:26  2.05GB 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-12-4=${NV_CUDA_LIB_VERSION}     ${NV_LIBNPP_PACKAGE}     cuda-nvtx-12-4=${NV_NVTX_VERSION}     libcusparse-12-4=${NV_LIBCUSPARSE_VERSION}     ${NV_LIBCUBLAS_PACKAGE}     ${NV_LIBNCCL_PACKAGE}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2024-04-23 07:46:26  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2024-04-23 07:46:26  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2024-04-23 07:46:26  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE
ENV NV_LIBNCCL_PACKAGE=libnccl2=2.21.5-1+cuda12.4
                        
# 2024-04-23 07:46:26  0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.21.5-1
                        
# 2024-04-23 07:46:26  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_VERSION
ENV NV_LIBNCCL_PACKAGE_VERSION=2.21.5-1
                        
# 2024-04-23 07:46:26  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_NAME
ENV NV_LIBNCCL_PACKAGE_NAME=libnccl2
                        
# 2024-04-23 07:46:26  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE
ENV NV_LIBCUBLAS_PACKAGE=libcublas-12-4=12.4.5.8-1
                        
# 2024-04-23 07:46:26  0.00B 设置环境变量 NV_LIBCUBLAS_VERSION
ENV NV_LIBCUBLAS_VERSION=12.4.5.8-1
                        
# 2024-04-23 07:46:26  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE_NAME
ENV NV_LIBCUBLAS_PACKAGE_NAME=libcublas-12-4
                        
# 2024-04-23 07:46:26  0.00B 设置环境变量 NV_LIBCUSPARSE_VERSION
ENV NV_LIBCUSPARSE_VERSION=12.3.1.170-1
                        
# 2024-04-23 07:46:26  0.00B 设置环境变量 NV_LIBNPP_PACKAGE
ENV NV_LIBNPP_PACKAGE=libnpp-12-4=12.2.5.30-1
                        
# 2024-04-23 07:46:26  0.00B 设置环境变量 NV_LIBNPP_VERSION
ENV NV_LIBNPP_VERSION=12.2.5.30-1
                        
# 2024-04-23 07:46:26  0.00B 设置环境变量 NV_NVTX_VERSION
ENV NV_NVTX_VERSION=12.4.127-1
                        
# 2024-04-23 07:46:26  0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=12.4.1-1
                        
# 2024-04-23 07:42:28  0.00B 设置环境变量 NVIDIA_DRIVER_CAPABILITIES
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
                        
# 2024-04-23 07:42:28  0.00B 设置环境变量 NVIDIA_VISIBLE_DEVICES
ENV NVIDIA_VISIBLE_DEVICES=all
                        
# 2024-04-23 07:42:28  17.29KB 复制新文件或目录到容器中
COPY NGC-DL-CONTAINER-LICENSE / # buildkit
                        
# 2024-04-23 07:42:28  0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64
                        
# 2024-04-23 07:42:28  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
                        
# 2024-04-23 07:42:28  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
                        
# 2024-04-23 07:42:28  155.93MB 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-12-4=${NV_CUDA_CUDART_VERSION}     ${NV_CUDA_COMPAT_PACKAGE}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2024-04-23 07:42:16  0.00B 设置环境变量 CUDA_VERSION
ENV CUDA_VERSION=12.4.1
                        
# 2024-04-23 07:42:16  10.57MB 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
                        
# 2024-04-23 07:42:16  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2024-04-23 07:42:16  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2024-04-23 07:42:16  0.00B 设置环境变量 NV_CUDA_COMPAT_PACKAGE
ENV NV_CUDA_COMPAT_PACKAGE=cuda-compat-12-4
                        
# 2024-04-23 07:42:16  0.00B 设置环境变量 NV_CUDA_CUDART_VERSION
ENV NV_CUDA_CUDART_VERSION=12.4.127-1
                        
# 2024-04-23 07:42:16  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>=12.4 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
                        
# 2024-04-23 07:42:16  0.00B 设置环境变量 NVARCH
ENV NVARCH=x86_64
                        
# 2024-04-11 02:52:04  0.00B 
/bin/sh -c #(nop)  CMD ["/bin/bash"]
                        
# 2024-04-11 02:52:04  77.86MB 
/bin/sh -c #(nop) ADD file:3bd10da0673e2e72cb06a1f64a9df49a36341df39b0f762e3d1b38ee4de296fa in / 
                        
# 2024-04-11 02:52:02  0.00B 
/bin/sh -c #(nop)  LABEL org.opencontainers.image.version=22.04
                        
# 2024-04-11 02:52:02  0.00B 
/bin/sh -c #(nop)  LABEL org.opencontainers.image.ref.name=ubuntu
                        
# 2024-04-11 02:52:02  0.00B 
/bin/sh -c #(nop)  ARG LAUNCHPAD_BUILD_ARCH
                        
# 2024-04-11 02:52:02  0.00B 
/bin/sh -c #(nop)  ARG RELEASE

镜像信息

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            "NV_CUDA_COMPAT_PACKAGE=cuda-compat-12-4",
            "CUDA_VERSION=12.4.1",
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            "NVIDIA_VISIBLE_DEVICES=all",
            "NVIDIA_DRIVER_CAPABILITIES=compute,utility",
            "NV_CUDA_LIB_VERSION=12.4.1-1",
            "NV_NVTX_VERSION=12.4.127-1",
            "NV_LIBNPP_VERSION=12.2.5.30-1",
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            "NV_LIBCUSPARSE_VERSION=12.3.1.170-1",
            "NV_LIBCUBLAS_PACKAGE_NAME=libcublas-12-4",
            "NV_LIBCUBLAS_VERSION=12.4.5.8-1",
            "NV_LIBCUBLAS_PACKAGE=libcublas-12-4=12.4.5.8-1",
            "NV_LIBNCCL_PACKAGE_NAME=libnccl2",
            "NV_LIBNCCL_PACKAGE_VERSION=2.21.5-1",
            "NCCL_VERSION=2.21.5-1",
            "NV_LIBNCCL_PACKAGE=libnccl2=2.21.5-1+cuda12.4",
            "NVIDIA_PRODUCT_NAME=CUDA",
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更多版本

docker.io/openmmlab/lmdeploy:v0.6.1-cu11

linux/amd64 docker.io16.62GB2024-09-30 11:49

212

docker.io/openmmlab/lmdeploy:v0.6.3.post1-cu12

linux/amd64 docker.io16.08GB2024-11-30 00:20

115

docker.io/openmmlab/lmdeploy:v0.6.3.post1-cu12 linux/amd64

镜像安全扫描 查看Trivy扫描报告

镜像安全扫描查看Trivy扫描报告