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注意：这是一个 latest 标签镜像

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docker.io/realamphion/amphion:latest
linux/amd64 docker.io
1. 镜像名称：realamphion/amphion 2.

镜像描述

  • 镜像来源：docker.io
  • 镜像名称：realamphion/amphion
3.

镜像信息

这是一个基于Docker的容器镜像，适合于Node.js应用。

  1. 使用场景：用于部署Node.js应用
  2. 适用环境：多platform（Windows、Linux、macOS）
  3. 镜像大小约为2G
519
浏览次数
19.60GB
镜像大小
源镜像
docker.io/realamphion/amphion:latest
国内镜像
swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/realamphion/amphion:latest
镜像ID
sha256:d57073a88944e45a7d517ea27c4f4c150f66c514519c9f13f979878209cea425
镜像 TAG
latest
镜像大小
19.60GB
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
/opt/nvidia/nvidia_entrypoint.sh
工作目录
/app
OS/平台
linux/amd64
镜像创建
2024-02-20T03:35:41.28163106+08:00
同步时间
2024-11-05 00:36
浏览量
519 次
贡献者
⚙️ 环境变量 48
KeyValue
PATH=/opt/conda/bin:/usr/local/cuda/bin:/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>=11.8 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 brand=tesla,driver>=510,driver<511 brand=unknown,driver>=510,driver<511 brand=nvidia,driver>=510,driver<511 brand=nvidiartx,driver>=510,driver<511 brand=geforce,driver>=510,driver<511 brand=geforcertx,driver>=510,driver<511 brand=quadro,driver>=510,driver<511 brand=quadrortx,driver>=510,driver<511 brand=titan,driver>=510,driver<511 brand=titanrtx,driver>=510,driver<511 brand=tesla,driver>=515,driver<516 brand=unknown,driver>=515,driver<516 brand=nvidia,driver>=515,driver<516 brand=nvidiartx,driver>=515,driver<516 brand=geforce,driver>=515,driver<516 brand=geforcertx,driver>=515,driver<516 brand=quadro,driver>=515,driver<516 brand=quadrortx,driver>=515,driver<516 brand=titan,driver>=515,driver<516 brand=titanrtx,driver>=515,driver<516 2
NV_CUDA_CUDART_VERSION=11.8.89-1 3
NV_CUDA_COMPAT_PACKAGE=cuda-compat-11-8 4
CUDA_VERSION=11.8.0 5
LD_LIBRARY_PATH=/usr/local/cuda/lib64:/usr/local/nvidia/lib:/usr/local/nvidia/lib64 6
NVIDIA_VISIBLE_DEVICES=all 7
NVIDIA_DRIVER_CAPABILITIES=compute,utility 8
NV_CUDA_LIB_VERSION=11.8.0-1 9
NV_NVTX_VERSION=11.8.86-1 10
NV_LIBNPP_VERSION=11.8.0.86-1 11
NV_LIBNPP_PACKAGE=libnpp-11-8=11.8.0.86-1 12
NV_LIBCUSPARSE_VERSION=11.7.5.86-1 13
NV_LIBCUBLAS_PACKAGE_NAME=libcublas-11-8 14
NV_LIBCUBLAS_VERSION=11.11.3.6-1 15
NV_LIBCUBLAS_PACKAGE=libcublas-11-8=11.11.3.6-1 16
NV_LIBNCCL_PACKAGE_NAME=libnccl2 17
NV_LIBNCCL_PACKAGE_VERSION=2.15.5-1 18
NCCL_VERSION=2.15.5-1 19
NV_LIBNCCL_PACKAGE=libnccl2=2.15.5-1+cuda11.8 20
NVIDIA_PRODUCT_NAME=CUDA 21
NV_CUDA_CUDART_DEV_VERSION=11.8.89-1 22
NV_NVML_DEV_VERSION=11.8.86-1 23
NV_LIBCUSPARSE_DEV_VERSION=11.7.5.86-1 24
NV_LIBNPP_DEV_VERSION=11.8.0.86-1 25
NV_LIBNPP_DEV_PACKAGE=libnpp-dev-11-8=11.8.0.86-1 26
NV_LIBCUBLAS_DEV_VERSION=11.11.3.6-1 27
NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-11-8 28
NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-11-8=11.11.3.6-1 29
NV_NVPROF_VERSION=11.8.87-1 30
NV_NVPROF_DEV_PACKAGE=cuda-nvprof-11-8=11.8.87-1 31
NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev 32
NV_LIBNCCL_DEV_PACKAGE_VERSION=2.15.5-1 33
NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.15.5-1+cuda11.8 34
LIBRARY_PATH=/usr/local/cuda/lib64:/usr/local/cuda/lib64/stubs 35
NV_CUDNN_VERSION=8.6.0.163 36
NV_CUDNN_PACKAGE_NAME=libcudnn8 37
NV_CUDNN_PACKAGE=libcudnn8=8.6.0.163-1+cuda11.8 38
NV_CUDNN_PACKAGE_DEV=libcudnn8-dev=8.6.0.163-1+cuda11.8 39
LANG=en_US.UTF-8 40
PYTHONIOENCODING=utf-8 41
PYTHONDONTWRITEBYTECODE=1 42
CUDA_HOME=/usr/local/cuda 43
CONDA_HOME=/opt/conda 44
SHELL=/bin/bash 45
CONDA_PREFIX=/opt/conda 46
NCCL_HOME=/usr/local/cuda 47
🏷️ 镜像标签 4
KeyValue
8.6.0.163 com.nvidia.cudnn.version
NVIDIA CORPORATION <cudatools@nvidia.com> maintainer
ubuntu org.opencontainers.image.ref.name
18.04 org.opencontainers.image.version
🛡️ 镜像安全扫描
ubuntu 18.04 Trivy 2024-11-05 00:40 查看完整报告
46
低危 LOW
163
中危 MEDIUM
22
高危 HIGH
1
严重 CRITICAL
受影响目标 (3)
docker.io/realamphion/amphion:latest (ubuntu 18.04) ubuntu Conda conda-pkg Python python-pkg
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/realamphion/amphion:latest
docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/realamphion/amphion:latest  docker.io/realamphion/amphion:latest

Containerd拉取命令 

ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/realamphion/amphion:latest
ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/realamphion/amphion:latest  docker.io/realamphion/amphion:latest

Shell快速替换命令 

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

Ansible快速分发-Containerd 

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

镜像构建历史 


# 2024-02-20 03:35:41  0.00B 设置默认要执行的命令
CMD ["/bin/bash"]
                        
# 2024-02-20 03:35:41  3.56KB 执行命令并创建新的镜像层
RUN |5 DEBIAN_FRONTEND=noninteractive PYTORCH=2.0.0 CUDA=cu118 SHELL=/bin/bash MINICONDA=Miniconda3-py39_23.3.1-0-Linux-x86_64.sh /bin/sh -c conda init     && echo "\nconda activate amphion\n" >> ~/.bashrc # buildkit
                        
# 2024-02-20 03:35:40  9.06GB 执行命令并创建新的镜像层
RUN |5 DEBIAN_FRONTEND=noninteractive PYTORCH=2.0.0 CUDA=cu118 SHELL=/bin/bash MINICONDA=Miniconda3-py39_23.3.1-0-Linux-x86_64.sh conda run -n amphion -vvv --no-capture-output ./env.sh # buildkit
                        
# 2024-02-20 00:41:32  1.22KB 执行命令并创建新的镜像层
RUN |5 DEBIAN_FRONTEND=noninteractive PYTORCH=2.0.0 CUDA=cu118 SHELL=/bin/bash MINICONDA=Miniconda3-py39_23.3.1-0-Linux-x86_64.sh /bin/sh -c chmod +x ./env.sh # buildkit
                        
# 2024-02-20 00:41:31  1.22KB 复制新文件或目录到容器中
COPY env.sh env.sh # buildkit
                        
# 2024-02-18 21:11:15  0.00B 设置工作目录为/app
WORKDIR /app
                        
# 2024-02-18 21:11:15  412.33MB 执行命令并创建新的镜像层
RUN |5 DEBIAN_FRONTEND=noninteractive PYTORCH=2.0.0 CUDA=cu118 SHELL=/bin/bash MINICONDA=Miniconda3-py39_23.3.1-0-Linux-x86_64.sh /bin/sh -c conda create -y --name amphion python=3.9.15 # buildkit
                        
# 2024-02-18 21:10:39  308.06MB 执行命令并创建新的镜像层
RUN |5 DEBIAN_FRONTEND=noninteractive PYTORCH=2.0.0 CUDA=cu118 SHELL=/bin/bash MINICONDA=Miniconda3-py39_23.3.1-0-Linux-x86_64.sh /bin/sh -c wget -t 0 -c -O /tmp/anaconda.sh https://repo.anaconda.com/miniconda/${MINICONDA}     && mv /tmp/anaconda.sh /root/anaconda.sh     && ${SHELL} /root/anaconda.sh -b -p $CONDA_HOME     && rm /root/anaconda.sh # buildkit
                        
# 2024-02-18 21:10:11  0.00B 指定运行容器时使用的用户
USER root
                        
# 2024-02-18 21:10:11  957.27MB 执行命令并创建新的镜像层
RUN |5 DEBIAN_FRONTEND=noninteractive PYTORCH=2.0.0 CUDA=cu118 SHELL=/bin/bash MINICONDA=Miniconda3-py39_23.3.1-0-Linux-x86_64.sh /bin/sh -c sed -i 's/archive.ubuntu.com/mirrors.cloud.tencent.com/g' /etc/apt/sources.list     && sed -i 's/security.ubuntu.com/mirrors.cloud.tencent.com/g' /etc/apt/sources.list     && rm /etc/apt/sources.list.d/cuda.list     && apt-get update     && apt-get -y install     python3-pip ffmpeg git less wget libsm6 libxext6 libxrender-dev     build-essential cmake pkg-config libx11-dev libatlas-base-dev     libgtk-3-dev libboost-python-dev vim libgl1-mesa-glx     libaio-dev software-properties-common tmux     espeak-ng # buildkit
                        
# 2024-02-18 21:10:11  0.00B 设置环境变量 PATH LD_LIBRARY_PATH LIBRARY_PATH CONDA_PREFIX NCCL_HOME
ENV PATH=/opt/conda/bin:/usr/local/cuda/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin LD_LIBRARY_PATH=/usr/local/cuda/lib64:/usr/local/nvidia/lib:/usr/local/nvidia/lib64 LIBRARY_PATH=/usr/local/cuda/lib64:/usr/local/cuda/lib64/stubs CONDA_PREFIX=/opt/conda NCCL_HOME=/usr/local/cuda
                        
# 2024-02-18 21:10:11  0.00B 设置环境变量 LANG PYTHONIOENCODING PYTHONDONTWRITEBYTECODE CUDA_HOME CONDA_HOME SHELL
ENV LANG=en_US.UTF-8 PYTHONIOENCODING=utf-8 PYTHONDONTWRITEBYTECODE=1 CUDA_HOME=/usr/local/cuda CONDA_HOME=/opt/conda SHELL=/bin/bash
                        
# 2024-02-18 21:10:11  0.00B 定义构建参数
ARG MINICONDA=Miniconda3-py39_23.3.1-0-Linux-x86_64.sh
                        
# 2024-02-18 21:10:11  0.00B 定义构建参数
ARG SHELL=/bin/bash
                        
# 2024-02-18 21:10:11  0.00B 定义构建参数
ARG CUDA=cu118
                        
# 2024-02-18 21:10:11  0.00B 定义构建参数
ARG PYTORCH=2.0.0
                        
# 2024-02-18 21:10:11  0.00B 定义构建参数
ARG DEBIAN_FRONTEND=noninteractive
                        
# 2023-02-02 13:38:31  2.51GB 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
                        
# 2023-02-02 13:38:31  0.00B 添加元数据标签
LABEL com.nvidia.cudnn.version=8.6.0.163
                        
# 2023-02-02 13:38:31  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2023-02-02 13:38:31  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2023-02-02 13:38:31  0.00B 设置环境变量 NV_CUDNN_PACKAGE_DEV
ENV NV_CUDNN_PACKAGE_DEV=libcudnn8-dev=8.6.0.163-1+cuda11.8
                        
# 2023-02-02 13:38:31  0.00B 设置环境变量 NV_CUDNN_PACKAGE
ENV NV_CUDNN_PACKAGE=libcudnn8=8.6.0.163-1+cuda11.8
                        
# 2023-02-02 13:38:31  0.00B 设置环境变量 NV_CUDNN_PACKAGE_NAME
ENV NV_CUDNN_PACKAGE_NAME=libcudnn8
                        
# 2023-02-02 13:38:31  0.00B 设置环境变量 NV_CUDNN_VERSION
ENV NV_CUDNN_VERSION=8.6.0.163
                        
# 2023-02-02 13:26:12  0.00B 设置环境变量 LIBRARY_PATH
ENV LIBRARY_PATH=/usr/local/cuda/lib64/stubs
                        
# 2023-02-02 13:26:12  370.27KB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-mark hold ${NV_LIBCUBLAS_DEV_PACKAGE_NAME} ${NV_LIBNCCL_DEV_PACKAGE_NAME} # buildkit
                        
# 2023-02-02 13:26:12  3.71GB 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-11-8=${NV_CUDA_CUDART_DEV_VERSION}     cuda-command-line-tools-11-8=${NV_CUDA_LIB_VERSION}     cuda-minimal-build-11-8=${NV_CUDA_LIB_VERSION}     cuda-libraries-dev-11-8=${NV_CUDA_LIB_VERSION}     cuda-nvml-dev-11-8=${NV_NVML_DEV_VERSION}     ${NV_NVPROF_DEV_PACKAGE}     ${NV_LIBNPP_DEV_PACKAGE}     libcusparse-dev-11-8=${NV_LIBCUSPARSE_DEV_VERSION}     ${NV_LIBCUBLAS_DEV_PACKAGE}     ${NV_LIBNCCL_DEV_PACKAGE}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2023-02-02 13:26:12  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2023-02-02 13:26:12  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2023-02-02 13:26:12  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE
ENV NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.15.5-1+cuda11.8
                        
# 2023-02-02 13:26:12  0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.15.5-1
                        
# 2023-02-02 13:26:12  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE_VERSION
ENV NV_LIBNCCL_DEV_PACKAGE_VERSION=2.15.5-1
                        
# 2023-02-02 13:26:12  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE_NAME
ENV NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev
                        
# 2023-02-02 13:26:12  0.00B 设置环境变量 NV_NVPROF_DEV_PACKAGE
ENV NV_NVPROF_DEV_PACKAGE=cuda-nvprof-11-8=11.8.87-1
                        
# 2023-02-02 13:26:12  0.00B 设置环境变量 NV_NVPROF_VERSION
ENV NV_NVPROF_VERSION=11.8.87-1
                        
# 2023-02-02 13:26:12  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_PACKAGE
ENV NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-11-8=11.11.3.6-1
                        
# 2023-02-02 13:26:12  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_PACKAGE_NAME
ENV NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-11-8
                        
# 2023-02-02 13:26:12  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_VERSION
ENV NV_LIBCUBLAS_DEV_VERSION=11.11.3.6-1
                        
# 2023-02-02 13:26:12  0.00B 设置环境变量 NV_LIBNPP_DEV_PACKAGE
ENV NV_LIBNPP_DEV_PACKAGE=libnpp-dev-11-8=11.8.0.86-1
                        
# 2023-02-02 13:26:12  0.00B 设置环境变量 NV_LIBNPP_DEV_VERSION
ENV NV_LIBNPP_DEV_VERSION=11.8.0.86-1
                        
# 2023-02-02 13:26:12  0.00B 设置环境变量 NV_LIBCUSPARSE_DEV_VERSION
ENV NV_LIBCUSPARSE_DEV_VERSION=11.7.5.86-1
                        
# 2023-02-02 13:26:12  0.00B 设置环境变量 NV_NVML_DEV_VERSION
ENV NV_NVML_DEV_VERSION=11.8.86-1
                        
# 2023-02-02 13:26:12  0.00B 设置环境变量 NV_CUDA_CUDART_DEV_VERSION
ENV NV_CUDA_CUDART_DEV_VERSION=11.8.89-1
                        
# 2023-02-02 13:26:12  0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=11.8.0-1
                        
# 2023-02-02 13:21:58  0.00B 配置容器启动时运行的命令
ENTRYPOINT ["/opt/nvidia/nvidia_entrypoint.sh"]
                        
# 2023-02-02 13:21:58  0.00B 设置环境变量 NVIDIA_PRODUCT_NAME
ENV NVIDIA_PRODUCT_NAME=CUDA
                        
# 2023-02-02 13:21:58  2.53KB 复制新文件或目录到容器中
COPY nvidia_entrypoint.sh /opt/nvidia/ # buildkit
                        
# 2023-02-02 13:21:58  3.04KB 复制新文件或目录到容器中
COPY entrypoint.d/ /opt/nvidia/entrypoint.d/ # buildkit
                        
# 2023-02-02 13:21:58  256.97KB 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
                        
# 2023-02-02 13:21:57  2.41GB 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-11-8=${NV_CUDA_LIB_VERSION}     ${NV_LIBNPP_PACKAGE}     cuda-nvtx-11-8=${NV_NVTX_VERSION}     libcusparse-11-8=${NV_LIBCUSPARSE_VERSION}     ${NV_LIBCUBLAS_PACKAGE}     ${NV_LIBNCCL_PACKAGE}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2023-02-02 13:21:57  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2023-02-02 13:21:57  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2023-02-02 13:21:57  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE
ENV NV_LIBNCCL_PACKAGE=libnccl2=2.15.5-1+cuda11.8
                        
# 2023-02-02 13:21:57  0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.15.5-1
                        
# 2023-02-02 13:21:57  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_VERSION
ENV NV_LIBNCCL_PACKAGE_VERSION=2.15.5-1
                        
# 2023-02-02 13:21:57  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_NAME
ENV NV_LIBNCCL_PACKAGE_NAME=libnccl2
                        
# 2023-02-02 13:21:57  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE
ENV NV_LIBCUBLAS_PACKAGE=libcublas-11-8=11.11.3.6-1
                        
# 2023-02-02 13:21:57  0.00B 设置环境变量 NV_LIBCUBLAS_VERSION
ENV NV_LIBCUBLAS_VERSION=11.11.3.6-1
                        
# 2023-02-02 13:21:57  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE_NAME
ENV NV_LIBCUBLAS_PACKAGE_NAME=libcublas-11-8
                        
# 2023-02-02 13:21:57  0.00B 设置环境变量 NV_LIBCUSPARSE_VERSION
ENV NV_LIBCUSPARSE_VERSION=11.7.5.86-1
                        
# 2023-02-02 13:21:57  0.00B 设置环境变量 NV_LIBNPP_PACKAGE
ENV NV_LIBNPP_PACKAGE=libnpp-11-8=11.8.0.86-1
                        
# 2023-02-02 13:21:57  0.00B 设置环境变量 NV_LIBNPP_VERSION
ENV NV_LIBNPP_VERSION=11.8.0.86-1
                        
# 2023-02-02 13:21:57  0.00B 设置环境变量 NV_NVTX_VERSION
ENV NV_NVTX_VERSION=11.8.86-1
                        
# 2023-02-02 13:21:57  0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=11.8.0-1
                        
# 2023-02-02 13:19:38  0.00B 设置环境变量 NVIDIA_DRIVER_CAPABILITIES
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
                        
# 2023-02-02 13:19:38  0.00B 设置环境变量 NVIDIA_VISIBLE_DEVICES
ENV NVIDIA_VISIBLE_DEVICES=all
                        
# 2023-02-02 13:19:38  16.05KB 复制新文件或目录到容器中
COPY NGC-DL-CONTAINER-LICENSE / # buildkit
                        
# 2023-02-02 13:19:37  0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64
                        
# 2023-02-02 13:19:37  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
                        
# 2023-02-02 13:19:37  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
                        
# 2023-02-02 13:19:37  150.70MB 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-11-8=${NV_CUDA_CUDART_VERSION}     ${NV_CUDA_COMPAT_PACKAGE}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2023-02-02 13:19:23  0.00B 设置环境变量 CUDA_VERSION
ENV CUDA_VERSION=11.8.0
                        
# 2023-02-02 13:19:23  16.53MB 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
                        
# 2023-02-02 13:19:23  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2023-02-02 13:19:23  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2023-02-02 13:19:23  0.00B 设置环境变量 NV_CUDA_COMPAT_PACKAGE
ENV NV_CUDA_COMPAT_PACKAGE=cuda-compat-11-8
                        
# 2023-02-02 13:19:23  0.00B 设置环境变量 NV_CUDA_CUDART_VERSION
ENV NV_CUDA_CUDART_VERSION=11.8.89-1
                        
# 2023-02-02 13:19:23  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
ENV NVIDIA_REQUIRE_CUDA=cuda>=11.8 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 brand=tesla,driver>=510,driver<511 brand=unknown,driver>=510,driver<511 brand=nvidia,driver>=510,driver<511 brand=nvidiartx,driver>=510,driver<511 brand=geforce,driver>=510,driver<511 brand=geforcertx,driver>=510,driver<511 brand=quadro,driver>=510,driver<511 brand=quadrortx,driver>=510,driver<511 brand=titan,driver>=510,driver<511 brand=titanrtx,driver>=510,driver<511 brand=tesla,driver>=515,driver<516 brand=unknown,driver>=515,driver<516 brand=nvidia,driver>=515,driver<516 brand=nvidiartx,driver>=515,driver<516 brand=geforce,driver>=515,driver<516 brand=geforcertx,driver>=515,driver<516 brand=quadro,driver>=515,driver<516 brand=quadrortx,driver>=515,driver<516 brand=titan,driver>=515,driver<516 brand=titanrtx,driver>=515,driver<516
                        
# 2023-02-02 13:19:23  0.00B 设置环境变量 NVARCH
ENV NVARCH=x86_64
                        
# 2023-01-26 18:03:05  0.00B 
/bin/sh -c #(nop)  CMD ["/bin/bash"]
                        
# 2023-01-26 18:03:04  63.15MB 
/bin/sh -c #(nop) ADD file:365c129e10f7ef1594e8086543b45f524313e36dd6a25b68f4da542a09491f04 in / 
                        
# 2023-01-26 18:03:03  0.00B 
/bin/sh -c #(nop)  LABEL org.opencontainers.image.version=18.04
                        
# 2023-01-26 18:03:03  0.00B 
/bin/sh -c #(nop)  LABEL org.opencontainers.image.ref.name=ubuntu
                        
# 2023-01-26 18:03:03  0.00B 
/bin/sh -c #(nop)  ARG LAUNCHPAD_BUILD_ARCH
                        
# 2023-01-26 18:03:03  0.00B 
/bin/sh -c #(nop)  ARG RELEASE

镜像信息 

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            "NV_CUDA_CUDART_VERSION=11.8.89-1",
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            "CUDA_VERSION=11.8.0",
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            "NVIDIA_VISIBLE_DEVICES=all",
            "NVIDIA_DRIVER_CAPABILITIES=compute,utility",
            "NV_CUDA_LIB_VERSION=11.8.0-1",
            "NV_NVTX_VERSION=11.8.86-1",
            "NV_LIBNPP_VERSION=11.8.0.86-1",
            "NV_LIBNPP_PACKAGE=libnpp-11-8=11.8.0.86-1",
            "NV_LIBCUSPARSE_VERSION=11.7.5.86-1",
            "NV_LIBCUBLAS_PACKAGE_NAME=libcublas-11-8",
            "NV_LIBCUBLAS_VERSION=11.11.3.6-1",
            "NV_LIBCUBLAS_PACKAGE=libcublas-11-8=11.11.3.6-1",
            "NV_LIBNCCL_PACKAGE_NAME=libnccl2",
            "NV_LIBNCCL_PACKAGE_VERSION=2.15.5-1",
            "NCCL_VERSION=2.15.5-1",
            "NV_LIBNCCL_PACKAGE=libnccl2=2.15.5-1+cuda11.8",
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}

更多版本

docker.io/realamphion/amphion:latest

linux/amd64 docker.io19.60GB2024-11-05 00:36
518
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