docker.io/wangcanlong/go-vad-asr-speaker-identification-grpc-server:v1.12.20-cu118 linux/amd64

docker.io/wangcanlong/go-vad-asr-speaker-identification-grpc-server:v1.12.20-cu118 - 国内下载镜像源 浏览次数:8
源镜像 docker.io/wangcanlong/go-vad-asr-speaker-identification-grpc-server:v1.12.20-cu118
国内镜像 swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/wangcanlong/go-vad-asr-speaker-identification-grpc-server:v1.12.20-cu118
镜像ID sha256:c3694cbe76d90b7050c4ae60c8d5d8faeeebd751f48f22cc3025df2523ec9c95
镜像TAG v1.12.20-cu118
大小 13.72GB
镜像源 docker.io
项目信息 Docker-Hub主页 🚀项目TAG 🚀
CMD
启动入口 ./go-vad-asr-speaker-identification-grpc-server
工作目录 /home/go-vad-asr-speaker-identification-grpc-server
OS/平台 linux/amd64
浏览量 8 次
贡献者
镜像创建 2026-01-16T11:54:15.739518414+08:00
同步时间 2026-01-17 03:03
更新时间 2026-01-17 04:05
开放端口
8080/tcp
环境变量
PATH=/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>=11.8 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=11.8.89-1 NV_CUDA_COMPAT_PACKAGE=cuda-compat-11-8 CUDA_VERSION=11.8.0 LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64 NVIDIA_VISIBLE_DEVICES=all NVIDIA_DRIVER_CAPABILITIES=compute,utility NV_CUDA_LIB_VERSION=11.8.0-1 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 NVIDIA_PRODUCT_NAME=CUDA NV_CUDA_CUDART_DEV_VERSION=11.8.89-1 NV_NVML_DEV_VERSION=11.8.86-1 NV_LIBCUSPARSE_DEV_VERSION=11.7.5.86-1 NV_LIBNPP_DEV_VERSION=11.8.0.86-1 NV_LIBNPP_DEV_PACKAGE=libnpp-dev-11-8=11.8.0.86-1 NV_LIBCUBLAS_DEV_VERSION=11.11.3.6-1 NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-11-8 NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-11-8=11.11.3.6-1 NV_CUDA_NSIGHT_COMPUTE_VERSION=11.8.0-1 NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE=cuda-nsight-compute-11-8=11.8.0-1 NV_NVPROF_VERSION=11.8.87-1 NV_NVPROF_DEV_PACKAGE=cuda-nvprof-11-8=11.8.87-1 NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev NV_LIBNCCL_DEV_PACKAGE_VERSION=2.15.5-1 NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.15.5-1+cuda11.8 LIBRARY_PATH=/usr/local/cuda/lib64/stubs NV_CUDNN_VERSION=8.9.6.50 NV_CUDNN_PACKAGE_NAME=libcudnn8 NV_CUDNN_PACKAGE=libcudnn8=8.9.6.50-1+cuda11.8 NV_CUDNN_PACKAGE_DEV=libcudnn8-dev=8.9.6.50-1+cuda11.8 TZ=Asia/Shanghai
镜像标签
8.9.6.50: com.nvidia.cudnn.version NVIDIA CORPORATION <cudatools@nvidia.com>: maintainer ubuntu: org.opencontainers.image.ref.name 22.04: org.opencontainers.image.version

Docker拉取命令

docker pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/wangcanlong/go-vad-asr-speaker-identification-grpc-server:v1.12.20-cu118
docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/wangcanlong/go-vad-asr-speaker-identification-grpc-server:v1.12.20-cu118  docker.io/wangcanlong/go-vad-asr-speaker-identification-grpc-server:v1.12.20-cu118

Containerd拉取命令

ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/wangcanlong/go-vad-asr-speaker-identification-grpc-server:v1.12.20-cu118
ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/wangcanlong/go-vad-asr-speaker-identification-grpc-server:v1.12.20-cu118  docker.io/wangcanlong/go-vad-asr-speaker-identification-grpc-server:v1.12.20-cu118

Shell快速替换命令

sed -i 's#wangcanlong/go-vad-asr-speaker-identification-grpc-server:v1.12.20-cu118#swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/wangcanlong/go-vad-asr-speaker-identification-grpc-server:v1.12.20-cu118#' 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/wangcanlong/go-vad-asr-speaker-identification-grpc-server:v1.12.20-cu118 && docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/wangcanlong/go-vad-asr-speaker-identification-grpc-server:v1.12.20-cu118  docker.io/wangcanlong/go-vad-asr-speaker-identification-grpc-server:v1.12.20-cu118'

Ansible快速分发-Containerd

#ansible k8s -m shell -a 'ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/wangcanlong/go-vad-asr-speaker-identification-grpc-server:v1.12.20-cu118 && ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/wangcanlong/go-vad-asr-speaker-identification-grpc-server:v1.12.20-cu118  docker.io/wangcanlong/go-vad-asr-speaker-identification-grpc-server:v1.12.20-cu118'

镜像构建历史


# 2026-01-16 11:54:15  0.00B 配置容器启动时运行的命令
ENTRYPOINT ["./go-vad-asr-speaker-identification-grpc-server"]
                        
# 2026-01-16 11:54:15  0.00B 声明容器运行时监听的端口
EXPOSE &{[{{26 0} {26 0}}] 0xc0076134c0}
                        
# 2026-01-16 11:54:15  13.70MB 执行命令并创建新的镜像层
RUN /bin/sh -c chmod +x ./go-vad-asr-speaker-identification-grpc-server # buildkit
                        
# 2026-01-16 11:54:15  13.70MB 复制新文件或目录到容器中
COPY go-vad-asr-speaker-identification-grpc-server ./ # buildkit
                        
# 2026-01-16 11:54:14  1.33MB 复制新文件或目录到容器中
COPY speakers ./speakers # buildkit
                        
# 2026-01-16 11:54:13  653.01MB 复制新文件或目录到容器中
COPY vendor ./vendor # buildkit
                        
# 2026-01-16 11:46:33  1.44GB 复制新文件或目录到容器中
COPY model_file ./model_file # buildkit
                        
# 2026-01-16 11:46:15  0.00B 设置工作目录为/home/go-vad-asr-speaker-identification-grpc-server
WORKDIR /home/go-vad-asr-speaker-identification-grpc-server
                        
# 2026-01-16 11:46:12  47.00B 执行命令并创建新的镜像层
RUN /bin/sh -c ln -snf /usr/share/zoneinfo/$TZ /etc/localtime && echo $TZ > /etc/timezone # buildkit
                        
# 2026-01-16 11:46:12  0.00B 设置环境变量 TZ
ENV TZ=Asia/Shanghai
                        
# 2024-09-18 15:33:38  1.85GB 

                        
# 2023-11-10 15:16:45  2.37GB 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 15:16:45  0.00B 添加元数据标签
LABEL com.nvidia.cudnn.version=8.9.6.50
                        
# 2023-11-10 15:16:45  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2023-11-10 15:16:45  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2023-11-10 15:16:45  0.00B 设置环境变量 NV_CUDNN_PACKAGE_DEV
ENV NV_CUDNN_PACKAGE_DEV=libcudnn8-dev=8.9.6.50-1+cuda11.8
                        
# 2023-11-10 15:16:45  0.00B 设置环境变量 NV_CUDNN_PACKAGE
ENV NV_CUDNN_PACKAGE=libcudnn8=8.9.6.50-1+cuda11.8
                        
# 2023-11-10 15:16:45  0.00B 设置环境变量 NV_CUDNN_PACKAGE_NAME
ENV NV_CUDNN_PACKAGE_NAME=libcudnn8
                        
# 2023-11-10 15:16:45  0.00B 设置环境变量 NV_CUDNN_VERSION
ENV NV_CUDNN_VERSION=8.9.6.50
                        
# 2023-11-10 14:55:21  0.00B 设置环境变量 LIBRARY_PATH
ENV LIBRARY_PATH=/usr/local/cuda/lib64/stubs
                        
# 2023-11-10 14:55:21  383.52KB 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 14:55:17  4.72GB 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}     ${NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2023-11-10 14:55:17  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2023-11-10 14:55:17  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2023-11-10 14:55:17  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
                        
# 2023-11-10 14:55:17  0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.15.5-1
                        
# 2023-11-10 14:55:17  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE_VERSION
ENV NV_LIBNCCL_DEV_PACKAGE_VERSION=2.15.5-1
                        
# 2023-11-10 14:55:17  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE_NAME
ENV NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev
                        
# 2023-11-10 14:55:17  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
                        
# 2023-11-10 14:55:17  0.00B 设置环境变量 NV_NVPROF_VERSION
ENV NV_NVPROF_VERSION=11.8.87-1
                        
# 2023-11-10 14:55:17  0.00B 设置环境变量 NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE
ENV NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE=cuda-nsight-compute-11-8=11.8.0-1
                        
# 2023-11-10 14:55:17  0.00B 设置环境变量 NV_CUDA_NSIGHT_COMPUTE_VERSION
ENV NV_CUDA_NSIGHT_COMPUTE_VERSION=11.8.0-1
                        
# 2023-11-10 14:55:17  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
                        
# 2023-11-10 14:55:17  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_PACKAGE_NAME
ENV NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-11-8
                        
# 2023-11-10 14:55:17  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_VERSION
ENV NV_LIBCUBLAS_DEV_VERSION=11.11.3.6-1
                        
# 2023-11-10 14:55:17  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
                        
# 2023-11-10 14:55:17  0.00B 设置环境变量 NV_LIBNPP_DEV_VERSION
ENV NV_LIBNPP_DEV_VERSION=11.8.0.86-1
                        
# 2023-11-10 14:55:17  0.00B 设置环境变量 NV_LIBCUSPARSE_DEV_VERSION
ENV NV_LIBCUSPARSE_DEV_VERSION=11.7.5.86-1
                        
# 2023-11-10 14:55:17  0.00B 设置环境变量 NV_NVML_DEV_VERSION
ENV NV_NVML_DEV_VERSION=11.8.86-1
                        
# 2023-11-10 14:55:17  0.00B 设置环境变量 NV_CUDA_CUDART_DEV_VERSION
ENV NV_CUDA_CUDART_DEV_VERSION=11.8.89-1
                        
# 2023-11-10 14:55:17  0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=11.8.0-1
                        
# 2023-11-10 14:42:37  0.00B 配置容器启动时运行的命令
ENTRYPOINT ["/opt/nvidia/nvidia_entrypoint.sh"]
                        
# 2023-11-10 14:42:37  0.00B 设置环境变量 NVIDIA_PRODUCT_NAME
ENV NVIDIA_PRODUCT_NAME=CUDA
                        
# 2023-11-10 14:42:37  2.53KB 复制新文件或目录到容器中
COPY nvidia_entrypoint.sh /opt/nvidia/ # buildkit
                        
# 2023-11-10 14:42:37  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 14:42:37  260.16KB 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 14:42:36  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
                        
# 2023-11-10 14:42:36  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2023-11-10 14:42:36  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2023-11-10 14:42:36  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE
ENV NV_LIBNCCL_PACKAGE=libnccl2=2.15.5-1+cuda11.8
                        
# 2023-11-10 14:42:36  0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.15.5-1
                        
# 2023-11-10 14:42:36  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_VERSION
ENV NV_LIBNCCL_PACKAGE_VERSION=2.15.5-1
                        
# 2023-11-10 14:42:36  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_NAME
ENV NV_LIBNCCL_PACKAGE_NAME=libnccl2
                        
# 2023-11-10 14:42:36  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE
ENV NV_LIBCUBLAS_PACKAGE=libcublas-11-8=11.11.3.6-1
                        
# 2023-11-10 14:42:36  0.00B 设置环境变量 NV_LIBCUBLAS_VERSION
ENV NV_LIBCUBLAS_VERSION=11.11.3.6-1
                        
# 2023-11-10 14:42:36  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE_NAME
ENV NV_LIBCUBLAS_PACKAGE_NAME=libcublas-11-8
                        
# 2023-11-10 14:42:36  0.00B 设置环境变量 NV_LIBCUSPARSE_VERSION
ENV NV_LIBCUSPARSE_VERSION=11.7.5.86-1
                        
# 2023-11-10 14:42:36  0.00B 设置环境变量 NV_LIBNPP_PACKAGE
ENV NV_LIBNPP_PACKAGE=libnpp-11-8=11.8.0.86-1
                        
# 2023-11-10 14:42:36  0.00B 设置环境变量 NV_LIBNPP_VERSION
ENV NV_LIBNPP_VERSION=11.8.0.86-1
                        
# 2023-11-10 14:42:36  0.00B 设置环境变量 NV_NVTX_VERSION
ENV NV_NVTX_VERSION=11.8.86-1
                        
# 2023-11-10 14:42:36  0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=11.8.0-1
                        
# 2023-11-10 14:37:16  0.00B 设置环境变量 NVIDIA_DRIVER_CAPABILITIES
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
                        
# 2023-11-10 14:37:16  0.00B 设置环境变量 NVIDIA_VISIBLE_DEVICES
ENV NVIDIA_VISIBLE_DEVICES=all
                        
# 2023-11-10 14:37:16  17.29KB 复制新文件或目录到容器中
COPY NGC-DL-CONTAINER-LICENSE / # buildkit
                        
# 2023-11-10 14:37:16  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 14:37:16  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
                        
# 2023-11-10 14:37:16  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
                        
# 2023-11-10 14:37:16  150.67MB 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
                        
# 2023-11-10 14:37:01  0.00B 设置环境变量 CUDA_VERSION
ENV CUDA_VERSION=11.8.0
                        
# 2023-11-10 14:37:01  10.56MB 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_1.0-1_all.deb &&     dpkg -i cuda-keyring_1.0-1_all.deb &&     apt-get purge --autoremove -y curl     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2023-11-10 14:37:01  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2023-11-10 14:37:01  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2023-11-10 14:37:01  0.00B 设置环境变量 NV_CUDA_COMPAT_PACKAGE
ENV NV_CUDA_COMPAT_PACKAGE=cuda-compat-11-8
                        
# 2023-11-10 14:37:01  0.00B 设置环境变量 NV_CUDA_CUDART_VERSION
ENV NV_CUDA_CUDART_VERSION=11.8.89-1
                        
# 2023-11-10 14:37:01  0.00B 设置环境变量 NVIDIA_REQUIRE_CUDA brand brand brand brand brand brand brand brand brand brand
ENV NVIDIA_REQUIRE_CUDA=cuda>=11.8 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
                        
# 2023-11-10 14:37:01  0.00B 设置环境变量 NVARCH
ENV NVARCH=x86_64
                        
# 2023-10-05 15:33:32  0.00B 
/bin/sh -c #(nop)  CMD ["/bin/bash"]
                        
# 2023-10-05 15:33:32  77.82MB 
/bin/sh -c #(nop) ADD file:63d5ab3ef0aab308c0e71cb67292c5467f60deafa9b0418cbb220affcd078444 in / 
                        
# 2023-10-05 15:33:30  0.00B 
/bin/sh -c #(nop)  LABEL org.opencontainers.image.version=22.04
                        
# 2023-10-05 15:33:30  0.00B 
/bin/sh -c #(nop)  LABEL org.opencontainers.image.ref.name=ubuntu
                        
# 2023-10-05 15:33:30  0.00B 
/bin/sh -c #(nop)  ARG LAUNCHPAD_BUILD_ARCH
                        
# 2023-10-05 15:33:30  0.00B 
/bin/sh -c #(nop)  ARG RELEASE
                        
                    

镜像信息

{
    "Id": "sha256:c3694cbe76d90b7050c4ae60c8d5d8faeeebd751f48f22cc3025df2523ec9c95",
    "RepoTags": [
        "wangcanlong/go-vad-asr-speaker-identification-grpc-server:v1.12.20-cu118",
        "swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/wangcanlong/go-vad-asr-speaker-identification-grpc-server:v1.12.20-cu118"
    ],
    "RepoDigests": [
        "wangcanlong/go-vad-asr-speaker-identification-grpc-server@sha256:808bc8d4546f357ed94dc66810929fc06e5658acc68f43d84c4a74173130d04b",
        "swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/wangcanlong/go-vad-asr-speaker-identification-grpc-server@sha256:808bc8d4546f357ed94dc66810929fc06e5658acc68f43d84c4a74173130d04b"
    ],
    "Parent": "",
    "Comment": "buildkit.dockerfile.v0",
    "Created": "2026-01-16T11:54:15.739518414+08:00",
    "Container": "",
    "ContainerConfig": null,
    "DockerVersion": "",
    "Author": "",
    "Config": {
        "Hostname": "",
        "Domainname": "",
        "User": "",
        "AttachStdin": false,
        "AttachStdout": false,
        "AttachStderr": false,
        "ExposedPorts": {
            "8080/tcp": {}
        },
        "Tty": false,
        "OpenStdin": false,
        "StdinOnce": false,
        "Env": [
            "PATH=/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\u003e=11.8 brand=tesla,driver\u003e=470,driver\u003c471 brand=unknown,driver\u003e=470,driver\u003c471 brand=nvidia,driver\u003e=470,driver\u003c471 brand=nvidiartx,driver\u003e=470,driver\u003c471 brand=geforce,driver\u003e=470,driver\u003c471 brand=geforcertx,driver\u003e=470,driver\u003c471 brand=quadro,driver\u003e=470,driver\u003c471 brand=quadrortx,driver\u003e=470,driver\u003c471 brand=titan,driver\u003e=470,driver\u003c471 brand=titanrtx,driver\u003e=470,driver\u003c471",
            "NV_CUDA_CUDART_VERSION=11.8.89-1",
            "NV_CUDA_COMPAT_PACKAGE=cuda-compat-11-8",
            "CUDA_VERSION=11.8.0",
            "LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64",
            "NVIDIA_VISIBLE_DEVICES=all",
            "NVIDIA_DRIVER_CAPABILITIES=compute,utility",
            "NV_CUDA_LIB_VERSION=11.8.0-1",
            "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",
            "NVIDIA_PRODUCT_NAME=CUDA",
            "NV_CUDA_CUDART_DEV_VERSION=11.8.89-1",
            "NV_NVML_DEV_VERSION=11.8.86-1",
            "NV_LIBCUSPARSE_DEV_VERSION=11.7.5.86-1",
            "NV_LIBNPP_DEV_VERSION=11.8.0.86-1",
            "NV_LIBNPP_DEV_PACKAGE=libnpp-dev-11-8=11.8.0.86-1",
            "NV_LIBCUBLAS_DEV_VERSION=11.11.3.6-1",
            "NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-11-8",
            "NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-11-8=11.11.3.6-1",
            "NV_CUDA_NSIGHT_COMPUTE_VERSION=11.8.0-1",
            "NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE=cuda-nsight-compute-11-8=11.8.0-1",
            "NV_NVPROF_VERSION=11.8.87-1",
            "NV_NVPROF_DEV_PACKAGE=cuda-nvprof-11-8=11.8.87-1",
            "NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev",
            "NV_LIBNCCL_DEV_PACKAGE_VERSION=2.15.5-1",
            "NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.15.5-1+cuda11.8",
            "LIBRARY_PATH=/usr/local/cuda/lib64/stubs",
            "NV_CUDNN_VERSION=8.9.6.50",
            "NV_CUDNN_PACKAGE_NAME=libcudnn8",
            "NV_CUDNN_PACKAGE=libcudnn8=8.9.6.50-1+cuda11.8",
            "NV_CUDNN_PACKAGE_DEV=libcudnn8-dev=8.9.6.50-1+cuda11.8",
            "TZ=Asia/Shanghai"
        ],
        "Cmd": null,
        "Image": "",
        "Volumes": null,
        "WorkingDir": "/home/go-vad-asr-speaker-identification-grpc-server",
        "Entrypoint": [
            "./go-vad-asr-speaker-identification-grpc-server"
        ],
        "OnBuild": null,
        "Labels": {
            "com.nvidia.cudnn.version": "8.9.6.50",
            "maintainer": "NVIDIA CORPORATION \u003ccudatools@nvidia.com\u003e",
            "org.opencontainers.image.ref.name": "ubuntu",
            "org.opencontainers.image.version": "22.04"
        }
    },
    "Architecture": "amd64",
    "Os": "linux",
    "Size": 13717079282,
    "GraphDriver": {
        "Data": {
            "LowerDir": "/var/lib/docker/overlay2/1e8751a9b955679ab9db8ccdf921c6a601eddee418f1025bc5c6bcddc574f9e2/diff:/var/lib/docker/overlay2/9413b602c50ef9b85914b35333aa396dd4f6ce5ef1a1f5e5651d9f4eec94de42/diff:/var/lib/docker/overlay2/9e1f33d0c4cd05dc3819a5fe4b9a7836d5c0415c4857fca6f9c1dc1e834fb466/diff:/var/lib/docker/overlay2/828bc5573c2bdcf95f9b80896ab97dcb3306d1fbee96f64f79b67cab1bdab79e/diff:/var/lib/docker/overlay2/1f3c0f5b1e284e8b64886afed238ad4d867671210086e4e00850ac5569a3a115/diff:/var/lib/docker/overlay2/a3253af5308b974c6545fbe7e10ffc80a4f54603675a81cdf290badb9b061f16/diff:/var/lib/docker/overlay2/a9420226831654dbd6e4801ab51558bfa6c7db815f32919a06636c1dcf523be0/diff:/var/lib/docker/overlay2/b78b7718284e46dfe3cf0182a3c87afa09c342773d8e5af6fcf9642375c2aea6/diff:/var/lib/docker/overlay2/ba2e37297321d945e1794759ca076ce9a63631dbc89c3838d874639e313fde6e/diff:/var/lib/docker/overlay2/bbdf6f8f27b93b86d6ee7e43e0df1798e534a4af87980707c8233d18add5c768/diff:/var/lib/docker/overlay2/d58f9dcd32028b5a33f415aa52c69c87cb7fccd4f13040d18d20aa6665f3f242/diff:/var/lib/docker/overlay2/f6421dfcf7122a40a0884e027ebd88a594dc26e4c6aeb7f9492699daa4afd9dc/diff:/var/lib/docker/overlay2/b7be7cffe2af233eeaf6a4f81d05b158d126d5dbd195ba99d0b5747b4d5ff85d/diff:/var/lib/docker/overlay2/1120239ad5d45ac84d9319daf372fa05db2bdc289f1c623c4d3ad06e05010231/diff:/var/lib/docker/overlay2/9ac6f6eb5bb065f4a0cd88b66ffd7fac7b06beaf335ffbd83ef8293bba067bac/diff:/var/lib/docker/overlay2/98c3f7304801d18afd8956204bb8f10cf8927ce002eb048c541baf3393aada14/diff:/var/lib/docker/overlay2/a639865c6523b12a3ca5e7e395cd4e36f1bb8a32729caecb49867ba293954ad5/diff:/var/lib/docker/overlay2/f996e45c947eb672236a6641012574efac29950d380ed0432824c91cda0ee123/diff:/var/lib/docker/overlay2/f2905627b4505cda033dd62b5a5dc1676edda5a6e1bda7cd6e6e2048fcf5aee0/diff",
            "MergedDir": "/var/lib/docker/overlay2/926a962189748c17899d06495f6048d073512f5b4e06df2cb71e92eb14cf01a7/merged",
            "UpperDir": "/var/lib/docker/overlay2/926a962189748c17899d06495f6048d073512f5b4e06df2cb71e92eb14cf01a7/diff",
            "WorkDir": "/var/lib/docker/overlay2/926a962189748c17899d06495f6048d073512f5b4e06df2cb71e92eb14cf01a7/work"
        },
        "Name": "overlay2"
    },
    "RootFS": {
        "Type": "layers",
        "Layers": [
            "sha256:256d88da41857db513b95b50ba9a9b28491b58c954e25477d5dad8abb465430b",
            "sha256:e6c05e83c163d632918d1c4906ee088b1e0d93a5bb3acfc6a268da52e76cc945",
            "sha256:d6b19a46b795f8b562888c6e2826a6b11f744ab98543268b4d45ee1af05ed1cf",
            "sha256:c0e21dcee62311c36e1f025307b3186a4b4a034f0b52011704402b39623b6587",
            "sha256:498bbcc60d01b2080fd6fc35117cb82c80ddd4eb8a654ee330dd91587b7ec90b",
            "sha256:bc352a27a0e47d42df7bc06e702351a4f3102d20016484c9613644dba63239e0",
            "sha256:399d155a03b034314cd9ea52e4e1feca44be4cf92ae172ba9c6ce14f5897f0a2",
            "sha256:dcb0f55f81ad931bb976c65730e4bafe7a03936d1fd1bd0fec6a9bcfde23561d",
            "sha256:345cfa465206a6d1cc0812481df7edbc4553b64a26c63ccda0e5b11b0f2bf81b",
            "sha256:23d753990c8d9e30e33dc706e188972e17fd21ae60b51bbce058d6d74aa08d29",
            "sha256:64758552f6fa927694d06ecab82c2a3d1f55e6bfb09c715b6d37f2963eaaa62c",
            "sha256:383e6312d4f952e0c59b0d42d00c8f4b6da63721e10ad4de2d8e7d26581c1391",
            "sha256:42b10655c53b72e9317ac929851bc4baafe50d1248f2e7f774ab8c1676a5bd5d",
            "sha256:f1dc5db80592c5c179007d59e337ece5406cc8587ba5a6510e634873465695b9",
            "sha256:c84f6ffa6701504378b8cf012db9a2a0e965903bf4c15d849d4d976beb1475d8",
            "sha256:e1f6fbeb9f98a3fe1e314ac1bc3443e5796a29b66ab3dc4ea8b132716227f56e",
            "sha256:6352d58a6f8dd67c250d2497229a60a6430b49b79590ae7a2c7d9b18866e74be",
            "sha256:48b536e685977e0dc077857a32449a06cfc1e1842ce785c258f08a5f6a7575ed",
            "sha256:489ee7b9223f718d050a8eb8bf0184cfbcc6221f99e6a8330f4f07edddf8e9d1",
            "sha256:489ee7b9223f718d050a8eb8bf0184cfbcc6221f99e6a8330f4f07edddf8e9d1"
        ]
    },
    "Metadata": {
        "LastTagTime": "2026-01-17T02:56:47.504936327+08:00"
    }
}

更多版本