docker.io/guiji2025/fish-speech-ziming:1.0.39 linux/amd64

docker.io/guiji2025/fish-speech-ziming:1.0.39 - 国内下载镜像源 浏览次数:454
```html

该镜像名称为 docker.io/guiji2025/fish-speech-ziming，根据名称推测，它可能是一个包含鱼类语音识别或相关功能的Docker镜像。 "fish-speech"暗示其功能与鱼类声音的处理有关，而"ziming"可能是项目名称或版本号等补充信息。 具体功能需要查看镜像的描述文档或运行该镜像后才能确定。

```
源镜像 docker.io/guiji2025/fish-speech-ziming:1.0.39
国内镜像 swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/guiji2025/fish-speech-ziming:1.0.39
镜像ID sha256:e030373ac56cc7ea056fb1a02ebfa36b1d0bd84da234ae65c5d1c6c12a7bc14f
镜像TAG 1.0.39
大小 31.26GB
镜像源 docker.io
项目信息 Docker-Hub主页 🚀项目TAG 🚀
CMD /bin/sh -c /bin/zsh
启动入口 /opt/nvidia/nvidia_entrypoint.sh
工作目录 /code
OS/平台 linux/amd64
浏览量 454 次
贡献者
镜像创建 2025-02-17T18:55:58.756660273+08:00
同步时间 2025-03-10 04:05
更新时间 2025-04-20 01:15
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>=12.1 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 NV_CUDA_CUDART_VERSION=12.1.105-1 NV_CUDA_COMPAT_PACKAGE=cuda-compat-12-1 CUDA_VERSION=12.1.1 LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64 NVIDIA_VISIBLE_DEVICES=all NVIDIA_DRIVER_CAPABILITIES=compute,utility NV_CUDA_LIB_VERSION=12.1.1-1 NV_NVTX_VERSION=12.1.105-1 NV_LIBNPP_VERSION=12.1.0.40-1 NV_LIBNPP_PACKAGE=libnpp-12-1=12.1.0.40-1 NV_LIBCUSPARSE_VERSION=12.1.0.106-1 NV_LIBCUBLAS_PACKAGE_NAME=libcublas-12-1 NV_LIBCUBLAS_VERSION=12.1.3.1-1 NV_LIBCUBLAS_PACKAGE=libcublas-12-1=12.1.3.1-1 NV_LIBNCCL_PACKAGE_NAME=libnccl2 NV_LIBNCCL_PACKAGE_VERSION=2.17.1-1 NCCL_VERSION=2.17.1-1 NV_LIBNCCL_PACKAGE=libnccl2=2.17.1-1+cuda12.1 NVIDIA_PRODUCT_NAME=CUDA NV_CUDA_CUDART_DEV_VERSION=12.1.105-1 NV_NVML_DEV_VERSION=12.1.105-1 NV_LIBCUSPARSE_DEV_VERSION=12.1.0.106-1 NV_LIBNPP_DEV_VERSION=12.1.0.40-1 NV_LIBNPP_DEV_PACKAGE=libnpp-dev-12-1=12.1.0.40-1 NV_LIBCUBLAS_DEV_VERSION=12.1.3.1-1 NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-12-1 NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-12-1=12.1.3.1-1 NV_CUDA_NSIGHT_COMPUTE_VERSION=12.1.1-1 NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE=cuda-nsight-compute-12-1=12.1.1-1 NV_NVPROF_VERSION=12.1.105-1 NV_NVPROF_DEV_PACKAGE=cuda-nvprof-12-1=12.1.105-1 NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev NV_LIBNCCL_DEV_PACKAGE_VERSION=2.17.1-1 NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.17.1-1+cuda12.1 LIBRARY_PATH=/usr/local/cuda/lib64/stubs NV_CUDNN_VERSION=8.9.0.131 NV_CUDNN_PACKAGE_NAME=libcudnn8 NV_CUDNN_PACKAGE=libcudnn8=8.9.0.131-1+cuda12.1 NV_CUDNN_PACKAGE_DEV=libcudnn8-dev=8.9.0.131-1+cuda12.1 DEBIAN_FRONTEND=noninteractive SHELL=/usr/bin/zsh
镜像标签
8.9.0.131: com.nvidia.cudnn.version NVIDIA CORPORATION <cudatools@nvidia.com>: maintainer ubuntu: org.opencontainers.image.ref.name 22.04: org.opencontainers.image.version
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无权限下载?点我修复 生成Docker Run命令

Docker拉取命令 

docker pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/guiji2025/fish-speech-ziming:1.0.39
docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/guiji2025/fish-speech-ziming:1.0.39  docker.io/guiji2025/fish-speech-ziming:1.0.39

Containerd拉取命令 

ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/guiji2025/fish-speech-ziming:1.0.39
ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/guiji2025/fish-speech-ziming:1.0.39  docker.io/guiji2025/fish-speech-ziming:1.0.39

Shell快速替换命令 

sed -i 's#guiji2025/fish-speech-ziming:1.0.39#swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/guiji2025/fish-speech-ziming:1.0.39#' 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/guiji2025/fish-speech-ziming:1.0.39 && docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/guiji2025/fish-speech-ziming:1.0.39  docker.io/guiji2025/fish-speech-ziming:1.0.39'

Ansible快速分发-Containerd 

#ansible k8s -m shell -a 'ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/guiji2025/fish-speech-ziming:1.0.39 && ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/guiji2025/fish-speech-ziming:1.0.39  docker.io/guiji2025/fish-speech-ziming:1.0.39'

镜像构建历史 


# 2025-02-17 18:55:58  0.00B 设置默认要执行的命令
CMD ["/bin/sh" "-c" "/bin/zsh"]
                        
# 2025-02-17 18:55:58  265.30KB 执行命令并创建新的镜像层
RUN /bin/sh -c cp /code/tools/rnnoise_new /usr/bin && chmod a+x /usr/bin/rnnoise_new # buildkit
                        
# 2025-02-17 18:55:56  1.49GB 复制新文件或目录到容器中
COPY . . # buildkit
                        
# 2025-01-09 10:20:01  243.94MB 执行命令并创建新的镜像层
RUN /bin/sh -c . /root/.bashrc && conda activate python310  && pip3 install ormsgpack -i https://mirrors.aliyun.com/pypi/simple/ && pip3 install silero-vad  -i https://pypi.tuna.tsinghua.edu.cn/simple/ && pip3 install websocket-client funasr aiofiles  -i https://mirrors.aliyun.com/pypi/simple/ # buildkit
                        
# 2024-10-09 13:49:25  0.00B 执行命令并创建新的镜像层
RUN /bin/sh -c rm -rf /code/* # buildkit
                        
# 2024-10-09 13:49:25  0.00B 设置环境变量 DEBIAN_FRONTEND
ENV DEBIAN_FRONTEND=noninteractive
                        
# 2024-10-09 13:49:23  0.00B 设置工作目录为/code
WORKDIR /code
                        
# 2024-07-26 16:10:28  0.00B 
/bin/sh -c #(nop)  CMD ["/bin/sh" "-c" "/bin/zsh"]
                        
# 2024-07-26 16:10:28  1.17GB 
/bin/sh -c #(nop) COPY dir:33e52ffa5b2daef7f8e22bc9a8164bf193b9843a2fa052120cf227fdcd60b705 in . 
                        
# 2024-07-26 16:10:10  3.09GB 
/bin/sh -c mkdir -p /root/.cache/whisper && cd /root/.cache/whisper && wget http://172.16.101.58:8888/whisper/large-v3.pt && cd /code
                        
# 2024-07-26 16:02:22  10.97MB 
/bin/sh -c . /root/.bashrc && conda activate python310  && pip3 install openai-whisper -i https://mirrors.aliyun.com/pypi/simple/
                        
# 2024-07-16 18:11:38  0.00B 
/bin/sh -c #(nop)  ENV DEBIAN_FRONTEND=noninteractive
                        
# 2024-07-16 18:11:38  0.00B 
/bin/sh -c #(nop) WORKDIR /code
                        
# 2024-07-16 11:36:53  0.00B 设置默认要执行的命令
CMD ["/bin/sh" "-c" "/bin/zsh"]
                        
# 2024-07-16 11:36:53  2.33GB 复制新文件或目录到容器中
COPY . . # buildkit
                        
# 2024-07-16 11:25:24  0.00B 执行命令并创建新的镜像层
RUN /bin/sh -c rm -f *.whl # buildkit
                        
# 2024-07-16 11:25:23  11.71MB 执行命令并创建新的镜像层
RUN /bin/sh -c . /root/.bashrc && conda activate python310  &&  wget http://172.16.101.58:8888/obs/huaweicloud-sdk-python-obs-3.22.2.zip     && pip3 install pycryptodome==3.10.1 cachetools  -i https://mirrors.aliyun.com/pypi/simple/      && unzip huaweicloud-sdk-python-obs-3.22.2.zip && cd huaweicloud-sdk-python-obs-3.22.2/src && python setup.py install # buildkit
                        
# 2024-07-15 14:28:13  12.94MB 执行命令并创建新的镜像层
RUN /bin/sh -c . /root/.bashrc && conda activate python310  && pip3 install aliyun-python-sdk-core==2.13.3 librosa pydub -i https://mirrors.aliyun.com/pypi/simple/ # buildkit
                        
# 2024-07-12 14:55:50  3.11MB 执行命令并创建新的镜像层
RUN /bin/sh -c . /root/.bashrc && conda activate python310  && pip3 install vector_quantize_pytorch pyaudio -i https://mirrors.aliyun.com/pypi/simple/ # buildkit
                        
# 2024-07-12 14:55:36  59.19MB 执行命令并创建新的镜像层
RUN /bin/sh -c apt-get update && apt-get install libasound2-dev portaudio19-dev libasound-dev portaudio19-dev libportaudio2 libportaudiocpp0 -y # buildkit
                        
# 2024-07-12 14:54:47  118.39MB 执行命令并创建新的镜像层
RUN /bin/sh -c . /root/.bashrc && conda activate python310  && pip3 install transformers natsort rich loralib uvicorn -i https://mirrors.aliyun.com/pypi/simple/ # buildkit
                        
# 2024-07-12 12:22:35  3.09MB 执行命令并创建新的镜像层
RUN /bin/sh -c . /root/.bashrc && conda activate python310  && pip3 install hydra-core  einops -i https://mirrors.aliyun.com/pypi/simple/ # buildkit
                        
# 2024-07-12 12:22:31  146.11MB 执行命令并创建新的镜像层
RUN /bin/sh -c . /root/.bashrc && conda activate python310  && pip3 install lightning wandb matplotlib -i https://mirrors.aliyun.com/pypi/simple/ # buildkit
                        
# 2024-07-12 12:20:35  0.00B 设置环境变量 SHELL
ENV SHELL=/usr/bin/zsh
                        
# 2024-07-12 12:20:35  2.55KB 执行命令并创建新的镜像层
RUN /bin/sh -c chsh -s /usr/bin/zsh # buildkit
                        
# 2024-07-12 12:20:35  851.45MB 执行命令并创建新的镜像层
RUN /bin/sh -c . /root/.bashrc && conda activate python310  &&  wget http://172.16.101.58:8888/nvidia/xgboost-2.1.0-py3-none-manylinux_2_28_x86_64.whl     && pip3 install xgboost-2.1.0-py3-none-manylinux_2_28_x86_64.whl -i https://mirrors.aliyun.com/pypi/simple/ # buildkit
                        
# 2024-07-12 12:07:23  326.24MB 执行命令并创建新的镜像层
RUN /bin/sh -c . /root/.bashrc && conda activate python310  && pip3 install librosa  pyrootutils kui  loguru num2words nltk  -i https://mirrors.aliyun.com/pypi/simple/ # buildkit
                        
# 2024-07-12 12:01:49  187.30MB 执行命令并创建新的镜像层
RUN /bin/sh -c . /root/.bashrc && conda activate python310  &&  wget http://172.16.101.58:8888/nvidia/scipy-1.14.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl     && pip3 install scipy-1.14.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl -i https://mirrors.aliyun.com/pypi/simple/ # buildkit
                        
# 2024-07-12 11:50:41  10.09GB 执行命令并创建新的镜像层
RUN /bin/sh -c . /root/.bashrc      && conda activate python310 && conda config --set ssl_verify false      &&  conda install pytorch torchvision torchaudio pytorch-cuda=12.1 -c pytorch -c nvidia # buildkit
                        
# 2024-07-11 20:29:38  345.93MB 执行命令并创建新的镜像层
RUN /bin/sh -c . /root/.bashrc     && conda config --add channels http://mirrors.lzu.edu.cn/anaconda/pkgs/main/     && conda config --add channels http://mirrors.lzu.edu.cn/anaconda/pkgs/free/     && conda config --set show_channel_urls yes     && conda create -n python310 python=3.10     && conda activate python310 # buildkit
                        
# 2024-07-11 20:28:59  480.58MB 执行命令并创建新的镜像层
RUN /bin/sh -c cd /code     && wget --no-check-certificate https://mirror.lzu.edu.cn/anaconda/miniconda/Miniconda3-py310_23.5.1-0-Linux-x86_64.sh     && bash Miniconda3-py310_23.5.1-0-Linux-x86_64.sh -b -p /opt/conda     && rm -f Miniconda3-py310_23.5.1-0-Linux-x86_64.sh     && ln -s /opt/conda/etc/profile.d/conda.sh /etc/profile.d/conda.sh     && echo ". /opt/conda/etc/profile.d/conda.sh" >> ~/.bashrc # buildkit
                        
# 2024-07-11 18:05:56  589.26MB 执行命令并创建新的镜像层
RUN /bin/sh -c apt-get install -y git curl build-essential ffmpeg libsm6 libxext6     zlib1g-dev aria2 zsh openssh-server sudo protobuf-compiler cmake libsox-dev &&     apt-get clean && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2024-07-11 15:20:28  221.47MB 执行命令并创建新的镜像层
RUN /bin/sh -c apt-get update  && apt-get install -y gcc make zlib1g-dev  libbz2-dev libxml2-dev libffi-dev libssl-dev libxslt1-dev vim wget unzip # buildkit
                        
# 2024-07-11 15:20:28  0.00B 设置环境变量 DEBIAN_FRONTEND
ENV DEBIAN_FRONTEND=noninteractive
                        
# 2024-07-11 15:12:40  0.00B 设置工作目录为/code
WORKDIR /code
                        
# 2023-11-10 13:52:16  2.45GB 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 13:52:16  0.00B 添加元数据标签
LABEL com.nvidia.cudnn.version=8.9.0.131
                        
# 2023-11-10 13:52:16  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2023-11-10 13:52:16  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2023-11-10 13:52:16  0.00B 设置环境变量 NV_CUDNN_PACKAGE_DEV
ENV NV_CUDNN_PACKAGE_DEV=libcudnn8-dev=8.9.0.131-1+cuda12.1
                        
# 2023-11-10 13:52:16  0.00B 设置环境变量 NV_CUDNN_PACKAGE
ENV NV_CUDNN_PACKAGE=libcudnn8=8.9.0.131-1+cuda12.1
                        
# 2023-11-10 13:52:16  0.00B 设置环境变量 NV_CUDNN_PACKAGE_NAME
ENV NV_CUDNN_PACKAGE_NAME=libcudnn8
                        
# 2023-11-10 13:52:16  0.00B 设置环境变量 NV_CUDNN_VERSION
ENV NV_CUDNN_VERSION=8.9.0.131
                        
# 2023-11-10 13:25:51  0.00B 设置环境变量 LIBRARY_PATH
ENV LIBRARY_PATH=/usr/local/cuda/lib64/stubs
                        
# 2023-11-10 13:25:51  385.69KB 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 13:25:51  4.79GB 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-12-1=${NV_CUDA_CUDART_DEV_VERSION}     cuda-command-line-tools-12-1=${NV_CUDA_LIB_VERSION}     cuda-minimal-build-12-1=${NV_CUDA_LIB_VERSION}     cuda-libraries-dev-12-1=${NV_CUDA_LIB_VERSION}     cuda-nvml-dev-12-1=${NV_NVML_DEV_VERSION}     ${NV_NVPROF_DEV_PACKAGE}     ${NV_LIBNPP_DEV_PACKAGE}     libcusparse-dev-12-1=${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 13:25:51  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2023-11-10 13:25:51  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2023-11-10 13:25:51  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE
ENV NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.17.1-1+cuda12.1
                        
# 2023-11-10 13:25:51  0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.17.1-1
                        
# 2023-11-10 13:25:51  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE_VERSION
ENV NV_LIBNCCL_DEV_PACKAGE_VERSION=2.17.1-1
                        
# 2023-11-10 13:25:51  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE_NAME
ENV NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev
                        
# 2023-11-10 13:25:51  0.00B 设置环境变量 NV_NVPROF_DEV_PACKAGE
ENV NV_NVPROF_DEV_PACKAGE=cuda-nvprof-12-1=12.1.105-1
                        
# 2023-11-10 13:25:51  0.00B 设置环境变量 NV_NVPROF_VERSION
ENV NV_NVPROF_VERSION=12.1.105-1
                        
# 2023-11-10 13:25:51  0.00B 设置环境变量 NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE
ENV NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE=cuda-nsight-compute-12-1=12.1.1-1
                        
# 2023-11-10 13:25:51  0.00B 设置环境变量 NV_CUDA_NSIGHT_COMPUTE_VERSION
ENV NV_CUDA_NSIGHT_COMPUTE_VERSION=12.1.1-1
                        
# 2023-11-10 13:25:51  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_PACKAGE
ENV NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-12-1=12.1.3.1-1
                        
# 2023-11-10 13:25:51  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_PACKAGE_NAME
ENV NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-12-1
                        
# 2023-11-10 13:25:51  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_VERSION
ENV NV_LIBCUBLAS_DEV_VERSION=12.1.3.1-1
                        
# 2023-11-10 13:25:51  0.00B 设置环境变量 NV_LIBNPP_DEV_PACKAGE
ENV NV_LIBNPP_DEV_PACKAGE=libnpp-dev-12-1=12.1.0.40-1
                        
# 2023-11-10 13:25:51  0.00B 设置环境变量 NV_LIBNPP_DEV_VERSION
ENV NV_LIBNPP_DEV_VERSION=12.1.0.40-1
                        
# 2023-11-10 13:25:51  0.00B 设置环境变量 NV_LIBCUSPARSE_DEV_VERSION
ENV NV_LIBCUSPARSE_DEV_VERSION=12.1.0.106-1
                        
# 2023-11-10 13:25:51  0.00B 设置环境变量 NV_NVML_DEV_VERSION
ENV NV_NVML_DEV_VERSION=12.1.105-1
                        
# 2023-11-10 13:25:51  0.00B 设置环境变量 NV_CUDA_CUDART_DEV_VERSION
ENV NV_CUDA_CUDART_DEV_VERSION=12.1.105-1
                        
# 2023-11-10 13:25:51  0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=12.1.1-1
                        
# 2023-11-10 13:13:35  0.00B 配置容器启动时运行的命令
ENTRYPOINT ["/opt/nvidia/nvidia_entrypoint.sh"]
                        
# 2023-11-10 13:13:35  0.00B 设置环境变量 NVIDIA_PRODUCT_NAME
ENV NVIDIA_PRODUCT_NAME=CUDA
                        
# 2023-11-10 13:13:35  2.53KB 复制新文件或目录到容器中
COPY nvidia_entrypoint.sh /opt/nvidia/ # buildkit
                        
# 2023-11-10 13:13:35  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 13:13:35  261.40KB 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 13:13:35  2.01GB 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-12-1=${NV_CUDA_LIB_VERSION}     ${NV_LIBNPP_PACKAGE}     cuda-nvtx-12-1=${NV_NVTX_VERSION}     libcusparse-12-1=${NV_LIBCUSPARSE_VERSION}     ${NV_LIBCUBLAS_PACKAGE}     ${NV_LIBNCCL_PACKAGE}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2023-11-10 13:13:35  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2023-11-10 13:13:35  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2023-11-10 13:13:35  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE
ENV NV_LIBNCCL_PACKAGE=libnccl2=2.17.1-1+cuda12.1
                        
# 2023-11-10 13:13:35  0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.17.1-1
                        
# 2023-11-10 13:13:35  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_VERSION
ENV NV_LIBNCCL_PACKAGE_VERSION=2.17.1-1
                        
# 2023-11-10 13:13:35  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_NAME
ENV NV_LIBNCCL_PACKAGE_NAME=libnccl2
                        
# 2023-11-10 13:13:35  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE
ENV NV_LIBCUBLAS_PACKAGE=libcublas-12-1=12.1.3.1-1
                        
# 2023-11-10 13:13:35  0.00B 设置环境变量 NV_LIBCUBLAS_VERSION
ENV NV_LIBCUBLAS_VERSION=12.1.3.1-1
                        
# 2023-11-10 13:13:35  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE_NAME
ENV NV_LIBCUBLAS_PACKAGE_NAME=libcublas-12-1
                        
# 2023-11-10 13:13:35  0.00B 设置环境变量 NV_LIBCUSPARSE_VERSION
ENV NV_LIBCUSPARSE_VERSION=12.1.0.106-1
                        
# 2023-11-10 13:13:35  0.00B 设置环境变量 NV_LIBNPP_PACKAGE
ENV NV_LIBNPP_PACKAGE=libnpp-12-1=12.1.0.40-1
                        
# 2023-11-10 13:13:35  0.00B 设置环境变量 NV_LIBNPP_VERSION
ENV NV_LIBNPP_VERSION=12.1.0.40-1
                        
# 2023-11-10 13:13:35  0.00B 设置环境变量 NV_NVTX_VERSION
ENV NV_NVTX_VERSION=12.1.105-1
                        
# 2023-11-10 13:13:35  0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=12.1.1-1
                        
# 2023-11-10 13:08:12  0.00B 设置环境变量 NVIDIA_DRIVER_CAPABILITIES
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
                        
# 2023-11-10 13:08:12  0.00B 设置环境变量 NVIDIA_VISIBLE_DEVICES
ENV NVIDIA_VISIBLE_DEVICES=all
                        
# 2023-11-10 13:08:12  17.29KB 复制新文件或目录到容器中
COPY NGC-DL-CONTAINER-LICENSE / # buildkit
                        
# 2023-11-10 13:08:12  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 13:08:12  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 13:08:12  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 13:08:11  149.59MB 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-12-1=${NV_CUDA_CUDART_VERSION}     ${NV_CUDA_COMPAT_PACKAGE}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2023-11-10 13:07:58  0.00B 设置环境变量 CUDA_VERSION
ENV CUDA_VERSION=12.1.1
                        
# 2023-11-10 13:07:58  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 13:07:58  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2023-11-10 13:07:58  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2023-11-10 13:07:58  0.00B 设置环境变量 NV_CUDA_COMPAT_PACKAGE
ENV NV_CUDA_COMPAT_PACKAGE=cuda-compat-12-1
                        
# 2023-11-10 13:07:58  0.00B 设置环境变量 NV_CUDA_CUDART_VERSION
ENV NV_CUDA_CUDART_VERSION=12.1.105-1
                        
# 2023-11-10 13:07:58  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
ENV NVIDIA_REQUIRE_CUDA=cuda>=12.1 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
                        
# 2023-11-10 13:07:58  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 

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    "Comment": "buildkit.dockerfile.v0",
    "Created": "2025-02-17T18:55:58.756660273+08:00",
    "Container": "",
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    "DockerVersion": "",
    "Author": "",
    "Config": {
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        "AttachStdin": false,
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            "NVARCH=x86_64",
            "NVIDIA_REQUIRE_CUDA=cuda\u003e=12.1 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 brand=tesla,driver\u003e=525,driver\u003c526 brand=unknown,driver\u003e=525,driver\u003c526 brand=nvidia,driver\u003e=525,driver\u003c526 brand=nvidiartx,driver\u003e=525,driver\u003c526 brand=geforce,driver\u003e=525,driver\u003c526 brand=geforcertx,driver\u003e=525,driver\u003c526 brand=quadro,driver\u003e=525,driver\u003c526 brand=quadrortx,driver\u003e=525,driver\u003c526 brand=titan,driver\u003e=525,driver\u003c526 brand=titanrtx,driver\u003e=525,driver\u003c526",
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            "NV_CUDA_COMPAT_PACKAGE=cuda-compat-12-1",
            "CUDA_VERSION=12.1.1",
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            "NVIDIA_VISIBLE_DEVICES=all",
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            "NCCL_VERSION=2.17.1-1",
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            "NVIDIA_PRODUCT_NAME=CUDA",
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            "NV_NVML_DEV_VERSION=12.1.105-1",
            "NV_LIBCUSPARSE_DEV_VERSION=12.1.0.106-1",
            "NV_LIBNPP_DEV_VERSION=12.1.0.40-1",
            "NV_LIBNPP_DEV_PACKAGE=libnpp-dev-12-1=12.1.0.40-1",
            "NV_LIBCUBLAS_DEV_VERSION=12.1.3.1-1",
            "NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-12-1",
            "NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-12-1=12.1.3.1-1",
            "NV_CUDA_NSIGHT_COMPUTE_VERSION=12.1.1-1",
            "NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE=cuda-nsight-compute-12-1=12.1.1-1",
            "NV_NVPROF_VERSION=12.1.105-1",
            "NV_NVPROF_DEV_PACKAGE=cuda-nvprof-12-1=12.1.105-1",
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    "Metadata": {
        "LastTagTime": "2025-03-10T03:33:06.821645834+08:00"
    }
}

更多版本

docker.io/guiji2025/fish-speech-ziming:1.0.39

linux/amd64 docker.io31.26GB2025-03-10 04:05
453