镜像构建历史
# 2023-10-27 19:58:13 0.00B 设置工作目录为/home/anaconda
WORKDIR /home/anaconda
# 2023-10-27 19:58:13 0.00B 指定运行容器时使用的用户
USER 1000
# 2023-10-27 19:58:13 2.47MB 执行命令并创建新的镜像层
RUN |1 FFMPEG_VERSION=5.0.2 /bin/bash -o pipefail -c apt-get --purge -y autoremove wget && rm -rf /var/lib/apt/lists/* /var/cache/apt/archives/* ${HOME}/FFmpeg* && rm -rvf /home/${ANACONDA_PATH}/.cache/yarn && fix-permissions ${HOME} && fix-permissions ${ANACONDA_PATH} # buildkit
# 2023-10-27 19:58:11 0.00B 执行命令并创建新的镜像层
RUN |1 FFMPEG_VERSION=5.0.2 /bin/bash -o pipefail -c conda clean -afy # buildkit
# 2023-10-27 19:58:10 0.00B 指定运行容器时使用的用户
USER root
# 2023-10-27 19:58:10 3.89KB 执行命令并创建新的镜像层
RUN |1 FFMPEG_VERSION=5.0.2 /bin/bash -o pipefail -c echo 'PATH="/usr/local/ffmpeg-nvidia/bin:$PATH"' >> ${HOME}/.bashrc # buildkit
# 2023-10-27 19:58:10 0.00B 执行命令并创建新的镜像层
RUN |1 FFMPEG_VERSION=5.0.2 /bin/bash -o pipefail -c cd ${HOME} && rm -rvf ${HOME}/ffmpeg-${FFMPEG_VERSION}.tar.gz ${HOME}/ffmpeg-${FFMPEG_VERSION} # buildkit
# 2023-10-27 19:58:09 0.00B 指定运行容器时使用的用户
USER 1000
# 2023-10-27 19:58:09 624.55MB 执行命令并创建新的镜像层
RUN |1 FFMPEG_VERSION=5.0.2 /bin/bash -o pipefail -c cd ${HOME}/ffmpeg-${FFMPEG_VERSION} && make install # buildkit
# 2023-10-27 19:58:04 0.00B 指定运行容器时使用的用户
USER root
# 2023-10-27 19:58:04 1.33GB 执行命令并创建新的镜像层
RUN |1 FFMPEG_VERSION=5.0.2 /bin/bash -o pipefail -c wget -O ${HOME}/ffmpeg-${FFMPEG_VERSION}.tar.gz https://ffmpeg.org/releases/ffmpeg-${FFMPEG_VERSION}.tar.gz && tar -xvf ${HOME}/ffmpeg-${FFMPEG_VERSION}.tar.gz && cd ${HOME}/ffmpeg-${FFMPEG_VERSION} && ./configure --prefix=/usr/local/ffmpeg-nvidia --extra-cflags=-I/usr/local/cuda/include --extra-ldflags=-L/usr/local/cuda/lib64 --toolchain=hardened --enable-gpl --disable-stripping --disable-filter=resample --enable-cuvid --enable-gnutls --enable-ladspa --enable-libaom --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libcodec2 --enable-libfdk-aac --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libjack --enable-libmp3lame --enable-libmysofa --enable-libnpp --enable-libopenjpeg --enable-libopenmpt --enable-libopus --enable-libpulse --enable-librsvg --enable-librubberband --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvorbis --enable-libvidstab --enable-libvpx --enable-libwebp --enable-libx265 --enable-libxml2 --enable-libxvid --enable-libzmq --enable-libzvbi --enable-lv2 --enable-nvenc --enable-nonfree --enable-omx --enable-openal --enable-opencl --enable-opengl --enable-sdl2 && make -j 8 # buildkit
# 2023-10-27 19:50:18 0.00B 设置工作目录为/home/anaconda
WORKDIR /home/anaconda
# 2023-10-27 19:50:18 0.00B 指定运行容器时使用的用户
USER 1000
# 2023-10-27 19:50:18 1.16GB 执行命令并创建新的镜像层
RUN |1 FFMPEG_VERSION=5.0.2 /bin/bash -o pipefail -c apt-get -y install cleancss doxygen debhelper-compat flite1-dev frei0r-plugins-dev ladspa-sdk libaom-dev libaribb24-dev libass-dev libbluray-dev libbs2b-dev libbz2-dev libcaca-dev libcdio-paranoia-dev libchromaprint-dev libcodec2-dev libdc1394-dev libdrm-dev libfdk-aac-dev libffmpeg-nvenc-dev libfontconfig1-dev libfreetype6-dev libfribidi-dev libgl1-mesa-dev libgme-dev libgnutls28-dev libgsm1-dev libiec61883-dev libavc1394-dev libjack-jackd2-dev liblensfun-dev liblilv-dev liblzma-dev libmp3lame-dev libmysofa-dev libnvidia-compute-470-server libnvidia-decode-470-server libnvidia-encode-470-server libopenal-dev libomxil-bellagio-dev libopencore-amrnb-dev libopencore-amrwb-dev libopenjp2-7-dev libopenmpt-dev libopus-dev libpulse-dev librubberband-dev librsvg2-dev libsctp-dev libsdl2-dev libshine-dev libsnappy-dev libsoxr-dev libspeex-dev libssh-gcrypt-dev libtesseract-dev libtheora-dev libtwolame-dev libva-dev libvdpau-dev libvidstab-dev libvo-amrwbenc-dev libvorbis-dev libvpx-dev libwavpack-dev libwebp-dev libx264-dev libx265-dev libxcb-shape0-dev libxcb-shm0-dev libxcb-xfixes0-dev libxml2-dev libxv-dev libxvidcore-dev libxvmc-dev libzmq3-dev libzvbi-dev nasm node-less ocl-icd-opencl-dev pkg-config texinfo tree wget zlib1g-dev # buildkit
# 2023-10-27 19:49:27 276.21MB 执行命令并创建新的镜像层
RUN |1 FFMPEG_VERSION=5.0.2 /bin/bash -o pipefail -c apt-get update --fix-missing && apt-get -y upgrade && apt-get -y dist-upgrade # buildkit
# 2023-10-27 19:49:27 0.00B 指定运行容器时使用的用户
USER root
# 2023-10-27 19:49:27 0.00B 设置环境变量 FFMPEG_VERSION
ENV FFMPEG_VERSION=5.0.2
# 2023-10-27 19:49:27 0.00B 定义构建参数
ARG FFMPEG_VERSION=5.0.2
# 2023-10-27 19:49:27 0.00B 添加元数据标签
LABEL description=FFmpeg GPU Container w/ Jupyter Notebooks
# 2023-10-27 14:47:41 0.00B 设置工作目录为/home/anaconda
WORKDIR /home/anaconda
# 2023-10-27 14:47:41 0.00B 指定运行容器时使用的用户
USER 1000
# 2023-10-27 14:47:41 4.29KB 执行命令并创建新的镜像层
RUN |5 JUPYTER_LAB_VERSION=4.0.3 JUPYTER_HUB_VERSION=4.0.1 JUPYTER_NB_CK_VERSION=2.3.1 JUPYTER_IPYWIDGETS_VERSION=8.0.7 JUPYTER_IPYKERNEL=6.24.0 /bin/bash -o pipefail -c sed -re "s/c.ServerApp/c.NotebookApp/g" /etc/jupyter/jupyter_server_config.py > /etc/jupyter/jupyter_notebook_config.py && fix-permissions /etc/jupyter/ # buildkit
# 2023-10-27 14:47:41 0.00B 指定运行容器时使用的用户
USER root
# 2023-10-27 14:47:41 2.47KB 复制新文件或目录到容器中
COPY scripts/jupyter_server_config.py scripts/docker_healthcheck.py /etc/jupyter/ # buildkit
# 2023-10-27 14:47:41 0.00B 设置默认要执行的命令
CMD ["jupyter" "lab"]
# 2023-10-27 14:47:41 0.00B 配置容器启动时运行的命令
ENTRYPOINT ["tini" "-g" "--"]
# 2023-10-27 14:47:41 0.00B 声明容器运行时监听的端口
EXPOSE map[8888/tcp:{}]
# 2023-10-27 14:47:41 144.99MB 执行命令并创建新的镜像层
RUN |5 JUPYTER_LAB_VERSION=4.0.3 JUPYTER_HUB_VERSION=4.0.1 JUPYTER_NB_CK_VERSION=2.3.1 JUPYTER_IPYWIDGETS_VERSION=8.0.7 JUPYTER_IPYKERNEL=6.24.0 /bin/bash -o pipefail -c conda clean -afy && fix-permissions ${HOME} && fix-permissions ${ANACONDA_PATH} # buildkit
# 2023-10-27 14:47:33 77.57KB 执行命令并创建新的镜像层
RUN |5 JUPYTER_LAB_VERSION=4.0.3 JUPYTER_HUB_VERSION=4.0.1 JUPYTER_NB_CK_VERSION=2.3.1 JUPYTER_IPYWIDGETS_VERSION=8.0.7 JUPYTER_IPYKERNEL=6.24.0 /bin/bash -o pipefail -c jupyter lab --generate-config # buildkit
# 2023-10-27 14:47:31 780.91MB 执行命令并创建新的镜像层
RUN |5 JUPYTER_LAB_VERSION=4.0.3 JUPYTER_HUB_VERSION=4.0.1 JUPYTER_NB_CK_VERSION=2.3.1 JUPYTER_IPYWIDGETS_VERSION=8.0.7 JUPYTER_IPYKERNEL=6.24.0 /bin/bash -o pipefail -c conda install -c conda-forge jupyterlab=${JUPYTER_LAB_VERSION} nb_conda_kernels=${JUPYTER_NB_CK_VERSION} ipywidgets=${JUPYTER_IPYWIDGETS_VERSION} ipykernel=${JUPYTER_IPYKERNEL} # buildkit
# 2023-10-27 14:45:01 160.86MB 执行命令并创建新的镜像层
RUN |5 JUPYTER_LAB_VERSION=4.0.3 JUPYTER_HUB_VERSION=4.0.1 JUPYTER_NB_CK_VERSION=2.3.1 JUPYTER_IPYWIDGETS_VERSION=8.0.7 JUPYTER_IPYKERNEL=6.24.0 /bin/bash -o pipefail -c conda update -c defaults conda # buildkit
# 2023-10-27 14:44:17 0.00B 设置工作目录为/home/anaconda
WORKDIR /home/anaconda
# 2023-10-27 14:44:17 0.00B 指定运行容器时使用的用户
USER 1000
# 2023-10-27 14:44:17 0.00B 设置环境变量 JUPYTER_IPYKERNEL
ENV JUPYTER_IPYKERNEL=6.24.0
# 2023-10-27 14:44:17 0.00B 设置环境变量 JUPYTER_IPYWIDGETS_VERSION
ENV JUPYTER_IPYWIDGETS_VERSION=8.0.7
# 2023-10-27 14:44:17 0.00B 设置环境变量 JUPYTER_NB_CK_VERSION
ENV JUPYTER_NB_CK_VERSION=2.3.1
# 2023-10-27 14:44:17 0.00B 设置环境变量 JUPYTER_LAB_VERSION
ENV JUPYTER_LAB_VERSION=4.0.3
# 2023-10-27 14:44:17 0.00B 定义构建参数
ARG JUPYTER_IPYKERNEL=6.24.0
# 2023-10-27 14:44:17 0.00B 定义构建参数
ARG JUPYTER_IPYWIDGETS_VERSION=8.0.7
# 2023-10-27 14:44:17 0.00B 定义构建参数
ARG JUPYTER_NB_CK_VERSION=2.3.1
# 2023-10-27 14:44:17 0.00B 定义构建参数
ARG JUPYTER_HUB_VERSION=4.0.1
# 2023-10-27 14:44:17 0.00B 定义构建参数
ARG JUPYTER_LAB_VERSION=4.0.3
# 2023-10-27 14:44:17 0.00B 添加元数据标签
LABEL description=Anaconda 3 GPU Container w/ Jupyter Notebooks
# 2023-10-27 14:39:17 0.00B 设置工作目录为/home/anaconda
WORKDIR /home/anaconda
# 2023-10-27 14:39:17 0.00B 指定运行容器时使用的用户
USER 1000
# 2023-10-27 14:39:17 0.00B 设置默认要执行的命令
CMD ["/bin/bash"]
# 2023-10-27 14:39:17 0.00B 配置容器启动时运行的命令
ENTRYPOINT ["tini" "-g" "--"]
# 2023-10-27 14:39:17 762.70KB 执行命令并创建新的镜像层
RUN |15 ANACONDA_CONTAINER=v23.3.1 ANACONDA_DIST=Miniconda3 ANACONDA_PYTHON=py310 ANACONDA_CONDA=23.3.1 ANACONDA_OS=Linux ANACONDA_ARCH=x86_64 ANACONDA_FLAVOR=Miniforge3 ANACONDA_PATCH=1 ANACONDA_VERSION=23.3.1-1 ANACONDA_INSTALLER=Miniforge3-23.3.1-1-Linux-x86_64.sh ANACONDA_ENV=base ANACONDA_GID=100 ANACONDA_PATH=/usr/local/anaconda3 ANACONDA_UID=1000 ANACONDA_USER=anaconda /bin/bash -o pipefail -c apt-get --purge -y remove wget curl && apt-get --purge -y autoremove && rm -rf /var/lib/apt/lists/* /var/cache/apt/archives/* && rm -rvf /home/${ANACONDA_PATH}/.cache/yarn # buildkit
# 2023-10-27 14:39:14 43.00B 执行命令并创建新的镜像层
RUN |15 ANACONDA_CONTAINER=v23.3.1 ANACONDA_DIST=Miniconda3 ANACONDA_PYTHON=py310 ANACONDA_CONDA=23.3.1 ANACONDA_OS=Linux ANACONDA_ARCH=x86_64 ANACONDA_FLAVOR=Miniforge3 ANACONDA_PATCH=1 ANACONDA_VERSION=23.3.1-1 ANACONDA_INSTALLER=Miniforge3-23.3.1-1-Linux-x86_64.sh ANACONDA_ENV=base ANACONDA_GID=100 ANACONDA_PATH=/usr/local/anaconda3 ANACONDA_UID=1000 ANACONDA_USER=anaconda /bin/bash -o pipefail -c ln -s ${ANACONDA_PATH}/etc/profile.d/conda.sh /etc/profile.d/conda.sh && fix-permissions /etc/profile.d/conda.sh # buildkit
# 2023-10-27 14:39:14 239.24MB 执行命令并创建新的镜像层
RUN |15 ANACONDA_CONTAINER=v23.3.1 ANACONDA_DIST=Miniconda3 ANACONDA_PYTHON=py310 ANACONDA_CONDA=23.3.1 ANACONDA_OS=Linux ANACONDA_ARCH=x86_64 ANACONDA_FLAVOR=Miniforge3 ANACONDA_PATCH=1 ANACONDA_VERSION=23.3.1-1 ANACONDA_INSTALLER=Miniforge3-23.3.1-1-Linux-x86_64.sh ANACONDA_ENV=base ANACONDA_GID=100 ANACONDA_PATH=/usr/local/anaconda3 ANACONDA_UID=1000 ANACONDA_USER=anaconda /bin/bash -o pipefail -c conda clean -afy && fix-permissions ${HOME} && fix-permissions ${ANACONDA_PATH} # buildkit
# 2023-10-27 14:39:08 0.00B 指定运行容器时使用的用户
USER root
# 2023-10-27 14:39:08 659.83KB 执行命令并创建新的镜像层
RUN |15 ANACONDA_CONTAINER=v23.3.1 ANACONDA_DIST=Miniconda3 ANACONDA_PYTHON=py310 ANACONDA_CONDA=23.3.1 ANACONDA_OS=Linux ANACONDA_ARCH=x86_64 ANACONDA_FLAVOR=Miniforge3 ANACONDA_PATCH=1 ANACONDA_VERSION=23.3.1-1 ANACONDA_INSTALLER=Miniforge3-23.3.1-1-Linux-x86_64.sh ANACONDA_ENV=base ANACONDA_GID=100 ANACONDA_PATH=/usr/local/anaconda3 ANACONDA_UID=1000 ANACONDA_USER=anaconda /bin/bash -o pipefail -c conda install -y tini # buildkit
# 2023-10-27 14:38:51 26.00B 执行命令并创建新的镜像层
RUN |15 ANACONDA_CONTAINER=v23.3.1 ANACONDA_DIST=Miniconda3 ANACONDA_PYTHON=py310 ANACONDA_CONDA=23.3.1 ANACONDA_OS=Linux ANACONDA_ARCH=x86_64 ANACONDA_FLAVOR=Miniforge3 ANACONDA_PATCH=1 ANACONDA_VERSION=23.3.1-1 ANACONDA_INSTALLER=Miniforge3-23.3.1-1-Linux-x86_64.sh ANACONDA_ENV=base ANACONDA_GID=100 ANACONDA_PATH=/usr/local/anaconda3 ANACONDA_UID=1000 ANACONDA_USER=anaconda /bin/bash -o pipefail -c conda config --add channels conda-forge # buildkit
# 2023-10-27 14:38:50 486.19MB 执行命令并创建新的镜像层
RUN |15 ANACONDA_CONTAINER=v23.3.1 ANACONDA_DIST=Miniconda3 ANACONDA_PYTHON=py310 ANACONDA_CONDA=23.3.1 ANACONDA_OS=Linux ANACONDA_ARCH=x86_64 ANACONDA_FLAVOR=Miniforge3 ANACONDA_PATCH=1 ANACONDA_VERSION=23.3.1-1 ANACONDA_INSTALLER=Miniforge3-23.3.1-1-Linux-x86_64.sh ANACONDA_ENV=base ANACONDA_GID=100 ANACONDA_PATH=/usr/local/anaconda3 ANACONDA_UID=1000 ANACONDA_USER=anaconda /bin/bash -o pipefail -c conda update -c defaults conda # buildkit
# 2023-10-27 14:37:51 391.66MB 执行命令并创建新的镜像层
RUN |15 ANACONDA_CONTAINER=v23.3.1 ANACONDA_DIST=Miniconda3 ANACONDA_PYTHON=py310 ANACONDA_CONDA=23.3.1 ANACONDA_OS=Linux ANACONDA_ARCH=x86_64 ANACONDA_FLAVOR=Miniforge3 ANACONDA_PATCH=1 ANACONDA_VERSION=23.3.1-1 ANACONDA_INSTALLER=Miniforge3-23.3.1-1-Linux-x86_64.sh ANACONDA_ENV=base ANACONDA_GID=100 ANACONDA_PATH=/usr/local/anaconda3 ANACONDA_UID=1000 ANACONDA_USER=anaconda /bin/bash -o pipefail -c wget --verbose -O ~/${ANACONDA_VERSION}.sh https://github.com/conda-forge/miniforge/releases/download/${ANACONDA_VERSION}/${ANACONDA_INSTALLER} && /bin/bash /home/${ANACONDA_USER}/${ANACONDA_VERSION}.sh -b -u -p ${ANACONDA_PATH} && chown -R ${ANACONDA_USER} ${ANACONDA_PATH} && rm -rvf ~/${ANACONDA_VERSION}.sh && echo ". ${ANACONDA_PATH}/etc/profile.d/conda.sh" >> ~/.bashrc && echo "conda activate \${ANACONDA_ENV}" >> ~/.bashrc && find ${ANACONDA_PATH} -follow -type f -name '*.a' -delete && find ${ANACONDA_PATH} -follow -type f -name '*.js.map' -delete && fix-permissions ${HOME} && fix-permissions ${ANACONDA_PATH} # buildkit
# 2023-10-27 14:37:39 0.00B 设置工作目录为/home/anaconda
WORKDIR /home/anaconda
# 2023-10-27 14:37:39 0.00B 指定运行容器时使用的用户
USER 1000
# 2023-10-27 14:37:39 338.79KB 执行命令并创建新的镜像层
RUN |15 ANACONDA_CONTAINER=v23.3.1 ANACONDA_DIST=Miniconda3 ANACONDA_PYTHON=py310 ANACONDA_CONDA=23.3.1 ANACONDA_OS=Linux ANACONDA_ARCH=x86_64 ANACONDA_FLAVOR=Miniforge3 ANACONDA_PATCH=1 ANACONDA_VERSION=23.3.1-1 ANACONDA_INSTALLER=Miniforge3-23.3.1-1-Linux-x86_64.sh ANACONDA_ENV=base ANACONDA_GID=100 ANACONDA_PATH=/usr/local/anaconda3 ANACONDA_UID=1000 ANACONDA_USER=anaconda /bin/bash -o pipefail -c echo "auth requisite pam_deny.so" >> /etc/pam.d/su && sed -i.bak -e 's/^%admin/#%admin/' /etc/sudoers && sed -i.bak -e 's/^%sudo/#%sudo/' /etc/sudoers && useradd -m -s /bin/bash -N -u ${ANACONDA_UID} ${ANACONDA_USER} && mkdir -p ${ANACONDA_PATH} && chown -R ${ANACONDA_USER}:${ANACONDA_GID} ${ANACONDA_PATH} && chmod g+w /etc/passwd && chmod a+rx /usr/local/bin/fix-permissions && fix-permissions ${HOME} && fix-permissions ${ANACONDA_PATH} # buildkit
# 2023-10-27 14:37:39 1.07KB 复制新文件或目录到容器中
COPY scripts/fix-permissions /usr/local/bin/fix-permissions # buildkit
# 2023-10-27 14:37:39 3.77KB 执行命令并创建新的镜像层
RUN |15 ANACONDA_CONTAINER=v23.3.1 ANACONDA_DIST=Miniconda3 ANACONDA_PYTHON=py310 ANACONDA_CONDA=23.3.1 ANACONDA_OS=Linux ANACONDA_ARCH=x86_64 ANACONDA_FLAVOR=Miniforge3 ANACONDA_PATCH=1 ANACONDA_VERSION=23.3.1-1 ANACONDA_INSTALLER=Miniforge3-23.3.1-1-Linux-x86_64.sh ANACONDA_ENV=base ANACONDA_GID=100 ANACONDA_PATH=/usr/local/anaconda3 ANACONDA_UID=1000 ANACONDA_USER=anaconda /bin/bash -o pipefail -c sed -i 's/^#force_color_prompt=yes/force_color_prompt=yes/' /etc/skel/.bashrc # buildkit
# 2023-10-27 14:37:38 0.00B 设置环境变量 PATH
ENV PATH=/usr/local/anaconda3/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
# 2023-10-27 14:37:38 0.00B 设置环境变量 ANACONDA_ENV ANACONDA_PATH ANACONDA_GID ANACONDA_UID ANACONDA_USER HOME LANG LANGUAGE LC_ALL SHELL
ENV ANACONDA_ENV=base ANACONDA_PATH=/usr/local/anaconda3 ANACONDA_GID=100 ANACONDA_UID=1000 ANACONDA_USER=anaconda HOME=/home/anaconda LANG=en_US.UTF-8 LANGUAGE=en_US.UTF-8 LC_ALL=en_US.UTF-8 SHELL=/bin/bash
# 2023-10-27 14:37:38 3.05MB 执行命令并创建新的镜像层
RUN |15 ANACONDA_CONTAINER=v23.3.1 ANACONDA_DIST=Miniconda3 ANACONDA_PYTHON=py310 ANACONDA_CONDA=23.3.1 ANACONDA_OS=Linux ANACONDA_ARCH=x86_64 ANACONDA_FLAVOR=Miniforge3 ANACONDA_PATCH=1 ANACONDA_VERSION=23.3.1-1 ANACONDA_INSTALLER=Miniforge3-23.3.1-1-Linux-x86_64.sh ANACONDA_ENV=base ANACONDA_GID=100 ANACONDA_PATH=/usr/local/anaconda3 ANACONDA_UID=1000 ANACONDA_USER=anaconda /bin/bash -o pipefail -c echo "en_US.UTF-8 UTF-8" > /etc/locale.gen && locale-gen # buildkit
# 2023-10-27 14:37:36 23.12MB 执行命令并创建新的镜像层
RUN |15 ANACONDA_CONTAINER=v23.3.1 ANACONDA_DIST=Miniconda3 ANACONDA_PYTHON=py310 ANACONDA_CONDA=23.3.1 ANACONDA_OS=Linux ANACONDA_ARCH=x86_64 ANACONDA_FLAVOR=Miniforge3 ANACONDA_PATCH=1 ANACONDA_VERSION=23.3.1-1 ANACONDA_INSTALLER=Miniforge3-23.3.1-1-Linux-x86_64.sh ANACONDA_ENV=base ANACONDA_GID=100 ANACONDA_PATH=/usr/local/anaconda3 ANACONDA_UID=1000 ANACONDA_USER=anaconda /bin/bash -o pipefail -c apt-get install -y --no-install-recommends bzip2 ca-certificates curl locales sudo wget # buildkit
# 2023-10-27 14:37:32 46.07MB 执行命令并创建新的镜像层
RUN |15 ANACONDA_CONTAINER=v23.3.1 ANACONDA_DIST=Miniconda3 ANACONDA_PYTHON=py310 ANACONDA_CONDA=23.3.1 ANACONDA_OS=Linux ANACONDA_ARCH=x86_64 ANACONDA_FLAVOR=Miniforge3 ANACONDA_PATCH=1 ANACONDA_VERSION=23.3.1-1 ANACONDA_INSTALLER=Miniforge3-23.3.1-1-Linux-x86_64.sh ANACONDA_ENV=base ANACONDA_GID=100 ANACONDA_PATH=/usr/local/anaconda3 ANACONDA_UID=1000 ANACONDA_USER=anaconda /bin/bash -o pipefail -c apt-get update --fix-missing # buildkit
# 2023-10-27 14:37:32 0.00B 设置环境变量 NVIDIA_DRIVER_CAPABILITIES
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
# 2023-10-27 14:37:32 0.00B 设置环境变量 NVIDIA_VISIBLE_DEVICES
ENV NVIDIA_VISIBLE_DEVICES=all
# 2023-10-27 14:37:32 0.00B 设置环境变量 DEBIAN_FRONTEND
ENV DEBIAN_FRONTEND=noninteractive
# 2023-10-27 14:37:32 0.00B 指定运行容器时使用的用户
USER root
# 2023-10-27 14:37:32 0.00B
SHELL [/bin/bash -o pipefail -c]
# 2023-10-27 14:37:32 0.00B 定义构建参数
ARG ANACONDA_USER=anaconda
# 2023-10-27 14:37:32 0.00B 定义构建参数
ARG ANACONDA_UID=1000
# 2023-10-27 14:37:32 0.00B 定义构建参数
ARG ANACONDA_PATH=/usr/local/anaconda3
# 2023-10-27 14:37:32 0.00B 定义构建参数
ARG ANACONDA_GID=100
# 2023-10-27 14:37:32 0.00B 定义构建参数
ARG ANACONDA_ENV=base
# 2023-10-27 14:37:32 0.00B 定义构建参数
ARG ANACONDA_INSTALLER=Miniforge3-23.3.1-1-Linux-x86_64.sh
# 2023-10-27 14:37:32 0.00B 定义构建参数
ARG ANACONDA_VERSION=23.3.1-1
# 2023-10-27 14:37:32 0.00B 定义构建参数
ARG ANACONDA_PATCH=1
# 2023-10-27 14:37:32 0.00B 定义构建参数
ARG ANACONDA_FLAVOR=Miniforge3
# 2023-10-27 14:37:32 0.00B 定义构建参数
ARG ANACONDA_ARCH=x86_64
# 2023-10-27 14:37:32 0.00B 定义构建参数
ARG ANACONDA_OS=Linux
# 2023-10-27 14:37:32 0.00B 定义构建参数
ARG ANACONDA_CONDA=23.3.1
# 2023-10-27 14:37:32 0.00B 定义构建参数
ARG ANACONDA_PYTHON=py310
# 2023-10-27 14:37:32 0.00B 定义构建参数
ARG ANACONDA_DIST=Miniconda3
# 2023-10-27 14:37:32 0.00B 定义构建参数
ARG ANACONDA_CONTAINER=v23.3.1
# 2023-10-27 14:37:32 0.00B 添加元数据标签
LABEL description=Anaconda3 GPU Container
# 2023-06-21 08:24:58 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
# 2023-06-21 08:24:58 0.00B 添加元数据标签
LABEL com.nvidia.cudnn.version=8.9.0.131
# 2023-06-21 08:24:58 0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
# 2023-06-21 08:24:58 0.00B 定义构建参数
ARG TARGETARCH
# 2023-06-21 08:24:58 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
# 2023-06-21 08:24:58 0.00B 设置环境变量 NV_CUDNN_PACKAGE
ENV NV_CUDNN_PACKAGE=libcudnn8=8.9.0.131-1+cuda12.1
# 2023-06-21 08:24:58 0.00B 设置环境变量 NV_CUDNN_PACKAGE_NAME
ENV NV_CUDNN_PACKAGE_NAME=libcudnn8
# 2023-06-21 08:24:58 0.00B 设置环境变量 NV_CUDNN_VERSION
ENV NV_CUDNN_VERSION=8.9.0.131
# 2023-06-21 08:00:20 0.00B 设置环境变量 LIBRARY_PATH
ENV LIBRARY_PATH=/usr/local/cuda/lib64/stubs
# 2023-06-21 08:00:20 385.79KB 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} ${NV_LIBNCCL_DEV_PACKAGE_NAME} # buildkit
# 2023-06-21 08:00:19 4.79GB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends cuda-cudart-dev-12-1=${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
# 2023-06-21 08:00:19 0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
# 2023-06-21 08:00:19 0.00B 定义构建参数
ARG TARGETARCH
# 2023-06-21 08:00:19 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
# 2023-06-21 08:00:19 0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.17.1-1
# 2023-06-21 08:00:19 0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE_VERSION
ENV NV_LIBNCCL_DEV_PACKAGE_VERSION=2.17.1-1
# 2023-06-21 08:00:19 0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE_NAME
ENV NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev
# 2023-06-21 08:00:19 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
# 2023-06-21 08:00:19 0.00B 设置环境变量 NV_NVPROF_VERSION
ENV NV_NVPROF_VERSION=12.1.105-1
# 2023-06-21 08:00:19 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
# 2023-06-21 08:00:19 0.00B 设置环境变量 NV_CUDA_NSIGHT_COMPUTE_VERSION
ENV NV_CUDA_NSIGHT_COMPUTE_VERSION=12.1.1-1
# 2023-06-21 08:00:19 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
# 2023-06-21 08:00:19 0.00B 设置环境变量 NV_LIBCUBLAS_DEV_PACKAGE_NAME
ENV NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-12-1
# 2023-06-21 08:00:19 0.00B 设置环境变量 NV_LIBCUBLAS_DEV_VERSION
ENV NV_LIBCUBLAS_DEV_VERSION=12.1.3.1-1
# 2023-06-21 08:00:19 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
# 2023-06-21 08:00:19 0.00B 设置环境变量 NV_LIBNPP_DEV_VERSION
ENV NV_LIBNPP_DEV_VERSION=12.1.0.40-1
# 2023-06-21 08:00:19 0.00B 设置环境变量 NV_LIBCUSPARSE_DEV_VERSION
ENV NV_LIBCUSPARSE_DEV_VERSION=12.1.0.106-1
# 2023-06-21 08:00:19 0.00B 设置环境变量 NV_NVML_DEV_VERSION
ENV NV_NVML_DEV_VERSION=12.1.105-1
# 2023-06-21 08:00:19 0.00B 设置环境变量 NV_CUDA_CUDART_DEV_VERSION
ENV NV_CUDA_CUDART_DEV_VERSION=12.1.105-1
# 2023-06-21 08:00:19 0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=12.1.1-1
# 2023-06-21 07:48:37 0.00B 配置容器启动时运行的命令
ENTRYPOINT ["/opt/nvidia/nvidia_entrypoint.sh"]
# 2023-06-21 07:48:37 0.00B 设置环境变量 NVIDIA_PRODUCT_NAME
ENV NVIDIA_PRODUCT_NAME=CUDA
# 2023-06-21 07:48:37 2.53KB 复制新文件或目录到容器中
COPY nvidia_entrypoint.sh /opt/nvidia/ # buildkit
# 2023-06-21 07:48:37 3.06KB 复制新文件或目录到容器中
COPY entrypoint.d/ /opt/nvidia/entrypoint.d/ # buildkit
# 2023-06-21 07:48:37 261.37KB 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} ${NV_LIBNCCL_PACKAGE_NAME} # buildkit
# 2023-06-21 07:48:36 2.01GB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends cuda-libraries-12-1=${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
# 2023-06-21 07:48:36 0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
# 2023-06-21 07:48:36 0.00B 定义构建参数
ARG TARGETARCH
# 2023-06-21 07:48:36 0.00B 设置环境变量 NV_LIBNCCL_PACKAGE
ENV NV_LIBNCCL_PACKAGE=libnccl2=2.17.1-1+cuda12.1
# 2023-06-21 07:48:36 0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.17.1-1
# 2023-06-21 07:48:36 0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_VERSION
ENV NV_LIBNCCL_PACKAGE_VERSION=2.17.1-1
# 2023-06-21 07:48:36 0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_NAME
ENV NV_LIBNCCL_PACKAGE_NAME=libnccl2
# 2023-06-21 07:48:36 0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE
ENV NV_LIBCUBLAS_PACKAGE=libcublas-12-1=12.1.3.1-1
# 2023-06-21 07:48:36 0.00B 设置环境变量 NV_LIBCUBLAS_VERSION
ENV NV_LIBCUBLAS_VERSION=12.1.3.1-1
# 2023-06-21 07:48:36 0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE_NAME
ENV NV_LIBCUBLAS_PACKAGE_NAME=libcublas-12-1
# 2023-06-21 07:48:36 0.00B 设置环境变量 NV_LIBCUSPARSE_VERSION
ENV NV_LIBCUSPARSE_VERSION=12.1.0.106-1
# 2023-06-21 07:48:36 0.00B 设置环境变量 NV_LIBNPP_PACKAGE
ENV NV_LIBNPP_PACKAGE=libnpp-12-1=12.1.0.40-1
# 2023-06-21 07:48:36 0.00B 设置环境变量 NV_LIBNPP_VERSION
ENV NV_LIBNPP_VERSION=12.1.0.40-1
# 2023-06-21 07:48:36 0.00B 设置环境变量 NV_NVTX_VERSION
ENV NV_NVTX_VERSION=12.1.105-1
# 2023-06-21 07:48:36 0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=12.1.1-1
# 2023-06-21 07:43:10 0.00B 设置环境变量 NVIDIA_DRIVER_CAPABILITIES
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
# 2023-06-21 07:43:10 0.00B 设置环境变量 NVIDIA_VISIBLE_DEVICES
ENV NVIDIA_VISIBLE_DEVICES=all
# 2023-06-21 07:43:10 17.29KB 复制新文件或目录到容器中
COPY NGC-DL-CONTAINER-LICENSE / # buildkit
# 2023-06-21 07:43:09 0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64
# 2023-06-21 07:43:09 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
# 2023-06-21 07:43:09 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
# 2023-06-21 07:43:09 149.59MB 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} ${NV_CUDA_COMPAT_PACKAGE} && rm -rf /var/lib/apt/lists/* # buildkit
# 2023-06-21 07:42:55 0.00B 设置环境变量 CUDA_VERSION
ENV CUDA_VERSION=12.1.1
# 2023-06-21 07:42:55 10.56MB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends gnupg2 curl ca-certificates && curl -fsSLO https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/${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
# 2023-06-21 07:42:55 0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
# 2023-06-21 07:42:55 0.00B 定义构建参数
ARG TARGETARCH
# 2023-06-21 07:42:55 0.00B 设置环境变量 NV_CUDA_COMPAT_PACKAGE
ENV NV_CUDA_COMPAT_PACKAGE=cuda-compat-12-1
# 2023-06-21 07:42:55 0.00B 设置环境变量 NV_CUDA_CUDART_VERSION
ENV NV_CUDA_CUDART_VERSION=12.1.105-1
# 2023-06-21 07:42:55 0.00B 设置环境变量 NVIDIA_REQUIRE_CUDA brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand
ENV NVIDIA_REQUIRE_CUDA=cuda>=12.1 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 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
# 2023-06-21 07:42:55 0.00B 设置环境变量 NVARCH
ENV NVARCH=x86_64
# 2023-06-06 01:00:39 0.00B
/bin/sh -c #(nop) CMD ["/bin/bash"]
# 2023-06-06 01:00:39 77.81MB
/bin/sh -c #(nop) ADD file:0ad2ee2cfb186802f49c9bf4148674d1c6fc201f83478ec01ffaa7086d491323 in /
# 2023-06-06 01:00:37 0.00B
/bin/sh -c #(nop) LABEL org.opencontainers.image.version=22.04
# 2023-06-06 01:00:37 0.00B
/bin/sh -c #(nop) LABEL org.opencontainers.image.ref.name=ubuntu
# 2023-06-06 01:00:37 0.00B
/bin/sh -c #(nop) ARG LAUNCHPAD_BUILD_ARCH
# 2023-06-06 01:00:37 0.00B
/bin/sh -c #(nop) ARG RELEASE
镜像信息
{
"Id": "sha256:37b430162e0421b8a50bb4f3ed4423b346caa9a3111d377a99e782686e5a2b35",
"RepoTags": [
"dolfly/ffmpeg-nvidia:v5.0.2-jupyter",
"swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/dolfly/ffmpeg-nvidia:v5.0.2-jupyter"
],
"RepoDigests": [
"dolfly/ffmpeg-nvidia@sha256:7c776ce0b714733d685885884b78e9c4c6d64f30fdde13731693588cc9c1bfc1",
"swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/dolfly/ffmpeg-nvidia@sha256:042fd7a351d95dcd4c8d2c807c1411bbaecc1cb8a7eeebcfd972174961c9b3a2"
],
"Parent": "",
"Comment": "buildkit.dockerfile.v0",
"Created": "2023-10-27T11:58:13.598404249Z",
"Container": "",
"ContainerConfig": null,
"DockerVersion": "",
"Author": "",
"Config": {
"Hostname": "",
"Domainname": "",
"User": "1000",
"AttachStdin": false,
"AttachStdout": false,
"AttachStderr": false,
"ExposedPorts": {
"8888/tcp": {}
},
"Tty": false,
"OpenStdin": false,
"StdinOnce": false,
"Env": [
"PATH=/usr/local/anaconda3/bin:/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=12.1 brand=tesla,driver\u003e=450,driver\u003c451 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=510,driver\u003c511 brand=unknown,driver\u003e=510,driver\u003c511 brand=nvidia,driver\u003e=510,driver\u003c511 brand=nvidiartx,driver\u003e=510,driver\u003c511 brand=geforce,driver\u003e=510,driver\u003c511 brand=geforcertx,driver\u003e=510,driver\u003c511 brand=quadro,driver\u003e=510,driver\u003c511 brand=quadrortx,driver\u003e=510,driver\u003c511 brand=titan,driver\u003e=510,driver\u003c511 brand=titanrtx,driver\u003e=510,driver\u003c511 brand=tesla,driver\u003e=515,driver\u003c516 brand=unknown,driver\u003e=515,driver\u003c516 brand=nvidia,driver\u003e=515,driver\u003c516 brand=nvidiartx,driver\u003e=515,driver\u003c516 brand=geforce,driver\u003e=515,driver\u003c516 brand=geforcertx,driver\u003e=515,driver\u003c516 brand=quadro,driver\u003e=515,driver\u003c516 brand=quadrortx,driver\u003e=515,driver\u003c516 brand=titan,driver\u003e=515,driver\u003c516 brand=titanrtx,driver\u003e=515,driver\u003c516 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",
"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",
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