镜像构建历史
# 2025-02-07 16:34:36 0.00B 配置容器启动时运行的命令
ENTRYPOINT ["/opt/DeepPrep/deepprep/deepprep.sh"]
# 2025-02-07 16:34:36 0.00B 声明容器运行时监听的端口
EXPOSE map[8501/tcp:{}]
# 2025-02-07 16:34:36 90.24MB 执行命令并创建新的镜像层
RUN /bin/sh -c find $HOME -type d -exec chmod go=u {} + && find $HOME -type f -exec chmod go=u {} + # buildkit
# 2025-02-07 16:34:33 22.65KB 执行命令并创建新的镜像层
RUN /bin/sh -c chmod 755 /opt/DeepPrep/deepprep/web/pages/*.sh && chmod 755 /opt/DeepPrep/deepprep/rest/denoise/bin/*.py # buildkit
# 2025-02-07 16:34:32 270.42KB 执行命令并创建新的镜像层
RUN /bin/sh -c chmod 755 /opt/DeepPrep/deepprep/deepprep.sh && chmod 755 /opt/DeepPrep/deepprep/nextflow/bin/*.py # buildkit
# 2025-02-07 16:34:32 0.00B 设置环境变量 DEEPPREP_VERSION
ENV DEEPPREP_VERSION=25.1.0
# 2025-02-07 16:34:32 7.23KB 复制新文件或目录到容器中
COPY deepprep/deepprep.sh /opt/DeepPrep/deepprep/deepprep.sh # buildkit
# 2025-02-07 16:34:32 302.34KB 复制新文件或目录到容器中
COPY deepprep/rest/denoise /opt/DeepPrep/deepprep/rest/denoise # buildkit
# 2025-02-07 16:34:31 15.21KB 复制新文件或目录到容器中
COPY deepprep/qc /opt/DeepPrep/deepprep/qc # buildkit
# 2025-02-07 16:34:31 68.62KB 复制新文件或目录到容器中
COPY deepprep/web /opt/DeepPrep/deepprep/web # buildkit
# 2025-02-07 16:34:31 41.67MB 复制新文件或目录到容器中
COPY deepprep/nextflow /opt/DeepPrep/deepprep/nextflow # buildkit
# 2025-01-08 15:39:18 80.12KB 复制新文件或目录到容器中
COPY deepprep/SynthMorph /opt/DeepPrep/deepprep/SynthMorph # buildkit
# 2025-01-08 15:39:18 152.94MB 复制新文件或目录到容器中
COPY deepprep/FastSurfer /opt/DeepPrep/deepprep/FastSurfer # buildkit
# 2025-01-08 15:39:16 49.60MB 复制新文件或目录到容器中
COPY deepprep/SUGAR /opt/DeepPrep/deepprep/SUGAR # buildkit
# 2025-01-08 15:39:15 209.08KB 复制新文件或目录到容器中
COPY deepprep/FastCSR /opt/DeepPrep/deepprep/FastCSR # buildkit
# 2025-01-08 15:39:15 225.00B 复制新文件或目录到容器中
COPY deepprep/FreeSurfer /opt/freesurfer # buildkit
# 2025-01-08 15:39:15 3.61GB 复制新文件或目录到容器中
COPY deepprep/model/SynthMorph /opt/model/SynthMorph # buildkit
# 2025-01-08 15:38:46 1.15GB 复制新文件或目录到容器中
COPY deepprep/model/SUGAR /opt/model/SUGAR # buildkit
# 2025-01-08 15:38:36 864.02MB 复制新文件或目录到容器中
COPY deepprep/model/FastCSR /opt/model/FastCSR # buildkit
# 2025-01-08 15:38:29 39.48MB 执行命令并创建新的镜像层
RUN /bin/sh -c find $HOME/.cache/templateflow -type d -exec chmod go=u {} + && find $HOME/.cache/templateflow -type f -exec chmod go=u {} + # buildkit
# 2025-01-08 15:38:27 3.45MB 执行命令并创建新的镜像层
RUN /bin/sh -c python3 -c "import templateflow.api as tflow; tflow.get('MNI152NLin6Asym', resolution='02', suffix='dseg', atlas='HCP', raise_empty=True)" && python3 -c "import templateflow.api as tflow; tflow.get('fsaverage', density='41k', suffix='sphere', raise_empty=True)" && python3 -c "import templateflow.api as tflow; tflow.get('fsLR', density='32k', suffix='midthickness', raise_empty=True)" && python3 -c "import templateflow.api as tflow; tflow.get('fsLR', density='32k', suffix='dparc', desc='nomedialwall', raise_empty=True)" # buildkit
# 2025-01-08 15:37:55 16.39MB 执行命令并创建新的镜像层
RUN /bin/sh -c python3 -c "from neuromaps.datasets import fetch_fsaverage; fetch_fsaverage(density='41k')" && python3 -c "from neuromaps.datasets import fetch_fslr; fetch_fslr(density='32k')" # buildkit
# 2025-01-08 15:37:42 36.03MB 执行命令并创建新的镜像层
RUN /bin/sh -c python3 -c "import templateflow.api as tflow; tflow.get('MNI152NLin6Asym', desc=None, resolution=1, suffix='T1w', extension='nii.gz')" && python3 -c "import templateflow.api as tflow; tflow.get('MNI152NLin6Asym', desc=None, resolution=2, suffix='T1w', extension='nii.gz')" && python3 -c "import templateflow.api as tflow; tflow.get('MNI152NLin2009cAsym', desc=None, resolution=1, suffix='T1w', extension='nii.gz')" && python3 -c "import templateflow.api as tflow; tflow.get('MNI152NLin2009cAsym', desc=None, resolution=2, suffix='T1w', extension='nii.gz')" && python3 -c "import templateflow.api as tflow; tflow.get('MNI152NLin2009cAsym', desc='brain', resolution=2, suffix='mask', extension='nii.gz')" && python3 -c "import templateflow.api as tflow; tflow.get('MNI152NLin2009cAsym', desc='fMRIPrep', resolution=2, suffix='boldref', extension='nii.gz')" && python3 -c "import templateflow.api as tflow; tflow.get('MNI152NLin2009cAsym', label='brain', resolution=1, suffix='probseg', extension='nii.gz')" # buildkit
# 2025-01-08 15:37:00 0.00B 设置环境变量 PATH CPATH LD_LIBRARY_PATH
ENV PATH=/opt/conda/envs/deepprep/bin:/opt/nextflow/bin:/opt/abin:/opt/ANTs/bin:/opt/workbench/bin_linux64:/opt/fsl/bin:/opt/freesurfer/tktools:/opt/freesurfer/bin:/opt/freesurfer/fsfast/bin:/opt/freesurfer/mni/bin:/opt/node-v20.18.1-linux-x64/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin CPATH=/opt/conda/envs/deepprep/include: LD_LIBRARY_PATH=/opt/conda/envs/deepprep/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64:/usr/lib/jvm/java-11-openjdk-amd64/lib:/usr/lib/jvm/java-11-openjdk-amd64/lib/server
# 2025-01-08 15:37:00 6.30KB 执行命令并创建新的镜像层
RUN /bin/sh -c micromamba shell init -s bash && echo "micromamba activate deepprep" >> $HOME/.bashrc # buildkit
# 2025-01-08 15:37:00 0.00B 设置环境变量 MAMBA_ROOT_PREFIX
ENV MAMBA_ROOT_PREFIX=/opt/conda
# 2025-01-08 15:37:00 9.60GB 复制新文件或目录到容器中
COPY /opt/conda/envs/deepprep /opt/conda/envs/deepprep # buildkit
# 2025-01-08 15:35:36 15.73MB 复制新文件或目录到容器中
COPY /bin/micromamba /bin/micromamba # buildkit
# 2025-01-08 15:35:36 0.00B 设置环境变量 PATH NXF_OFFLINE
ENV PATH=/opt/nextflow/bin:/opt/abin:/opt/ANTs/bin:/opt/workbench/bin_linux64:/opt/fsl/bin:/opt/freesurfer/tktools:/opt/freesurfer/bin:/opt/freesurfer/fsfast/bin:/opt/freesurfer/mni/bin:/opt/node-v20.18.1-linux-x64/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin NXF_OFFLINE=true
# 2025-01-08 15:35:36 34.36MB 执行命令并创建新的镜像层
RUN /bin/sh -c find $HOME/.nextflow -type d -exec chmod go=u {} + && find $HOME/.nextflow -type f -exec chmod go=u {} + # buildkit
# 2025-01-08 15:35:36 34.36MB 执行命令并创建新的镜像层
RUN /bin/sh -c /opt/nextflow/bin/nextflow # buildkit
# 2025-01-08 15:35:30 17.64KB 复制新文件或目录到容器中
COPY /opt/nextflow /opt/nextflow # buildkit
# 2025-01-08 15:35:29 0.00B 设置环境变量 HOME
ENV HOME=/home/deepprep
# 2025-01-08 15:35:29 0.00B 设置工作目录为/home/deepprep
WORKDIR /home/deepprep
# 2025-01-08 15:35:29 333.98KB 执行命令并创建新的镜像层
RUN /bin/sh -c useradd -m -s /bin/bash -G users deepprep # buildkit
# 2025-01-08 15:35:29 0.00B 设置环境变量 PATH
ENV PATH=/opt/abin:/opt/ANTs/bin:/opt/workbench/bin_linux64:/opt/fsl/bin:/opt/freesurfer/tktools:/opt/freesurfer/bin:/opt/freesurfer/fsfast/bin:/opt/freesurfer/mni/bin:/opt/node-v20.18.1-linux-x64/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
# 2025-01-08 15:35:29 2.69MB 执行命令并创建新的镜像层
RUN /bin/sh -c apt-get update && apt-get install -y --no-install-recommends libxpm-dev libpng12-0 libxp6 libxft2 && apt-get clean && rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/* # buildkit
# 2025-01-08 15:34:39 21.42MB 复制新文件或目录到容器中
COPY /opt/abin /opt/abin # buildkit
# 2025-01-08 15:34:38 0.00B 设置环境变量 PATH
ENV PATH=/opt/ANTs/bin:/opt/workbench/bin_linux64:/opt/fsl/bin:/opt/freesurfer/tktools:/opt/freesurfer/bin:/opt/freesurfer/fsfast/bin:/opt/freesurfer/mni/bin:/opt/node-v20.18.1-linux-x64/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
# 2025-01-08 15:34:38 0.00B 设置环境变量 ANTS_RANDOM_SEED
ENV ANTS_RANDOM_SEED=14193
# 2025-01-08 15:34:38 0.00B 设置环境变量 ANTSPATH
ENV ANTSPATH=/opt/ANTs/bin
# 2025-01-08 15:34:38 2.30GB 复制新文件或目录到容器中
COPY /opt/ANTs /opt/ANTs # buildkit
# 2025-01-08 15:34:15 0.00B 设置环境变量 PATH
ENV PATH=/opt/workbench/bin_linux64:/opt/fsl/bin:/opt/freesurfer/tktools:/opt/freesurfer/bin:/opt/freesurfer/fsfast/bin:/opt/freesurfer/mni/bin:/opt/node-v20.18.1-linux-x64/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
# 2025-01-08 15:34:15 273.49MB 复制新文件或目录到容器中
COPY /opt/workbench /opt/workbench # buildkit
# 2025-01-08 15:34:11 0.00B 设置环境变量 PATH
ENV PATH=/opt/fsl/bin:/opt/freesurfer/tktools:/opt/freesurfer/bin:/opt/freesurfer/fsfast/bin:/opt/freesurfer/mni/bin:/opt/node-v20.18.1-linux-x64/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
# 2025-01-08 15:34:11 0.00B 设置环境变量 FSLDISPLAY PYTHONNOUSERSITE FSL_DIR FSL_BIN FSLCONVERT FSLOUTPUTTYPE FSLMULTIFILEQUIT FSLLOCKDIR FSLMACHINELIST FSLREMOTECALL FSLGECUDAQ
ENV FSLDISPLAY=/usr/bin/display PYTHONNOUSERSITE=1 FSL_DIR=/opt/fsl FSL_BIN=/opt/fsl/bin FSLCONVERT=/usr/bin/convert FSLOUTPUTTYPE=NIFTI_GZ FSLMULTIFILEQUIT=TRUE FSLLOCKDIR= FSLMACHINELIST= FSLREMOTECALL= FSLGECUDAQ=cuda.q
# 2025-01-08 15:34:11 0.00B 设置环境变量 FSLDIR
ENV FSLDIR=/opt/fsl
# 2025-01-08 15:34:11 112.42MB 执行命令并创建新的镜像层
RUN /bin/sh -c apt-get update && apt-get install -y --no-install-recommends libopenblas-dev && apt-get clean && rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/* # buildkit
# 2025-01-08 15:33:12 1.27GB 复制新文件或目录到容器中
COPY /opt/fsl /opt/fsl # buildkit
# 2025-01-08 15:32:59 0.00B 设置环境变量 PATH
ENV PATH=/opt/freesurfer/tktools:/opt/freesurfer/bin:/opt/freesurfer/fsfast/bin:/opt/freesurfer/mni/bin:/opt/node-v20.18.1-linux-x64/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
# 2025-01-08 15:32:59 0.00B 设置环境变量 PERL5LIB MNI_PERL5LIB
ENV PERL5LIB=/opt/freesurfer/mni/share/perl5 MNI_PERL5LIB=/opt/freesurfer/mni/share/perl5
# 2025-01-08 15:32:59 0.00B 设置环境变量 SUBJECTS_DIR FUNCTIONALS_DIR MNI_DIR LOCAL_DIR FSFAST_HOME FMRI_ANALYSIS_DIR MINC_BIN_DIR MINC_LIB_DIR MNI_DATAPATH
ENV SUBJECTS_DIR=/opt/freesurfer/subjects FUNCTIONALS_DIR=/opt/freesurfer/sessions MNI_DIR=/opt/freesurfer/mni LOCAL_DIR=/opt/freesurfer/local FSFAST_HOME=/opt/freesurfer/fsfast FMRI_ANALYSIS_DIR=/opt/freesurfer/fsfast MINC_BIN_DIR=/opt/freesurfer/mni/bin MINC_LIB_DIR=/opt/freesurfer/mni/lib MNI_DATAPATH=/opt/freesurfer/mni/data
# 2025-01-08 15:32:59 0.00B 设置环境变量 OS FS_OVERRIDE FIX_VERTEX_AREA FSF_OUTPUT_FORMAT FREESURFER
ENV OS=Linux FS_OVERRIDE=0 FIX_VERTEX_AREA= FSF_OUTPUT_FORMAT=nii.gz FREESURFER=/opt/freesurfer
# 2025-01-08 15:32:59 0.00B 设置环境变量 FREESURFER_HOME
ENV FREESURFER_HOME=/opt/freesurfer
# 2025-01-08 15:32:59 18.33MB 执行命令并创建新的镜像层
RUN /bin/sh -c apt-get update && apt-get install -y --no-install-recommends bc binutils libgomp1 perl psmisc tcsh libpng12-0 libglu1-mesa && apt-get clean && rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/* # buildkit
# 2025-01-08 15:32:01 3.64GB 复制新文件或目录到容器中
COPY /opt/freesurfer /opt/freesurfer # buildkit
# 2025-01-08 15:30:45 235.18MB 执行命令并创建新的镜像层
RUN /bin/sh -c curl "https://awscli.amazonaws.com/awscli-exe-linux-x86_64.zip" -o "awscliv2.zip" && unzip awscliv2.zip && ./aws/install && rm -rf aws awscliv2.zip # buildkit
# 2025-01-08 15:30:35 2.48MB 执行命令并创建新的镜像层
RUN /bin/sh -c apt-get update && apt-get install -y --no-install-recommends unzip && apt-get clean && rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/* # buildkit
# 2025-01-08 15:29:50 612.28MB 执行命令并创建新的镜像层
RUN /bin/sh -c npm install -g svgo@^3.2.0 bids-validator@^1.14.0 && rm -r ~/.npm # buildkit
# 2025-01-08 15:28:24 161.38MB 执行命令并创建新的镜像层
RUN /bin/sh -c wget --content-disposition -P /opt/ https://nodejs.org/dist/v20.18.1/node-v20.18.1-linux-x64.tar.xz && tar -C /opt -xvf /opt/node-v20.18.1-linux-x64.tar.xz && rm /opt/node-v20.18.1-linux-x64.tar.xz # buildkit
# 2025-01-08 15:28:12 2.89MB 执行命令并创建新的镜像层
RUN /bin/sh -c apt-get update && apt-get install -y --no-install-recommends wget xz-utils && apt-get clean && rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/* # buildkit
# 2025-01-08 15:12:44 0.00B 设置环境变量 PATH
ENV PATH=/opt/node-v20.18.1-linux-x64/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
# 2025-01-08 15:12:44 0.00B 设置环境变量 UV_USE_IO_URING
ENV UV_USE_IO_URING=0
# 2025-01-08 15:12:44 171.57KB 执行命令并创建新的镜像层
RUN /bin/sh -c sed -i.bak '/^save / s/^/#/' /etc/redis/redis.conf # buildkit
# 2025-01-08 15:12:44 85.79KB 执行命令并创建新的镜像层
RUN /bin/sh -c sed -i '147c\supervised systemd' /etc/redis/redis.conf # buildkit
# 2025-01-08 15:12:43 0.00B 设置环境变量 LD_LIBRARY_PATH JAVA_HOME
ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64:/usr/lib/jvm/java-11-openjdk-amd64/lib:/usr/lib/jvm/java-11-openjdk-amd64/lib/server JAVA_HOME=/usr/lib/jvm/java-11-openjdk-amd64
# 2025-01-08 15:12:43 766.83MB 执行命令并创建新的镜像层
RUN /bin/sh -c apt-get update && apt-get install -y --no-install-recommends libmagickwand-dev libxmu6 redis-server openjdk-11-jdk && apt-get clean && rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/* # buildkit
# 2025-01-07 17:37:42 1.73KB 执行命令并创建新的镜像层
RUN /bin/sh -c curl -sL "https://keyserver.ubuntu.com/pks/lookup?op=get&search=0xEA8CACC073C3DB2A" | gpg --dearmor -o /usr/share/keyrings/linuxuprising.gpg && curl -sL "https://keyserver.ubuntu.com/pks/lookup?op=get&search=0xA1301338A3A48C4A" | gpg --dearmor -o /usr/share/keyrings/zeehio.gpg && echo "deb [signed-by=/usr/share/keyrings/linuxuprising.gpg] https://ppa.launchpadcontent.net/linuxuprising/libpng12/ubuntu jammy main" > /etc/apt/sources.list.d/linuxuprising.list && echo "deb [signed-by=/usr/share/keyrings/zeehio.gpg] https://ppa.launchpadcontent.net/zeehio/libxp/ubuntu jammy main" > /etc/apt/sources.list.d/zeehio.list # buildkit
# 2025-01-07 17:37:39 8.01MB 执行命令并创建新的镜像层
RUN /bin/sh -c apt-get update && apt-get install -y --no-install-recommends curl rsync tzdata && apt-get clean && rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/* # buildkit
# 2025-01-07 17:37:02 0.00B 设置环境变量 TZ
ENV TZ=Etc/UTC
# 2025-01-07 17:37:02 61.88MB 执行命令并创建新的镜像层
RUN /bin/sh -c apt-get update && apt-get upgrade -y && apt-get clean && rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/* # buildkit
# 2025-01-07 17:37:02 0.00B 设置环境变量 DEBIAN_FRONTEND LANG LC_ALL
ENV DEBIAN_FRONTEND=noninteractive LANG=C.UTF-8 LC_ALL=C.UTF-8
# 2023-11-10 15:09:27 1.09GB 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} && apt-mark hold ${NV_CUDNN_PACKAGE_NAME} && rm -rf /var/lib/apt/lists/* # buildkit
# 2023-11-10 15:09:27 0.00B 添加元数据标签
LABEL com.nvidia.cudnn.version=8.9.6.50
# 2023-11-10 15:09:27 0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
# 2023-11-10 15:09:27 0.00B 定义构建参数
ARG TARGETARCH
# 2023-11-10 15:09:27 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 15:09:27 0.00B 设置环境变量 NV_CUDNN_PACKAGE_NAME
ENV NV_CUDNN_PACKAGE_NAME=libcudnn8
# 2023-11-10 15:09:27 0.00B 设置环境变量 NV_CUDNN_VERSION
ENV NV_CUDNN_VERSION=8.9.6.50
# 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": "sha256:98c3708335496938d0afbaa37c2e0d9c0468411397a0ff5434b96f941ce8e31a",
"RepoTags": [
"pbfslab/deepprep:25.1.0",
"swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pbfslab/deepprep:25.1.0"
],
"RepoDigests": [
"pbfslab/deepprep@sha256:8d35461da04b055c7a5cd005500dc1db8b00220379f5d266975e5a40e3e9bbff",
"swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/pbfslab/deepprep@sha256:8d35461da04b055c7a5cd005500dc1db8b00220379f5d266975e5a40e3e9bbff"
],
"Parent": "",
"Comment": "buildkit.dockerfile.v0",
"Created": "2025-02-07T16:34:36.826943019+08:00",
"Container": "",
"ContainerConfig": null,
"DockerVersion": "",
"Author": "",
"Config": {
"Hostname": "",
"Domainname": "",
"User": "",
"AttachStdin": false,
"AttachStdout": false,
"AttachStderr": false,
"ExposedPorts": {
"8501/tcp": {}
},
"Tty": false,
"OpenStdin": false,
"StdinOnce": false,
"Env": [
"PATH=/opt/conda/envs/deepprep/bin:/opt/nextflow/bin:/opt/abin:/opt/ANTs/bin:/opt/workbench/bin_linux64:/opt/fsl/bin:/opt/freesurfer/tktools:/opt/freesurfer/bin:/opt/freesurfer/fsfast/bin:/opt/freesurfer/mni/bin:/opt/node-v20.18.1-linux-x64/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=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=/opt/conda/envs/deepprep/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64:/usr/lib/jvm/java-11-openjdk-amd64/lib:/usr/lib/jvm/java-11-openjdk-amd64/lib/server",
"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_CUDNN_VERSION=8.9.6.50",
"NV_CUDNN_PACKAGE_NAME=libcudnn8",
"NV_CUDNN_PACKAGE=libcudnn8=8.9.6.50-1+cuda11.8",
"DEBIAN_FRONTEND=noninteractive",
"LANG=C.UTF-8",
"LC_ALL=C.UTF-8",
"TZ=Etc/UTC",
"JAVA_HOME=/usr/lib/jvm/java-11-openjdk-amd64",
"UV_USE_IO_URING=0",
"FREESURFER_HOME=/opt/freesurfer",
"OS=Linux",
"FS_OVERRIDE=0",
"FIX_VERTEX_AREA=",
"FSF_OUTPUT_FORMAT=nii.gz",
"FREESURFER=/opt/freesurfer",
"SUBJECTS_DIR=/opt/freesurfer/subjects",
"FUNCTIONALS_DIR=/opt/freesurfer/sessions",
"MNI_DIR=/opt/freesurfer/mni",
"LOCAL_DIR=/opt/freesurfer/local",
"FSFAST_HOME=/opt/freesurfer/fsfast",
"FMRI_ANALYSIS_DIR=/opt/freesurfer/fsfast",
"MINC_BIN_DIR=/opt/freesurfer/mni/bin",
"MINC_LIB_DIR=/opt/freesurfer/mni/lib",
"MNI_DATAPATH=/opt/freesurfer/mni/data",
"PERL5LIB=/opt/freesurfer/mni/share/perl5",
"MNI_PERL5LIB=/opt/freesurfer/mni/share/perl5",
"FSLDIR=/opt/fsl",
"FSLDISPLAY=/usr/bin/display",
"PYTHONNOUSERSITE=1",
"FSL_DIR=/opt/fsl",
"FSL_BIN=/opt/fsl/bin",
"FSLCONVERT=/usr/bin/convert",
"FSLOUTPUTTYPE=NIFTI_GZ",
"FSLMULTIFILEQUIT=TRUE",
"FSLLOCKDIR=",
"FSLMACHINELIST=",
"FSLREMOTECALL=",
"FSLGECUDAQ=cuda.q",
"ANTSPATH=/opt/ANTs/bin",
"ANTS_RANDOM_SEED=14193",
"HOME=/home/deepprep",
"NXF_OFFLINE=true",
"MAMBA_ROOT_PREFIX=/opt/conda",
"CPATH=/opt/conda/envs/deepprep/include:",
"DEEPPREP_VERSION=25.1.0"
],
"Cmd": null,
"Image": "",
"Volumes": null,
"WorkingDir": "/home/deepprep",
"Entrypoint": [
"/opt/DeepPrep/deepprep/deepprep.sh"
],
"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": 28963423858,
"GraphDriver": {
"Data": {
"LowerDir": "/var/lib/docker/overlay2/49a1400913d9895b0a589d62c67ce45920307b4965490ef783c0753079105a75/diff:/var/lib/docker/overlay2/b9747c4b536634c18b2817fad94407a55aa573368eaa4010547900784d0396d2/diff:/var/lib/docker/overlay2/b131c05c50a81ad3b29503aafb462a5cbb75d4501fdc96aa2fba941cda3a8e2c/diff:/var/lib/docker/overlay2/8a1bfd57f5334fdbd4c43cdc31354f2d7ee50222fe2e679552257b72547a85f9/diff:/var/lib/docker/overlay2/cfb5e296eb862ed06d579461390551df70655697e258d664758ee20688f152ab/diff:/var/lib/docker/overlay2/ae7572a45ad32670930047cfd6d4e788980d0f1762d3966da6daa0df1b0b4434/diff:/var/lib/docker/overlay2/a1ff38e8097d1fa52464fd4f8739ba64e85e6a2718748d153df319e76b140124/diff:/var/lib/docker/overlay2/10c978e650dee3528ebfc56c18a5a38329d848fe7e4f3bd464ce94fc9d1909f8/diff:/var/lib/docker/overlay2/a4330a1bbd3792d7cdaa26ed52eaed67d3b1e9ab477782686c651885c6118f57/diff:/var/lib/docker/overlay2/ec7c36a3f8a71d07d717b4489d599a6d7971e59e22a6b3540bddedbf86dd66eb/diff:/var/lib/docker/overlay2/64c79dd895945a285e5c2f3f11728934c343f39166129416bcf42d286164e331/diff:/var/lib/docker/overlay2/d7684f6d0540fd07a67fec037b01324fd33142c020093d0f1815a620ef297afd/diff:/var/lib/docker/overlay2/05eb0c8668c047332e804d2d10a2a97d47287cc8cd6da0da3cb22624ef164ae2/diff:/var/lib/docker/overlay2/6ff516ebeb0dfb94cad80ea2827e7173a550078419a6c84376f6339114dac099/diff:/var/lib/docker/overlay2/be773b2918ee53986315c16bb0de66592280cb7082ad67b913ef78ab5e898b05/diff:/var/lib/docker/overlay2/e470b78d4c8a7145885ec8d991f3108ca14a86bd55b8d4e107e9884a559481f9/diff:/var/lib/docker/overlay2/1587507e9e7a93cdf6e36da6f4be6825166132cc8f43690cdc0dae7981c4f1a0/diff:/var/lib/docker/overlay2/b2bfa45f6be97d3fc157753d8b6920182e8d0be4b58081dd30701d8c4b8e7f82/diff:/var/lib/docker/overlay2/ae0715742b15cdd97a96d5c5b2db5ce67341bdd8a29cbbfbb0f8e0c50a42d8db/diff:/var/lib/docker/overlay2/70c6c547158e34fc7cba1a7f9492665aac49dae65b8619c294cbf951f4cbda7c/diff:/var/lib/docker/overlay2/a73959d6dd15d119b780ed499d3008e9ccc0517b4cc3b1b8610cae0be01b9032/diff:/var/lib/docker/overlay2/ad2210d7448055cbb098f57b93df0667fcf2f6290e8b1a7db9ffe963240536d0/diff:/var/lib/docker/overlay2/9c14ada331a097ee1c2e6a25217147f1ce58e1b8ce1ecf8efd9009e3580f8a60/diff:/var/lib/docker/overlay2/723d9fc780c6a07088d509c479a3f467aa98d21a33459b733a6cefba62541125/diff:/var/lib/docker/overlay2/5400045d7258f8bb314b71df0bec54ac75bdf582c38f746712ff3916d74e2ab7/diff:/var/lib/docker/overlay2/e3f96acf1de0aa0cee71d3f0ec09ed6c7165f1bdd9a7e9708aaf23630e34f915/diff:/var/lib/docker/overlay2/abb4548a518b7386497bac4e48004b19df7f99b4ac0a3784a08e4c1edd8b50bb/diff:/var/lib/docker/overlay2/a55b7aca1afa42895ec25a2d8ca5531ea12d2fd44e4b00d16366c4eaa4547b47/diff:/var/lib/docker/overlay2/913a077ee2155f42b79bdebaa13f370cc1405fa24e75ce1a39d668e3977ad8ad/diff:/var/lib/docker/overlay2/cf1b943b523d0fddca40afcba7d9c65e0c9bb7b46eb91aa28131e5b1636b2287/diff:/var/lib/docker/overlay2/afb0d75b225f9b1e56907ce8c08a374122ef7406e667ca590299db04533dbb5c/diff:/var/lib/docker/overlay2/cd61d06d02bb277f94c84094567b832322804ce6ccf6e28dd88e68fda42fda80/diff:/var/lib/docker/overlay2/ded8d0dad7cfafdbd73a66f5d46be6d8959e1be0b271c1b70b39691542e0cbd5/diff:/var/lib/docker/overlay2/c1900430567923d39d2f5013c4256cbbabc11303420db97c62cfb963ad96ec82/diff:/var/lib/docker/overlay2/8881131cc2727740b862634c705ec209621bb8d8f04208affd135f7f81e7d545/diff:/var/lib/docker/overlay2/49376fed62e5e0fd8232d64b9ef71675d004963765aff6998812068c81e4d63d/diff:/var/lib/docker/overlay2/70dc42329a0da7ce963e99291e1b374d55961e397800059d01849c626c714832/diff:/var/lib/docker/overlay2/79c4556f5f23718333e2c608ffa68baea73671f4404faa0cd406b062a60102e2/diff:/var/lib/docker/overlay2/9578621afcce96bcb85d413abceb222c2944d0ba6951c5ba04d7d9043e835e08/diff:/var/lib/docker/overlay2/ad409e960ced10f8f281da49f111098fa171dfd726c5b9212288667dc4640f1f/diff:/var/lib/docker/overlay2/deb0c30e1bbec7f7298aea2f6e8d41063c63eb0829c2fb2dc796b7dcdec64b03/diff:/var/lib/docker/overlay2/03d2f23c2e821e860aa085de44adbfce19b05367727cfaaa0ded97e4816b039c/diff:/var/lib/docker/overlay2/6e76637e6afc38049faab2a7bcbf816de5a239b954e81e46890bcd3a2e5cee50/diff:/var/lib/docker/overlay2/836bbb3d57f4a09344d639a45e355ee068133ab31f5d2dc14f61f9c05d8b6533/diff:/var/lib/docker/overlay2/58d438c13b7d7dca9f2a46f4a77781b1bf14c1ef7841883ecf7450e6dbda07eb/diff:/var/lib/docker/overlay2/c7fe2370dff13aff7d1a078f4a46aa56d0839837a00c7dbc0652c75ed09c397a/diff:/var/lib/docker/overlay2/c743a5e0bf1d04831afb9c46fe1ac25be4da5fd06df9fb48cbb836bcf38483c1/diff:/var/lib/docker/overlay2/abbfe3608e9b44e2f1f4aa38a0a74beead3982f621d06481b9d12b5bf0ace162/diff:/var/lib/docker/overlay2/09f72fc9f7e139123f8bf360a9f7fd1e700ae6afce3cbdf312888491890c6471/diff:/var/lib/docker/overlay2/c0f41dfd234ab245ea4c7e2d0e9e1389b69b0b8d386ab82f934a6313674f1eed/diff:/var/lib/docker/overlay2/78e446dc1df7cbd4e21b5194bc781cef7cddd9e37d3ac6cb50016bb3b8f31d03/diff:/var/lib/docker/overlay2/b97035c32664dcef8cdf799505a784c5beb4144287350f4e8b02d92e5f7ec937/diff:/var/lib/docker/overlay2/45a6fa0fdaab92a42736cfcd30441caa58fc084598dafe00429b20c3283d9806/diff:/var/lib/docker/overlay2/27fe21c9386989b8b79e356e787ae3d1f71f1a4a9657d30061a91a22609a7c4c/diff:/var/lib/docker/overlay2/b49c601d2825b69830d562d394503f3ec8579a1f3a7799fc2a0bb58780503951/diff:/var/lib/docker/overlay2/f2905627b4505cda033dd62b5a5dc1676edda5a6e1bda7cd6e6e2048fcf5aee0/diff",
"MergedDir": "/var/lib/docker/overlay2/a648c15a243fa783eb1447e431c684358161b6af815be6fb89be22f32ccbcd20/merged",
"UpperDir": "/var/lib/docker/overlay2/a648c15a243fa783eb1447e431c684358161b6af815be6fb89be22f32ccbcd20/diff",
"WorkDir": "/var/lib/docker/overlay2/a648c15a243fa783eb1447e431c684358161b6af815be6fb89be22f32ccbcd20/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",
"sha256:04b6eafdd5ee6a825f7e3e6ca99cbc43d52da021b05cec4cae987dfd0f78e8a7",
"sha256:0ca4e81d8618cb3db36322acd7b1fc65ac68b6bcda240c7be453d75055e7c5e4",
"sha256:4518d8edaf898f7fd2ff5f68c2e2f66a09b3e0c8f883993888d10ff3cfcc1814",
"sha256:53a7a991c52fee4fad44010a2bf42fe1657bffa1846cb28da6e719fca6f9c56e",
"sha256:d3b0e570bd0ab61cf7b8cca19322e3b0c2605f9319d99a78dce63126607feeda",
"sha256:4f21fffb43a13e96593acf1fd67389d40e620a61239e913c369c0f860753e20f",
"sha256:6eaa685f5d6bc21a73e8f912b0686575cc2eee7803d6aaad5a470699c128fb15",
"sha256:b8e16d77fd58c1f8529e2e2f85f2bb933c6f6b8b2377ff9bcab2a9d4a0685cbf",
"sha256:f2505e437c03d754024e9d4a7c753b336336964f571c21a03dd936e29363b6ba",
"sha256:9be6e9ce1066b7ced0bfa9dfe0ceece3fc6a292e75d7a2ed79b20a00bc5087eb",
"sha256:f0be5a4d9b5da63445fe5a8e0621170c5a77b0c35a8f916d36f43dc4d648234a",
"sha256:bb3cadadacdd45a493c91e29b5f8f0fba96b5b414c823fba63c4c889bd1dac06",
"sha256:513e0a4fe916b8c6c42193c8f651f87a544733d47918465dad511c715a1a3999",
"sha256:b8aaed996ac25920aa449520f356469ca7a3b8d54dbfce4687886448e4699ecf",
"sha256:ab1a6ed49334d19a268db0454fd68e6bb92c7ad04445d5b43c13e378f663a4a2",
"sha256:dfe0b045196ad5bcf020898698eac342cea3d39847c964c9500830ce18a5e39f",
"sha256:f981636ac01a513074312daf33ea90e7246cb492d358c37d8b54ba0f0e93d354",
"sha256:2d17041df44526146a063b790e10236ef055304091b1ae4cb87819bbf290b696",
"sha256:dc24e8a6ff2ee5f92554d4a7268e7bf6e53c4f1e87a2088adb5d49d8f1d2c557",
"sha256:27aabc1995a517aceae7322efe464f92944706926a316e7e2a195c31465a5d1f",
"sha256:94fcccb3c2c4a5b4328546158ddd4a4d995f1933aefc6aaf3bd46682c0bd44dc",
"sha256:5f70bf18a086007016e948b04aed3b82103a36bea41755b6cddfaf10ace3c6ef",
"sha256:a30a1561469f19cfb1f03194573e2a7deae7b1f795df3f49cf897e4cbb076810",
"sha256:9e05c6437766b6f5327d4eaa2d52afd5a1d77844654da2c2677dae4e2a169ce1",
"sha256:74a8a69837848c930d92c87710bb4434c777cc26df833bb07cc96a6a1b057699",
"sha256:04d1b7c2e79ea1ded08aa2648dfda342408a80d76462363617062da669f1e58d",
"sha256:4f0b8faf196feaf5532495b6beab4b1dbba3eb182549fdeec4b36c10f2b4a98d",
"sha256:9d5dea1ec497da5e4df11c51e2f64e78774afd20cfb76922122212b415354c1c",
"sha256:16fcfc4c312069e71a2b15b503d050a1fa6e4e8ff7f6307bd4624ed5ae26a02b",
"sha256:47a94159e091d7df01324c02df66da3e09bf2b433d29029f8ff7701b12252645",
"sha256:11a31178f390fa7ff54d22c919145e0d5d08d8cbe6cb9f4d1878422f91d0f72b",
"sha256:62c09c5dd31373888d1176caae0e2c29dbe0eb50ea6c017e03eda5762bb199ef",
"sha256:b46e3e74f29db8c5a4bb61465b10bda31509c3e023bcfc75071b20dfe361f283",
"sha256:7d91b9c413331ab014b970cccee1f08f46ac8bebaf340977bc792b04c751bfdf",
"sha256:211a820d998ad9b3840dfd4426e81635b60b71350d396c2b23b99cac507e8e73",
"sha256:d44a74075c3d515bdf752b3552903797bbff5295bd24f3c3e502f9666eeac04d",
"sha256:a5a8d341c686fecaad7819aeee2875dc83e15d99ca6f7fe7be463d006b6b1467",
"sha256:2712a5af4a42a51ecf2927d4e0231c3a33e7774eef065c77531c423eb8dd5a07",
"sha256:53a18e12e8e506d25a82ca110a2d82fd8a83ef0a0d781d3c30c0eb58ccd35453",
"sha256:022e100ab8d52dd164093f5d17d75168fbd9abf4b4af59fc0addc4fb81a51b0a",
"sha256:7d58b51fea312de1c261c77569e0bfc0c090d3869b91c49a7e26d2e7507a8bca",
"sha256:ac2722262e037c71965f051cfcca8fec3be837b421d13716ed1bb768329fce60",
"sha256:39fb97975406b8b5852427ffc350bc3ea9ec82d72392ce5d262b28b7946c72a7",
"sha256:b622eebd498f6f83977a3c1ab1a7d5f7b915a5fdd135d581e8ad762ef4c97a53",
"sha256:a8b3bf9067935f8502147b9c38c8dce355a17d3191b675ad6ec5187e9e4dbcba",
"sha256:b9014abcf38849559ce4eb2aefbb9ee0e3f3378c7db23ff2cd8b5a8aaca14306",
"sha256:4dde7e5d6106e64ea845fe2bf2f228cd909c67c9c421bcc48e09ca9b88db1cc1",
"sha256:35b38cb57a2547ed5087a895b95b7786746c5e948d2b84e9484abaa3a5c921cd"
]
},
"Metadata": {
"LastTagTime": "2025-12-24T03:08:53.238954121+08:00"
}
}