docker.io/nvcr.io/nvidia/pytorch:25.04-py3 linux/amd64

Docker拉取命令

docker pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nvcr.io/nvidia/pytorch:25.04-py3
docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nvcr.io/nvidia/pytorch:25.04-py3  docker.io/nvcr.io/nvidia/pytorch:25.04-py3

Containerd拉取命令

ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nvcr.io/nvidia/pytorch:25.04-py3
ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nvcr.io/nvidia/pytorch:25.04-py3  docker.io/nvcr.io/nvidia/pytorch:25.04-py3

Shell快速替换命令

sed -i 's#nvcr.io/nvidia/pytorch:25.04-py3#swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nvcr.io/nvidia/pytorch:25.04-py3#' 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/nvcr.io/nvidia/pytorch:25.04-py3 && docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nvcr.io/nvidia/pytorch:25.04-py3  docker.io/nvcr.io/nvidia/pytorch:25.04-py3'

Ansible快速分发-Containerd

#ansible k8s -m shell -a 'ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nvcr.io/nvidia/pytorch:25.04-py3 && ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nvcr.io/nvidia/pytorch:25.04-py3  docker.io/nvcr.io/nvidia/pytorch:25.04-py3'

镜像构建历史

# 2025-04-16 04:00:55  0.00B 添加元数据标签
LABEL com.nvidia.build.ref=8d28f2ff75a3f186220e187654c5890a49f8d87a
                        
# 2025-04-16 04:00:55  0.00B 定义构建参数
ARG NVIDIA_BUILD_REF=8d28f2ff75a3f186220e187654c5890a49f8d87a
                        
# 2025-04-16 04:00:55  0.00B 添加元数据标签
LABEL com.nvidia.build.id=159049541
                        
# 2025-04-16 04:00:55  0.00B 设置环境变量 NVIDIA_BUILD_ID
ENV NVIDIA_BUILD_ID=159049541
                        
# 2025-04-16 04:00:55  0.00B 定义构建参数
ARG NVIDIA_BUILD_ID=159049541
                        
# 2025-04-16 04:00:55  719.00B 复制新文件或目录到容器中
COPY entrypoint.d/ /opt/nvidia/entrypoint.d/ # buildkit
                        
# 2025-04-16 04:00:55  84.06KB 执行命令并创建新的镜像层
RUN |8 NVIDIA_PYTORCH_VERSION=25.04 PYTORCH_BUILD_VERSION=2.7.0a0+79aa174 NVFUSER_BUILD_VERSION=5111d3b TARGETARCH=amd64 PYVER=3.12 PYVER_MAJMIN=312 L4T=0 DALI_EXTRA_INDEX_URL=http://sqrl/nvdl/datasets/dali/pip-dali /bin/sh -c ln -sf ${_CUDA_COMPAT_PATH}/lib.real ${_CUDA_COMPAT_PATH}/lib  && echo ${_CUDA_COMPAT_PATH}/lib > /etc/ld.so.conf.d/00-cuda-compat.conf  && ldconfig  && rm -f ${_CUDA_COMPAT_PATH}/lib # buildkit
                        
# 2025-04-16 04:00:55  0.00B 设置环境变量 TORCH_NCCL_USE_COMM_NONBLOCKING
ENV TORCH_NCCL_USE_COMM_NONBLOCKING=0
                        
# 2025-04-16 04:00:55  0.00B 设置环境变量 CUDA_MODULE_LOADING
ENV CUDA_MODULE_LOADING=LAZY
                        
# 2025-04-16 04:00:55  805.14MB 执行命令并创建新的镜像层
RUN |8 NVIDIA_PYTORCH_VERSION=25.04 PYTORCH_BUILD_VERSION=2.7.0a0+79aa174 NVFUSER_BUILD_VERSION=5111d3b TARGETARCH=amd64 PYVER=3.12 PYVER_MAJMIN=312 L4T=0 DALI_EXTRA_INDEX_URL=http://sqrl/nvdl/datasets/dali/pip-dali /bin/sh -c if [ "${L4T}" = "1" ]; then echo "Not installing Transformer Engine in iGPU container until Version variable is set"; else     /nvidia/build-scripts/installCAL.sh &&     /nvidia/build-scripts/installCUBLASMP.sh &&     /nvidia/build-scripts/installNVSHMEM.sh &&     git clone -b release_v${TRANSFORMER_ENGINE_VERSION} --single-branch --recursive https://github.com/NVIDIA/TransformerEngine.git &&     env NVTE_CUDA_ARCHS="70;80;89;90;100;120" NVTE_BUILD_THREADS_PER_JOB=8 pip install --no-cache-dir --no-build-isolation ./TransformerEngine &&     rm -rf TransformerEngine; fi # buildkit
                        
# 2025-04-16 03:53:10  1.44GB 执行命令并创建新的镜像层
RUN |8 NVIDIA_PYTORCH_VERSION=25.04 PYTORCH_BUILD_VERSION=2.7.0a0+79aa174 NVFUSER_BUILD_VERSION=5111d3b TARGETARCH=amd64 PYVER=3.12 PYVER_MAJMIN=312 L4T=0 DALI_EXTRA_INDEX_URL=http://sqrl/nvdl/datasets/dali/pip-dali /bin/sh -c if [ "${L4T}" = "1" ]; then echo "Not installing Flash Attention wheel in iGPU as it is a requirement for Transformer Engine"; else     pip install --no-cache-dir /opt/pytorch/flash_attn*.whl; fi # buildkit
                        
# 2025-04-16 03:22:45  46.02MB 执行命令并创建新的镜像层
RUN |8 NVIDIA_PYTORCH_VERSION=25.04 PYTORCH_BUILD_VERSION=2.7.0a0+79aa174 NVFUSER_BUILD_VERSION=5111d3b TARGETARCH=amd64 PYVER=3.12 PYVER_MAJMIN=312 L4T=0 DALI_EXTRA_INDEX_URL=http://sqrl/nvdl/datasets/dali/pip-dali /bin/sh -c pip install --no-cache-dir /opt/pytorch/torch_tensorrt/dist/*.whl # buildkit
                        
# 2025-04-16 03:22:43  602.83MB 执行命令并创建新的镜像层
RUN |8 NVIDIA_PYTORCH_VERSION=25.04 PYTORCH_BUILD_VERSION=2.7.0a0+79aa174 NVFUSER_BUILD_VERSION=5111d3b TARGETARCH=amd64 PYVER=3.12 PYVER_MAJMIN=312 L4T=0 DALI_EXTRA_INDEX_URL=http://sqrl/nvdl/datasets/dali/pip-dali /bin/sh -c pip install --no-cache-dir /opt/pytorch/apex/dist/*.whl # buildkit
                        
# 2025-04-16 02:48:39  0.00B 设置环境变量 PATH
ENV PATH=/usr/local/lib/python3.12/dist-packages/torch_tensorrt/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/mpi/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/ucx/bin:/opt/amazon/efa/bin:/opt/tensorrt/bin
                        
# 2025-04-16 02:48:39  0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/lib/python3.12/dist-packages/torch/lib:/usr/local/lib/python3.12/dist-packages/torch_tensorrt/lib:/usr/local/cuda/compat/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64
                        
# 2025-04-16 02:48:39  0.00B 定义构建参数
ARG PYVER=3.12
                        
# 2025-04-16 02:48:39  162.08MB 复制新文件或目录到容器中
COPY torch_tensorrt/ /opt/pytorch/torch_tensorrt/ # buildkit
                        
# 2025-04-16 02:48:38  54.40MB 执行命令并创建新的镜像层
RUN |8 NVIDIA_PYTORCH_VERSION=25.04 PYTORCH_BUILD_VERSION=2.7.0a0+79aa174 NVFUSER_BUILD_VERSION=5111d3b TARGETARCH=amd64 PYVER=3.12 PYVER_MAJMIN=312 L4T=0 DALI_EXTRA_INDEX_URL=http://sqrl/nvdl/datasets/dali/pip-dali /bin/sh -c pip --version && python -c 'import sys; print(sys.platform)'     && pip install --extra-index-url https://urm.nvidia.com/artifactory/api/pypi/sw-tensorrt-pypi/simple --no-cache-dir "polygraphy==${POLYGRAPHY_VERSION}"     && pip install  --index-url https://gitlab-master.nvidia.com/api/v4/projects/95421/packages/pypi/simple --extra-index-url https://pypi.nvidia.com "nvidia-modelopt[torch]==${MODEL_OPT_VERSION}" # buildkit
                        
# 2025-04-16 02:48:32  0.00B 设置环境变量 PATH
ENV PATH=/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/mpi/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/ucx/bin:/opt/amazon/efa/bin:/opt/tensorrt/bin
                        
# 2025-04-16 02:48:32  6.59MB 执行命令并创建新的镜像层
RUN |8 NVIDIA_PYTORCH_VERSION=25.04 PYTORCH_BUILD_VERSION=2.7.0a0+79aa174 NVFUSER_BUILD_VERSION=5111d3b TARGETARCH=amd64 PYVER=3.12 PYVER_MAJMIN=312 L4T=0 DALI_EXTRA_INDEX_URL=http://sqrl/nvdl/datasets/dali/pip-dali /bin/sh -c set -x     && WHEELS=1 /nvidia/build-scripts/installTRT.sh # buildkit
                        
# 2025-04-16 02:46:46  34.90MB 执行命令并创建新的镜像层
RUN |8 NVIDIA_PYTORCH_VERSION=25.04 PYTORCH_BUILD_VERSION=2.7.0a0+79aa174 NVFUSER_BUILD_VERSION=5111d3b TARGETARCH=amd64 PYVER=3.12 PYVER_MAJMIN=312 L4T=0 DALI_EXTRA_INDEX_URL=http://sqrl/nvdl/datasets/dali/pip-dali /bin/sh -c chmod -R a+w . # buildkit
                        
# 2025-04-16 02:46:45  34.89MB 复制新文件或目录到容器中
COPY tutorials tutorials # buildkit
                        
# 2025-04-16 02:46:45  2.07KB 复制新文件或目录到容器中
COPY docker-examples docker-examples # buildkit
                        
# 2025-04-16 02:46:45  2.05KB 复制新文件或目录到容器中
COPY NVREADME.md README.md # buildkit
                        
# 2025-04-16 02:46:45  0.00B 设置工作目录为/workspace
WORKDIR /workspace
                        
# 2025-04-16 02:46:45  2.67GB 执行命令并创建新的镜像层
RUN |8 NVIDIA_PYTORCH_VERSION=25.04 PYTORCH_BUILD_VERSION=2.7.0a0+79aa174 NVFUSER_BUILD_VERSION=5111d3b TARGETARCH=amd64 PYVER=3.12 PYVER_MAJMIN=312 L4T=0 DALI_EXTRA_INDEX_URL=http://sqrl/nvdl/datasets/dali/pip-dali /bin/sh -c if [ "${L4T}" = "1" ]; then     echo "Not installing rapids for L4T build."; exit 0; fi  && find /rapids  -name "*-Linux.tar.gz" -exec     tar -C /usr --exclude="*.a" --exclude="bin/xgboost" --strip-components=1 -xvf {} \;  && find /rapids -name "*.whl"     ! -name "tornado-*"     ! -name "Pillow-*"     ! -name "certifi-*"     ! -name "protobuf-*"     ! -name "six-*"     -exec pip install --no-cache-dir {} + # buildkit
                        
# 2025-04-16 02:46:13  224.07KB 执行命令并创建新的镜像层
RUN |8 NVIDIA_PYTORCH_VERSION=25.04 PYTORCH_BUILD_VERSION=2.7.0a0+79aa174 NVFUSER_BUILD_VERSION=5111d3b TARGETARCH=amd64 PYVER=3.12 PYVER_MAJMIN=312 L4T=0 DALI_EXTRA_INDEX_URL=http://sqrl/nvdl/datasets/dali/pip-dali /bin/sh -c pip install tabulate # buildkit
                        
# 2025-04-16 02:46:11  173.53MB 执行命令并创建新的镜像层
RUN |8 NVIDIA_PYTORCH_VERSION=25.04 PYTORCH_BUILD_VERSION=2.7.0a0+79aa174 NVFUSER_BUILD_VERSION=5111d3b TARGETARCH=amd64 PYVER=3.12 PYVER_MAJMIN=312 L4T=0 DALI_EXTRA_INDEX_URL=http://sqrl/nvdl/datasets/dali/pip-dali /bin/sh -c ( cd fuser && pip install -r requirements.txt &&  python setup.py -version-tag=a0+${NVFUSER_VERSION} install && python setup.py clean && cp $(find /usr/local/lib/python${PYVER}/dist-packages/ -name libnvfuser_codegen.so)  /usr/local/lib/python${PYVER}/dist-packages/torch/lib/ )  && ( cd lightning-thunder && python setup.py install && rm -rf build *.egg-info)  && ( cd lightning-thunder && mkdir tmp && cd tmp && git clone -b v${CUDNN_FRONTEND_VERSION} --recursive --single-branch https://github.com/NVIDIA/cudnn-frontend.git cudnn_frontend && cd cudnn_frontend && pip install --no-build-isolation . && cd ../../ && rm -rf tmp )  && ( cd pytorch/third_party/onnx && pip uninstall typing -y && CMAKE_ARGS="-DONNX_USE_PROTOBUF_SHARED_LIBS=ON" pip install --no-build-isolation . ) # buildkit
                        
# 2025-04-16 02:39:37  2.21KB 复制新文件或目录到容器中
COPY singularity/ /.singularity.d/ # buildkit
                        
# 2025-04-16 02:39:37  70.82MB 执行命令并创建新的镜像层
RUN |8 NVIDIA_PYTORCH_VERSION=25.04 PYTORCH_BUILD_VERSION=2.7.0a0+79aa174 NVFUSER_BUILD_VERSION=5111d3b TARGETARCH=amd64 PYVER=3.12 PYVER_MAJMIN=312 L4T=0 DALI_EXTRA_INDEX_URL=http://sqrl/nvdl/datasets/dali/pip-dali /bin/sh -c export COCOAPI_TAG=$(echo ${COCOAPI_VERSION} | sed 's/^.*+n//')  && pip install git+https://github.com/nvidia/cocoapi.git@${COCOAPI_TAG}#subdirectory=PythonAPI # buildkit
                        
# 2025-04-16 02:39:09  0.00B 设置环境变量 COCOAPI_VERSION
ENV COCOAPI_VERSION=2.0+nv0.8.1
                        
# 2025-04-16 02:39:09  955.38MB 执行命令并创建新的镜像层
RUN |8 NVIDIA_PYTORCH_VERSION=25.04 PYTORCH_BUILD_VERSION=2.7.0a0+79aa174 NVFUSER_BUILD_VERSION=5111d3b TARGETARCH=amd64 PYVER=3.12 PYVER_MAJMIN=312 L4T=0 DALI_EXTRA_INDEX_URL=http://sqrl/nvdl/datasets/dali/pip-dali /bin/sh -c if [ -z "${DALI_VERSION}" ] ; then   echo "Not Installing DALI for L4T Build." ; exit 0; fi   && export CUDA_VERSION_MAJOR=$(ls /usr/local/cuda/lib64/libcudart.so.*.*.* | cut -d . -f 3)   && export DALI_PKG_SUFFIX="cuda${CUDA_VERSION_MAJOR}0"   && if [ -z "${DALI_URL_SUFFIX}" ] ; then export DALI_EXTRA_INDEX_URL="${DALI_EXTRA_INDEX_URL}-qa"; fi   && pip install                 --extra-index-url https://developer.download.nvidia.com/compute/redist                 --extra-index-url "${DALI_EXTRA_INDEX_URL}"                 --trusted-host sqrl         nvidia-dali-${DALI_PKG_SUFFIX}==${DALI_VERSION} # buildkit
                        
# 2025-04-16 02:38:56  0.00B 定义构建参数
ARG DALI_EXTRA_INDEX_URL=http://sqrl/nvdl/datasets/dali/pip-dali
                        
# 2025-04-16 02:38:56  701.66MB 执行命令并创建新的镜像层
RUN |7 NVIDIA_PYTORCH_VERSION=25.04 PYTORCH_BUILD_VERSION=2.7.0a0+79aa174 NVFUSER_BUILD_VERSION=5111d3b TARGETARCH=amd64 PYVER=3.12 PYVER_MAJMIN=312 L4T=0 /bin/sh -c pip install --no-cache-dir /tmp/dist/*.whl # buildkit
                        
# 2025-04-16 02:38:43  8.62MB 执行命令并创建新的镜像层
RUN |7 NVIDIA_PYTORCH_VERSION=25.04 PYTORCH_BUILD_VERSION=2.7.0a0+79aa174 NVFUSER_BUILD_VERSION=5111d3b TARGETARCH=amd64 PYVER=3.12 PYVER_MAJMIN=312 L4T=0 /bin/sh -c cd pytorch && pip install -v -r /opt/pytorch/pytorch/requirements.txt # buildkit
                        
# 2025-04-16 02:38:41  14.48MB 执行命令并创建新的镜像层
RUN |7 NVIDIA_PYTORCH_VERSION=25.04 PYTORCH_BUILD_VERSION=2.7.0a0+79aa174 NVFUSER_BUILD_VERSION=5111d3b TARGETARCH=amd64 PYVER=3.12 PYVER_MAJMIN=312 L4T=0 /bin/sh -c patchelf --set-rpath '$ORIGIN:/usr/local/lib/python3.12/dist-packages/torch/lib:/usr/local/lib/python3.12/dist-packages/torchvision/' /usr/local/lib/libtorchvision.so.1.0 && patchelf --set-soname libtorchvision.so.1 --output /usr/local/lib/libtorchvision.so.1.0 /usr/local/lib/libtorchvision.so.1.0 && ldconfig && pushd /usr/local/lib && ln -s libtorchvision.so.1 /usr/local/lib/libtorchvision.so && popd && patchelf --set-soname libjpeg.so.62 --output /usr/local/lib/libjpeg.so.62 $(readlink -f $(ldd /usr/local/lib/python3.12/dist-packages/torchvision/image.so | grep libjpeg | awk '{print $3}')) # buildkit
                        
# 2025-04-16 02:38:41  0.00B 复制新文件或目录到容器中
COPY /usr/local/lib64/libjpeg* /usr/local/lib/ # buildkit
                        
# 2025-04-16 02:38:41  12.29MB 复制新文件或目录到容器中
COPY /usr/local/lib64/libtorchvision.so /usr/local/lib/libtorchvision.so.1.0 # buildkit
                        
# 2025-04-16 02:38:41  397.33KB 复制新文件或目录到容器中
COPY /usr/local/include/torchvision/ /usr/local/include/torchvision/ # buildkit
                        
# 2025-04-16 02:38:41  9.01KB 复制新文件或目录到容器中
COPY /usr/local/share/cmake/TorchVision/ /usr/local/share/cmake/TorchVision/ # buildkit
                        
# 2025-04-16 02:38:41  2.30GB 执行命令并创建新的镜像层
RUN |7 NVIDIA_PYTORCH_VERSION=25.04 PYTORCH_BUILD_VERSION=2.7.0a0+79aa174 NVFUSER_BUILD_VERSION=5111d3b TARGETARCH=amd64 PYVER=3.12 PYVER_MAJMIN=312 L4T=0 /bin/sh -c pip install /opt/transfer/torch*.whl     && patchelf --set-rpath '/usr/local/lib' /usr/local/lib/python${PYVER}/dist-packages/torch/lib/libtorch_global_deps.so # buildkit
                        
# 2025-04-16 02:38:13  0.00B 设置环境变量 TORCH_ALLOW_TF32_CUBLAS_OVERRIDE
ENV TORCH_ALLOW_TF32_CUBLAS_OVERRIDE=1
                        
# 2025-04-16 02:38:13  0.00B 设置环境变量 CUDA_HOME
ENV CUDA_HOME=/usr/local/cuda
                        
# 2025-04-16 02:38:13  0.00B 设置环境变量 PYTORCH_HOME
ENV PYTORCH_HOME=/opt/pytorch/pytorch
                        
# 2025-04-16 02:38:13  0.00B 设置环境变量 TORCH_CUDA_ARCH_LIST
ENV TORCH_CUDA_ARCH_LIST=7.5 8.0 8.6 9.0 10.0 12.0+PTX
                        
# 2025-04-16 02:38:13  0.00B 设置环境变量 UCC_CL_BASIC_TLS
ENV UCC_CL_BASIC_TLS=^sharp
                        
# 2025-04-16 02:38:13  65.56MB 执行命令并创建新的镜像层
RUN |7 NVIDIA_PYTORCH_VERSION=25.04 PYTORCH_BUILD_VERSION=2.7.0a0+79aa174 NVFUSER_BUILD_VERSION=5111d3b TARGETARCH=amd64 PYVER=3.12 PYVER_MAJMIN=312 L4T=0 /bin/sh -c OPENCV_VERSION=4.10.0 &&     cd / &&     wget -q -O - https://github.com/opencv/opencv/archive/${OPENCV_VERSION}.tar.gz | tar -xzf - &&     cd /opencv-${OPENCV_VERSION} &&     cmake -GNinja -Bbuild -H.           -DWITH_CUDA=OFF -DWITH_1394=OFF           -DPYTHON3_PACKAGES_PATH="/usr/local/lib/python${PYVER}/dist-packages"           -DBUILD_opencv_cudalegacy=OFF -DBUILD_opencv_stitching=OFF -DWITH_IPP=OFF -DWITH_PROTOBUF=OFF &&     cmake --build build --target install &&     cd modules/python/package &&     pip install -v . &&     rm -rf /opencv-${OPENCV_VERSION} # buildkit
                        
# 2025-04-16 02:33:58  0.00B 声明容器运行时监听的端口
EXPOSE map[6006/tcp:{}]
                        
# 2025-04-16 02:33:58  0.00B 声明容器运行时监听的端口
EXPOSE map[8888/tcp:{}]
                        
# 2025-04-16 02:33:58  0.00B 设置环境变量 TENSORBOARD_PORT
ENV TENSORBOARD_PORT=6006
                        
# 2025-04-16 02:33:58  0.00B 设置环境变量 JUPYTER_PORT
ENV JUPYTER_PORT=8888
                        
# 2025-04-16 02:33:58  248.00B 复制新文件或目录到容器中
COPY jupyter_config/settings.jupyterlab-settings /root/.jupyter/lab/user-settings/@jupyterlab/completer-extension/ # buildkit
                        
# 2025-04-16 02:33:58  236.00B 复制新文件或目录到容器中
COPY jupyter_config/manager.jupyterlab-settings /root/.jupyter/lab/user-settings/@jupyterlab/completer-extension/ # buildkit
                        
# 2025-04-16 02:33:58  519.00B 复制新文件或目录到容器中
COPY jupyter_config/jupyter_notebook_config.py /usr/local/etc/jupyter/ # buildkit
                        
# 2025-04-16 02:33:58  14.33MB 执行命令并创建新的镜像层
RUN |7 NVIDIA_PYTORCH_VERSION=25.04 PYTORCH_BUILD_VERSION=2.7.0a0+79aa174 NVFUSER_BUILD_VERSION=5111d3b TARGETARCH=amd64 PYVER=3.12 PYVER_MAJMIN=312 L4T=0 /bin/sh -c pip install --no-cache-dir /builder/*.whl jupytext black isort  && mkdir -p /root/.jupyter/lab/user-settings/@jupyterlab/completer-extension/  && jupyter lab clean # buildkit
                        
# 2025-04-16 02:33:12  0.00B 设置工作目录为/opt/pytorch
WORKDIR /opt/pytorch
                        
# 2025-04-16 02:33:12  27.81KB 执行命令并创建新的镜像层
RUN |7 NVIDIA_PYTORCH_VERSION=25.04 PYTORCH_BUILD_VERSION=2.7.0a0+79aa174 NVFUSER_BUILD_VERSION=5111d3b TARGETARCH=amd64 PYVER=3.12 PYVER_MAJMIN=312 L4T=0 /bin/sh -c PATCHED_FILE=$(python -c "from tensorboard.plugins.core import core_plugin as _; print(_.__file__)") &&     sed -i 's/^\( *"--bind_all",\)$/\1 default=True,/' "$PATCHED_FILE" &&     test $(grep '^ *"--bind_all", default=True,$' "$PATCHED_FILE" | wc -l) -eq 1 # buildkit
                        
# 2025-04-16 02:33:11  244.98MB 执行命令并创建新的镜像层
RUN |7 NVIDIA_PYTORCH_VERSION=25.04 PYTORCH_BUILD_VERSION=2.7.0a0+79aa174 NVFUSER_BUILD_VERSION=5111d3b TARGETARCH=amd64 PYVER=3.12 PYVER_MAJMIN=312 L4T=0 /bin/sh -c git config --global url."https://github".insteadOf git://github &&     pip install jupyterlab notebook tensorboard     jupyterlab_code_formatter python-hostlist # buildkit
                        
# 2025-04-16 02:32:58  2.21GB 执行命令并创建新的镜像层
RUN |7 NVIDIA_PYTORCH_VERSION=25.04 PYTORCH_BUILD_VERSION=2.7.0a0+79aa174 NVFUSER_BUILD_VERSION=5111d3b TARGETARCH=amd64 PYVER=3.12 PYVER_MAJMIN=312 L4T=0 /bin/sh -c pip install         numpy         scipy         PyYAML         astunparse         typing_extensions         cffi         spacy         mock         tqdm         librosa         expecttest         hypothesis         xdoctest         pytest         pytest-xdist         pytest-rerunfailures         pytest-shard         pytest-flakefinder         pybind11         Cython         regex         protobuf         six &&     if [[ $TARGETARCH = "amd64" ]] ; then pip install --no-cache-dir mkl mkl-include mkl-devel ;     find /usr/local/lib -maxdepth 1 -type f -regex '.*\/lib\(tbb\|mkl\).*\.so\($\|\.[0-9]*\.[0-9]*\)' -exec rm -v {} + ; fi # buildkit
                        
# 2025-04-16 02:32:06  0.00B 设置环境变量 PIP_DEFAULT_TIMEOUT
ENV PIP_DEFAULT_TIMEOUT=100
                        
# 2025-04-16 02:32:06  0.00B 设置环境变量 LC_ALL
ENV LC_ALL=C.UTF-8
                        
# 2025-04-16 02:32:06  0.00B 设置环境变量 PYTHONIOENCODING
ENV PYTHONIOENCODING=utf-8
                        
# 2025-04-16 02:32:06  1.46GB 复制新文件或目录到容器中
COPY . . # buildkit
                        
# 2025-04-16 02:31:57  0.00B 设置工作目录为/opt/pytorch
WORKDIR /opt/pytorch
                        
# 2025-04-16 02:31:57  0.00B 设置环境变量 NVPL_LAPACK_MATH_MODE
ENV NVPL_LAPACK_MATH_MODE=PEDANTIC
                        
# 2025-04-16 02:31:57  0.00B 执行命令并创建新的镜像层
RUN |7 NVIDIA_PYTORCH_VERSION=25.04 PYTORCH_BUILD_VERSION=2.7.0a0+79aa174 NVFUSER_BUILD_VERSION=5111d3b TARGETARCH=amd64 PYVER=3.12 PYVER_MAJMIN=312 L4T=0 /bin/sh -c if [ $TARGETARCH = "arm64" ]; then cd /opt &&     curl "https://gitlab-master.nvidia.com/api/v4/projects/105799/packages/generic/nvpl_slim_24.04/sbsa/nvpl_slim_24.04.tar" --output nvpl_slim_24.04.tar &&     tar -xf nvpl_slim_24.04.tar &&     cp -r nvpl_slim_24.04/lib/* /usr/local/lib &&     cp -r nvpl_slim_24.04/include/* /usr/local/include &&     rm -rf nvpl_slim_24.04.tar nvpl_slim_24.04 ; fi # buildkit
                        
# 2025-04-16 02:31:57  46.71MB 执行命令并创建新的镜像层
RUN |7 NVIDIA_PYTORCH_VERSION=25.04 PYTORCH_BUILD_VERSION=2.7.0a0+79aa174 NVFUSER_BUILD_VERSION=5111d3b TARGETARCH=amd64 PYVER=3.12 PYVER_MAJMIN=312 L4T=0 /bin/sh -c curl "https://gitlab-master.nvidia.com/api/v4/projects/105799/packages/generic/OpenBLAS/0.3.24-$(uname -m)/OpenBLAS-0.3.24-$(uname -m).tar.gz" --output OpenBLAS.tar.gz &&     tar -xf OpenBLAS.tar.gz -C /usr/local/ &&     rm OpenBLAS.tar.gz # buildkit
                        
# 2025-04-16 02:31:56  76.82MB 执行命令并创建新的镜像层
RUN |7 NVIDIA_PYTORCH_VERSION=25.04 PYTORCH_BUILD_VERSION=2.7.0a0+79aa174 NVFUSER_BUILD_VERSION=5111d3b TARGETARCH=amd64 PYVER=3.12 PYVER_MAJMIN=312 L4T=0 /bin/sh -c pip install pip setuptools &&     pip install cmake # buildkit
                        
# 2025-04-16 02:31:53  5.78KB 复制新文件或目录到容器中
COPY constraint.txt /etc/pip/constraint.txt # buildkit
                        
# 2025-04-16 02:31:53  0.00B 设置环境变量 PIP_CONSTRAINT
ENV PIP_CONSTRAINT=/etc/pip/constraint.txt
                        
# 2025-04-16 02:31:53  13.00MB 执行命令并创建新的镜像层
RUN |7 NVIDIA_PYTORCH_VERSION=25.04 PYTORCH_BUILD_VERSION=2.7.0a0+79aa174 NVFUSER_BUILD_VERSION=5111d3b TARGETARCH=amd64 PYVER=3.12 PYVER_MAJMIN=312 L4T=0 /bin/sh -c DEBIAN_FRONTEND=noninteractive apt remove -y --force-yes python3-pip &&    curl -O https://bootstrap.pypa.io/get-pip.py &&     python get-pip.py &&     rm get-pip.py # buildkit
                        
# 2025-04-16 02:31:50  0.00B 设置环境变量 PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION
ENV PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python
                        
# 2025-04-16 02:31:50  226.66MB 执行命令并创建新的镜像层
RUN |7 NVIDIA_PYTORCH_VERSION=25.04 PYTORCH_BUILD_VERSION=2.7.0a0+79aa174 NVFUSER_BUILD_VERSION=5111d3b TARGETARCH=amd64 PYVER=3.12 PYVER_MAJMIN=312 L4T=0 /bin/sh -c export PYSFX=`echo "${PYVER}" | cut -c1-1` &&     export DEBIAN_FRONTEND=noninteractive &&     apt-get update &&     apt-get install -y --no-install-recommends         python$PYVER-dev         python$PYSFX         python$PYSFX-dev         python$PYSFX-venv         python-is-python$PYSFX         autoconf         automake         libatlas-base-dev         libgoogle-glog-dev         libbz2-dev         libc-ares2         libre2-dev         libleveldb-dev         liblmdb-dev         libprotobuf-dev         libsnappy-dev         libtool         nasm         protobuf-compiler         pkg-config         unzip         sox         libsndfile1         libpng-dev         libhdf5-dev         gfortran         rapidjson-dev         ninja-build         libedit-dev         build-essential         patchelf     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2025-04-16 02:31:50  0.00B 定义构建参数
ARG L4T=0
                        
# 2025-04-16 02:31:50  0.00B 设置环境变量 PIP_BREAK_SYSTEM_PACKAGES
ENV PIP_BREAK_SYSTEM_PACKAGES=1
                        
# 2025-04-16 02:31:50  0.00B 定义构建参数
ARG PYVER_MAJMIN=312
                        
# 2025-04-16 02:31:50  0.00B 定义构建参数
ARG PYVER=3.12
                        
# 2025-04-16 02:31:50  0.00B 定义构建参数
ARG TARGETARCH=amd64
                        
# 2025-04-16 02:31:50  0.00B 添加元数据标签
LABEL com.nvidia.pytorch.version=2.7.0a0+79aa174
                        
# 2025-04-16 02:31:50  0.00B 设置环境变量 NVFUSER_BUILD_VERSION NVFUSER_VERSION
ENV NVFUSER_BUILD_VERSION=5111d3b NVFUSER_VERSION=5111d3b
                        
# 2025-04-16 02:31:50  0.00B 设置环境变量 PYTORCH_BUILD_VERSION PYTORCH_VERSION PYTORCH_BUILD_NUMBER NVIDIA_PYTORCH_VERSION
ENV PYTORCH_BUILD_VERSION=2.7.0a0+79aa174 PYTORCH_VERSION=2.7.0a0+79aa174 PYTORCH_BUILD_NUMBER=0 NVIDIA_PYTORCH_VERSION=25.04
                        
# 2025-04-16 02:31:50  0.00B 定义构建参数
ARG NVFUSER_BUILD_VERSION=5111d3b
                        
# 2025-04-16 02:31:50  0.00B 定义构建参数
ARG PYTORCH_BUILD_VERSION=2.7.0a0+79aa174
                        
# 2025-04-16 02:31:50  0.00B 定义构建参数
ARG NVIDIA_PYTORCH_VERSION=25.04
                        
# 2025-04-16 02:31:50  0.00B 设置环境变量 NVIDIA_PRODUCT_NAME
ENV NVIDIA_PRODUCT_NAME=PyTorch
                        
# 2025-04-16 00:59:31  0.00B 设置环境变量 LIBRARY_PATH
ENV LIBRARY_PATH=/usr/local/cuda/lib64/stubs:
                        
# 2025-04-16 00:59:31  1.01GB 执行命令并创建新的镜像层
RUN /bin/sh -c export DEVEL=1 BASE=0  && /nvidia/build-scripts/installNCU.sh  && /nvidia/build-scripts/installCUDA.sh  && /nvidia/build-scripts/installLIBS.sh  && if [ ! -f /etc/ld.so.conf.d/nvidia-tegra.conf ]; then /nvidia/build-scripts/installNCCL.sh; fi  && /nvidia/build-scripts/installCUDNN.sh  && /nvidia/build-scripts/installTRT.sh  && /nvidia/build-scripts/installNSYS.sh  && /nvidia/build-scripts/installCUSPARSELT.sh  && if [ -f "/tmp/cuda-${_CUDA_VERSION_MAJMIN}.patch" ]; then patch -p0 < /tmp/cuda-${_CUDA_VERSION_MAJMIN}.patch; fi  && rm -f /tmp/cuda-*.patch # buildkit
                        
# 2025-04-16 00:56:13  1.49KB 复制新文件或目录到容器中
COPY cuda-*.patch /tmp # buildkit
                        
# 2025-04-16 00:56:13  99.01MB 执行命令并创建新的镜像层
RUN /bin/sh -c export DEBIAN_FRONTEND=noninteractive  && apt-get update  && apt-get install -y --no-install-recommends         build-essential         git         libglib2.0-0         less         libhwloc15         libnl-route-3-200         libnl-3-dev         libnl-route-3-dev         libnuma-dev         libnuma1         libpmi2-0-dev         nano         numactl         openssh-client         vim         wget  && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2025-04-16 00:49:21  467.00B 执行命令并创建新的镜像层
RUN |39 JETPACK_HOST_MOUNTS= GDRCOPY_VERSION=2.4.1 HPCX_VERSION=2.22.1 RDMACORE_VERSION=50.0 MOFED_VERSION=5.4-rdmacore50.0 OPENUCX_VERSION=1.18.0 OPENMPI_VERSION=4.1.7 EFA_VERSION=1.38.1 AWS_OFI_NCCL_VERSION=1.14.0 TARGETARCH=amd64 CUDA_VERSION=12.9.0.036 CUDA_DRIVER_VERSION=575.51.02 NCCL_VERSION=2.26.3 CUBLAS_VERSION=12.9.0.2 CUFFT_VERSION=11.4.0.6 CURAND_VERSION=10.3.10.19 CUSPARSE_VERSION=12.5.9.5 CUSOLVER_VERSION=11.7.4.40 NPP_VERSION=12.4.0.27 NVJPEG_VERSION=12.4.0.16 CUFILE_VERSION=1.14.0.30 NVJITLINK_VERSION=12.9.41 CUBLASMP_VERSION=0.4.0.789 CAL_VERSION=0.4.4.50 NVSHMEM_VERSION=3.2.5 CUDNN_VERSION=9.9.0.52 CUDNN_FRONTEND_VERSION=1.11.0 TRT_VERSION=10.9.0.34+cuda12.8 TRTOSS_VERSION= NSIGHT_SYSTEMS_VERSION=2025.2.1.130 NSIGHT_COMPUTE_VERSION=2025.2.0.11 CUSPARSELT_VERSION=0.7.1.0 DALI_VERSION=1.48.0 DALI_BUILD= DALI_URL_SUFFIX=120 POLYGRAPHY_VERSION=0.49.20 TRANSFORMER_ENGINE_VERSION=2.2 MODEL_OPT_VERSION=0.25.0 _LIBPATH_SUFFIX= /bin/sh -c mkdir -p /workspace && cp -f -p /opt/nvidia/entrypoint.d/30-container-license.txt /workspace/license.txt # buildkit
                        
# 2025-04-16 00:49:21  0.00B 配置容器启动时运行的命令
ENTRYPOINT ["/opt/nvidia/nvidia_entrypoint.sh"]
                        
# 2025-04-16 00:49:21  0.00B 设置环境变量 NVIDIA_PRODUCT_NAME
ENV NVIDIA_PRODUCT_NAME=CUDA
                        
# 2025-04-16 00:49:21  16.04KB 复制新文件或目录到容器中
COPY entrypoint/ /opt/nvidia/ # buildkit
                        
# 2025-04-16 00:49:21  33.35KB 执行命令并创建新的镜像层
RUN |39 JETPACK_HOST_MOUNTS= GDRCOPY_VERSION=2.4.1 HPCX_VERSION=2.22.1 RDMACORE_VERSION=50.0 MOFED_VERSION=5.4-rdmacore50.0 OPENUCX_VERSION=1.18.0 OPENMPI_VERSION=4.1.7 EFA_VERSION=1.38.1 AWS_OFI_NCCL_VERSION=1.14.0 TARGETARCH=amd64 CUDA_VERSION=12.9.0.036 CUDA_DRIVER_VERSION=575.51.02 NCCL_VERSION=2.26.3 CUBLAS_VERSION=12.9.0.2 CUFFT_VERSION=11.4.0.6 CURAND_VERSION=10.3.10.19 CUSPARSE_VERSION=12.5.9.5 CUSOLVER_VERSION=11.7.4.40 NPP_VERSION=12.4.0.27 NVJPEG_VERSION=12.4.0.16 CUFILE_VERSION=1.14.0.30 NVJITLINK_VERSION=12.9.41 CUBLASMP_VERSION=0.4.0.789 CAL_VERSION=0.4.4.50 NVSHMEM_VERSION=3.2.5 CUDNN_VERSION=9.9.0.52 CUDNN_FRONTEND_VERSION=1.11.0 TRT_VERSION=10.9.0.34+cuda12.8 TRTOSS_VERSION= NSIGHT_SYSTEMS_VERSION=2025.2.1.130 NSIGHT_COMPUTE_VERSION=2025.2.0.11 CUSPARSELT_VERSION=0.7.1.0 DALI_VERSION=1.48.0 DALI_BUILD= DALI_URL_SUFFIX=120 POLYGRAPHY_VERSION=0.49.20 TRANSFORMER_ENGINE_VERSION=2.2 MODEL_OPT_VERSION=0.25.0 _LIBPATH_SUFFIX= /bin/sh -c if [ ! -f /etc/ld.so.conf.d/nvidia-tegra.conf ]; then            echo "/opt/amazon/aws-ofi-nccl/lib" > /etc/ld.so.conf.d/aws-ofi-nccl.conf       && ldconfig;                                                 fi # buildkit
                        
# 2025-04-16 00:49:21  5.11MB 复制新文件或目录到容器中
COPY /opt/amazon/aws-ofi-nccl /opt/amazon/aws-ofi-nccl # buildkit
                        
# 2025-04-16 00:48:01  0.00B 设置环境变量 PATH LD_LIBRARY_PATH NVIDIA_VISIBLE_DEVICES NVIDIA_DRIVER_CAPABILITIES
ENV PATH=/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/mpi/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/ucx/bin:/opt/amazon/efa/bin LD_LIBRARY_PATH=/usr/local/cuda/compat/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64 NVIDIA_VISIBLE_DEVICES=all NVIDIA_DRIVER_CAPABILITIES=compute,utility,video
                        
# 2025-04-16 00:48:01  0.00B 定义构建参数
ARG _LIBPATH_SUFFIX=
                        
# 2025-04-16 00:48:01  46.00B 执行命令并创建新的镜像层
RUN |38 JETPACK_HOST_MOUNTS= GDRCOPY_VERSION=2.4.1 HPCX_VERSION=2.22.1 RDMACORE_VERSION=50.0 MOFED_VERSION=5.4-rdmacore50.0 OPENUCX_VERSION=1.18.0 OPENMPI_VERSION=4.1.7 EFA_VERSION=1.38.1 AWS_OFI_NCCL_VERSION=1.14.0 TARGETARCH=amd64 CUDA_VERSION=12.9.0.036 CUDA_DRIVER_VERSION=575.51.02 NCCL_VERSION=2.26.3 CUBLAS_VERSION=12.9.0.2 CUFFT_VERSION=11.4.0.6 CURAND_VERSION=10.3.10.19 CUSPARSE_VERSION=12.5.9.5 CUSOLVER_VERSION=11.7.4.40 NPP_VERSION=12.4.0.27 NVJPEG_VERSION=12.4.0.16 CUFILE_VERSION=1.14.0.30 NVJITLINK_VERSION=12.9.41 CUBLASMP_VERSION=0.4.0.789 CAL_VERSION=0.4.4.50 NVSHMEM_VERSION=3.2.5 CUDNN_VERSION=9.9.0.52 CUDNN_FRONTEND_VERSION=1.11.0 TRT_VERSION=10.9.0.34+cuda12.8 TRTOSS_VERSION= NSIGHT_SYSTEMS_VERSION=2025.2.1.130 NSIGHT_COMPUTE_VERSION=2025.2.0.11 CUSPARSELT_VERSION=0.7.1.0 DALI_VERSION=1.48.0 DALI_BUILD= DALI_URL_SUFFIX=120 POLYGRAPHY_VERSION=0.49.20 TRANSFORMER_ENGINE_VERSION=2.2 MODEL_OPT_VERSION=0.25.0 /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
                        
# 2025-04-16 00:48:01  13.39KB 复制文件或目录到容器中
ADD docs.tgz / # buildkit
                        
# 2025-04-16 00:48:01  0.00B 设置环境变量 DALI_VERSION DALI_BUILD DALI_URL_SUFFIX POLYGRAPHY_VERSION TRANSFORMER_ENGINE_VERSION MODEL_OPT_VERSION
ENV DALI_VERSION=1.48.0 DALI_BUILD= DALI_URL_SUFFIX=120 POLYGRAPHY_VERSION=0.49.20 TRANSFORMER_ENGINE_VERSION=2.2 MODEL_OPT_VERSION=0.25.0
                        
# 2025-04-16 00:48:01  0.00B 定义构建参数
ARG MODEL_OPT_VERSION=0.25.0
                        
# 2025-04-16 00:48:01  0.00B 定义构建参数
ARG TRANSFORMER_ENGINE_VERSION=2.2
                        
# 2025-04-16 00:48:01  0.00B 定义构建参数
ARG POLYGRAPHY_VERSION=0.49.20
                        
# 2025-04-16 00:48:01  0.00B 定义构建参数
ARG DALI_URL_SUFFIX=120
                        
# 2025-04-16 00:48:01  0.00B 定义构建参数
ARG DALI_BUILD=
                        
# 2025-04-16 00:48:01  0.00B 定义构建参数
ARG DALI_VERSION=1.48.0
                        
# 2025-04-16 00:48:01  0.00B 添加元数据标签
LABEL com.nvidia.nccl.version=2.26.3 com.nvidia.cublas.version=12.9.0.2 com.nvidia.cufft.version=11.4.0.6 com.nvidia.curand.version=10.3.10.19 com.nvidia.cusparse.version=12.5.9.5 com.nvidia.cusparselt.version=0.7.1.0 com.nvidia.cusolver.version=11.7.4.40 com.nvidia.npp.version=12.4.0.27 com.nvidia.nvjpeg.version=12.4.0.16 com.nvidia.cublasmp.version=0.4.0.789 com.nvidia.cal.version=0.4.4.50 com.nvidia.cudnn.version=9.9.0.52 com.nvidia.tensorrt.version=10.9.0.34+cuda12.8 com.nvidia.tensorrtoss.version= com.nvidia.nsightsystems.version=2025.2.1.130 com.nvidia.nsightcompute.version=2025.2.0.11
                        
# 2025-04-16 00:48:01  7.59GB 执行命令并创建新的镜像层
RUN |32 JETPACK_HOST_MOUNTS= GDRCOPY_VERSION=2.4.1 HPCX_VERSION=2.22.1 RDMACORE_VERSION=50.0 MOFED_VERSION=5.4-rdmacore50.0 OPENUCX_VERSION=1.18.0 OPENMPI_VERSION=4.1.7 EFA_VERSION=1.38.1 AWS_OFI_NCCL_VERSION=1.14.0 TARGETARCH=amd64 CUDA_VERSION=12.9.0.036 CUDA_DRIVER_VERSION=575.51.02 NCCL_VERSION=2.26.3 CUBLAS_VERSION=12.9.0.2 CUFFT_VERSION=11.4.0.6 CURAND_VERSION=10.3.10.19 CUSPARSE_VERSION=12.5.9.5 CUSOLVER_VERSION=11.7.4.40 NPP_VERSION=12.4.0.27 NVJPEG_VERSION=12.4.0.16 CUFILE_VERSION=1.14.0.30 NVJITLINK_VERSION=12.9.41 CUBLASMP_VERSION=0.4.0.789 CAL_VERSION=0.4.4.50 NVSHMEM_VERSION=3.2.5 CUDNN_VERSION=9.9.0.52 CUDNN_FRONTEND_VERSION=1.11.0 TRT_VERSION=10.9.0.34+cuda12.8 TRTOSS_VERSION= NSIGHT_SYSTEMS_VERSION=2025.2.1.130 NSIGHT_COMPUTE_VERSION=2025.2.0.11 CUSPARSELT_VERSION=0.7.1.0 /bin/sh -c /nvidia/build-scripts/installLIBS.sh  && /nvidia/build-scripts/installCUDNN.sh  && /nvidia/build-scripts/installTRT.sh  && /nvidia/build-scripts/installNSYS.sh  && /nvidia/build-scripts/installNCU.sh  && /nvidia/build-scripts/installCUSPARSELT.sh  && if [ -z "${JETPACK_HOST_MOUNTS}" ]; then       /nvidia/build-scripts/installNCCL.sh;     fi; # buildkit
                        
# 2025-04-16 00:46:55  0.00B 设置环境变量 NCCL_VERSION CUBLAS_VERSION CUFFT_VERSION CURAND_VERSION CUSPARSE_VERSION CUSPARSELT_VERSION CUSOLVER_VERSION NPP_VERSION NVJPEG_VERSION CUFILE_VERSION NVJITLINK_VERSION CUBLASMP_VERSION CAL_VERSION NVSHMEM_VERSION CUDNN_VERSION CUDNN_FRONTEND_VERSION TRT_VERSION TRTOSS_VERSION NSIGHT_SYSTEMS_VERSION NSIGHT_COMPUTE_VERSION
ENV NCCL_VERSION=2.26.3 CUBLAS_VERSION=12.9.0.2 CUFFT_VERSION=11.4.0.6 CURAND_VERSION=10.3.10.19 CUSPARSE_VERSION=12.5.9.5 CUSPARSELT_VERSION=0.7.1.0 CUSOLVER_VERSION=11.7.4.40 NPP_VERSION=12.4.0.27 NVJPEG_VERSION=12.4.0.16 CUFILE_VERSION=1.14.0.30 NVJITLINK_VERSION=12.9.41 CUBLASMP_VERSION=0.4.0.789 CAL_VERSION=0.4.4.50 NVSHMEM_VERSION=3.2.5 CUDNN_VERSION=9.9.0.52 CUDNN_FRONTEND_VERSION=1.11.0 TRT_VERSION=10.9.0.34+cuda12.8 TRTOSS_VERSION= NSIGHT_SYSTEMS_VERSION=2025.2.1.130 NSIGHT_COMPUTE_VERSION=2025.2.0.11
                        
# 2025-04-16 00:46:55  0.00B 定义构建参数
ARG CUSPARSELT_VERSION=0.7.1.0
                        
# 2025-04-16 00:46:55  0.00B 定义构建参数
ARG NSIGHT_COMPUTE_VERSION=2025.2.0.11
                        
# 2025-04-16 00:46:55  0.00B 定义构建参数
ARG NSIGHT_SYSTEMS_VERSION=2025.2.1.130
                        
# 2025-04-16 00:46:55  0.00B 定义构建参数
ARG TRTOSS_VERSION=
                        
# 2025-04-16 00:46:55  0.00B 定义构建参数
ARG TRT_VERSION=10.9.0.34+cuda12.8
                        
# 2025-04-16 00:46:55  0.00B 定义构建参数
ARG CUDNN_FRONTEND_VERSION=1.11.0
                        
# 2025-04-16 00:46:55  0.00B 定义构建参数
ARG CUDNN_VERSION=9.9.0.52
                        
# 2025-04-16 00:46:55  0.00B 定义构建参数
ARG NVSHMEM_VERSION=3.2.5
                        
# 2025-04-16 00:46:55  0.00B 定义构建参数
ARG CAL_VERSION=0.4.4.50
                        
# 2025-04-16 00:46:55  0.00B 定义构建参数
ARG CUBLASMP_VERSION=0.4.0.789
                        
# 2025-04-16 00:46:55  0.00B 定义构建参数
ARG NVJITLINK_VERSION=12.9.41
                        
# 2025-04-16 00:46:55  0.00B 定义构建参数
ARG CUFILE_VERSION=1.14.0.30
                        
# 2025-04-16 00:46:55  0.00B 定义构建参数
ARG NVJPEG_VERSION=12.4.0.16
                        
# 2025-04-16 00:46:55  0.00B 定义构建参数
ARG NPP_VERSION=12.4.0.27
                        
# 2025-04-16 00:46:55  0.00B 定义构建参数
ARG CUSOLVER_VERSION=11.7.4.40
                        
# 2025-04-16 00:46:55  0.00B 定义构建参数
ARG CUSPARSE_VERSION=12.5.9.5
                        
# 2025-04-16 00:46:55  0.00B 定义构建参数
ARG CURAND_VERSION=10.3.10.19
                        
# 2025-04-16 00:46:55  0.00B 定义构建参数
ARG CUFFT_VERSION=11.4.0.6
                        
# 2025-04-16 00:46:55  0.00B 定义构建参数
ARG CUBLAS_VERSION=12.9.0.2
                        
# 2025-04-16 00:46:55  0.00B 定义构建参数
ARG NCCL_VERSION=2.26.3
                        
# 2025-04-16 00:46:55  0.00B 添加元数据标签
LABEL com.nvidia.volumes.needed=nvidia_driver com.nvidia.cuda.version=9.0
                        
# 2025-04-16 00:46:55  0.00B 设置环境变量 _CUDA_COMPAT_PATH ENV BASH_ENV SHELL NVIDIA_REQUIRE_CUDA
ENV _CUDA_COMPAT_PATH=/usr/local/cuda/compat ENV=/etc/shinit_v2 BASH_ENV=/etc/bash.bashrc SHELL=/bin/bash NVIDIA_REQUIRE_CUDA=cuda>=9.0
                        
# 2025-04-16 00:46:55  59.18KB 执行命令并创建新的镜像层
RUN |12 JETPACK_HOST_MOUNTS= GDRCOPY_VERSION=2.4.1 HPCX_VERSION=2.22.1 RDMACORE_VERSION=50.0 MOFED_VERSION=5.4-rdmacore50.0 OPENUCX_VERSION=1.18.0 OPENMPI_VERSION=4.1.7 EFA_VERSION=1.38.1 AWS_OFI_NCCL_VERSION=1.14.0 TARGETARCH=amd64 CUDA_VERSION=12.9.0.036 CUDA_DRIVER_VERSION=575.51.02 /bin/sh -c cp -vprd /nvidia/. /  &&  patch -p0 < /etc/startup_scripts.patch  &&  rm -f /etc/startup_scripts.patch # buildkit
                        
# 2025-04-16 00:46:55  874.65MB 执行命令并创建新的镜像层
RUN |12 JETPACK_HOST_MOUNTS= GDRCOPY_VERSION=2.4.1 HPCX_VERSION=2.22.1 RDMACORE_VERSION=50.0 MOFED_VERSION=5.4-rdmacore50.0 OPENUCX_VERSION=1.18.0 OPENMPI_VERSION=4.1.7 EFA_VERSION=1.38.1 AWS_OFI_NCCL_VERSION=1.14.0 TARGETARCH=amd64 CUDA_VERSION=12.9.0.036 CUDA_DRIVER_VERSION=575.51.02 /bin/sh -c /nvidia/build-scripts/installCUDA.sh # buildkit
                        
# 2025-04-11 09:18:54  0.00B 设置环境变量 CUDA_VERSION CUDA_DRIVER_VERSION
ENV CUDA_VERSION=12.9.0.036 CUDA_DRIVER_VERSION=575.51.02
                        
# 2025-04-11 09:18:54  0.00B 定义构建参数
ARG CUDA_DRIVER_VERSION=575.51.02
                        
# 2025-04-11 09:18:54  0.00B 定义构建参数
ARG CUDA_VERSION=12.9.0.036
                        
# 2025-04-11 09:18:54  0.00B 设置环境变量 OMPI_MCA_coll_hcoll_enable
ENV OMPI_MCA_coll_hcoll_enable=0
                        
# 2025-04-11 09:18:54  0.00B 设置环境变量 OPAL_PREFIX PATH
ENV OPAL_PREFIX=/opt/hpcx/ompi PATH=/usr/local/mpi/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/ucx/bin:/opt/amazon/efa/bin
                        
# 2025-04-11 09:18:54  230.02MB 执行命令并创建新的镜像层
RUN |10 JETPACK_HOST_MOUNTS= GDRCOPY_VERSION=2.4.1 HPCX_VERSION=2.22.1 RDMACORE_VERSION=50.0 MOFED_VERSION=5.4-rdmacore50.0 OPENUCX_VERSION=1.18.0 OPENMPI_VERSION=4.1.7 EFA_VERSION=1.38.1 AWS_OFI_NCCL_VERSION=1.14.0 TARGETARCH=amd64 /bin/sh -c cd /nvidia  && ( export DEBIAN_FRONTEND=noninteractive        && apt-get update                            && apt-get install -y --no-install-recommends              libibverbs1                                  libibverbs-dev                               librdmacm1                                   librdmacm-dev                                libibumad3                                   libibumad-dev                                ibverbs-utils                                ibverbs-providers                     && rm -rf /var/lib/apt/lists/*               && rm $(dpkg-query -L                                    libibverbs-dev                               librdmacm-dev                                libibumad-dev                            | grep "\(\.so\|\.a\)$")          )                                            && ( cd opt/gdrcopy/                              && dpkg -i libgdrapi_*.deb                   )                                         && ( cp -r opt/hpcx /opt/                                         && cp etc/ld.so.conf.d/hpcx.conf /etc/ld.so.conf.d/          && ln -sf /opt/hpcx/ompi /usr/local/mpi                      && ln -sf /opt/hpcx/ucx  /usr/local/ucx                      && sed -i 's/^\(hwloc_base_binding_policy\) = core$/\1 = none/' /opt/hpcx/ompi/etc/openmpi-mca-params.conf         && sed -i 's/^\(btl = self\)$/#\1/'                             /opt/hpcx/ompi/etc/openmpi-mca-params.conf       )                                                         && ( if [ ! -f /etc/ld.so.conf.d/nvidia-tegra.conf ]; then           cd opt/amazon/efa/                                           && dpkg -i libfabric*.deb                                    && rm /opt/amazon/efa/lib/libfabric.a                        && echo "/opt/amazon/efa/lib" > /etc/ld.so.conf.d/efa.conf;         fi                                                         )                                                         && ldconfig # buildkit
                        
# 2025-04-11 09:18:47  0.00B 定义构建参数
ARG TARGETARCH=amd64
                        
# 2025-04-11 09:18:47  0.00B 设置环境变量 GDRCOPY_VERSION HPCX_VERSION MOFED_VERSION OPENUCX_VERSION OPENMPI_VERSION RDMACORE_VERSION EFA_VERSION AWS_OFI_NCCL_VERSION
ENV GDRCOPY_VERSION=2.4.1 HPCX_VERSION=2.22.1 MOFED_VERSION=5.4-rdmacore50.0 OPENUCX_VERSION=1.18.0 OPENMPI_VERSION=4.1.7 RDMACORE_VERSION=50.0 EFA_VERSION=1.38.1 AWS_OFI_NCCL_VERSION=1.14.0
                        
# 2025-04-11 09:18:47  0.00B 定义构建参数
ARG AWS_OFI_NCCL_VERSION=1.14.0
                        
# 2025-04-11 09:18:47  0.00B 定义构建参数
ARG EFA_VERSION=1.38.1
                        
# 2025-04-11 09:18:47  0.00B 定义构建参数
ARG OPENMPI_VERSION=4.1.7
                        
# 2025-04-11 09:18:47  0.00B 定义构建参数
ARG OPENUCX_VERSION=1.18.0
                        
# 2025-04-11 09:18:47  0.00B 定义构建参数
ARG MOFED_VERSION=5.4-rdmacore50.0
                        
# 2025-04-11 09:18:47  0.00B 定义构建参数
ARG RDMACORE_VERSION=50.0
                        
# 2025-04-11 09:18:47  0.00B 定义构建参数
ARG HPCX_VERSION=2.22.1
                        
# 2025-04-11 09:18:47  0.00B 定义构建参数
ARG GDRCOPY_VERSION=2.4.1
                        
# 2025-04-11 09:18:47  311.13MB 执行命令并创建新的镜像层
RUN |1 JETPACK_HOST_MOUNTS= /bin/sh -c export DEBIAN_FRONTEND=noninteractive  && apt-get update  && apt-get install -y --no-install-recommends         apt-utils         build-essential         ca-certificates         curl         libncurses6         libncursesw6         patch         wget         unzip         jq         gnupg         libtcmalloc-minimal4  && rm -rf /var/lib/apt/lists/*  && echo "hsts=0" > /root/.wgetrc # buildkit
                        
# 2025-04-11 09:18:30  0.00B 执行命令并创建新的镜像层
RUN |1 JETPACK_HOST_MOUNTS= /bin/sh -c if [ -n "${JETPACK_HOST_MOUNTS}" ]; then        echo "/usr/lib/aarch64-linux-gnu/tegra" > /etc/ld.so.conf.d/nvidia-tegra.conf     && echo "/usr/lib/aarch64-linux-gnu/tegra-egl" >> /etc/ld.so.conf.d/nvidia-tegra.conf;     fi # buildkit
                        
# 2025-04-11 09:18:30  0.00B 设置环境变量 NVIDIA_REQUIRE_JETPACK_HOST_MOUNTS
ENV NVIDIA_REQUIRE_JETPACK_HOST_MOUNTS=
                        
# 2025-04-11 09:18:30  0.00B 定义构建参数
ARG JETPACK_HOST_MOUNTS=
                        
# 2025-04-08 18:43:15  0.00B 
/bin/sh -c #(nop)  CMD ["/bin/bash"]
                        
# 2025-04-08 18:43:14  78.10MB 
/bin/sh -c #(nop) ADD file:1d7c45546e94b90e941c5bf5c7a5d415d7b868581ad96171d4beb76caa8ab683 in / 
                        
# 2025-04-08 18:43:12  0.00B 
/bin/sh -c #(nop)  LABEL org.opencontainers.image.version=24.04
                        
# 2025-04-08 18:43:12  0.00B 
/bin/sh -c #(nop)  LABEL org.opencontainers.image.ref.name=ubuntu
                        
# 2025-04-08 18:43:12  0.00B 
/bin/sh -c #(nop)  ARG LAUNCHPAD_BUILD_ARCH
                        
# 2025-04-08 18:43:12  0.00B 
/bin/sh -c #(nop)  ARG RELEASE
                        
                    

镜像信息

{
    "Id": "sha256:43e6802c38a508fb7fb61b2733b7617550d221d03f97e0f6ebc8fc858dafc467",
    "RepoTags": [
        "nvcr.io/nvidia/pytorch:25.04-py3",
        "swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nvcr.io/nvidia/pytorch:25.04-py3"
    ],
    "RepoDigests": [
        "nvcr.io/nvidia/pytorch@sha256:d1eac6220dd98ef5870b1a76673cfb6f84451135a6d8a174cb92258a6bf4576d",
        "swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nvcr.io/nvidia/pytorch@sha256:d5a91770e89c3cd8ca7af7f4851de52c7098edd712716b64b3c0521af919ad1a"
    ],
    "Parent": "",
    "Comment": "buildkit.dockerfile.v0",
    "Created": "2025-04-15T20:00:55.643606662Z",
    "Container": "",
    "ContainerConfig": null,
    "DockerVersion": "",
    "Author": "",
    "Config": {
        "Hostname": "",
        "Domainname": "",
        "User": "",
        "AttachStdin": false,
        "AttachStdout": false,
        "AttachStderr": false,
        "ExposedPorts": {
            "6006/tcp": {},
            "8888/tcp": {}
        },
        "Tty": false,
        "OpenStdin": false,
        "StdinOnce": false,
        "Env": [
            "PATH=/usr/local/lib/python3.12/dist-packages/torch_tensorrt/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/mpi/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/ucx/bin:/opt/amazon/efa/bin:/opt/tensorrt/bin",
            "NVIDIA_REQUIRE_JETPACK_HOST_MOUNTS=",
            "GDRCOPY_VERSION=2.4.1",
            "HPCX_VERSION=2.22.1",
            "MOFED_VERSION=5.4-rdmacore50.0",
            "OPENUCX_VERSION=1.18.0",
            "OPENMPI_VERSION=4.1.7",
            "RDMACORE_VERSION=50.0",
            "EFA_VERSION=1.38.1",
            "AWS_OFI_NCCL_VERSION=1.14.0",
            "OPAL_PREFIX=/opt/hpcx/ompi",
            "OMPI_MCA_coll_hcoll_enable=0",
            "CUDA_VERSION=12.9.0.036",
            "CUDA_DRIVER_VERSION=575.51.02",
            "_CUDA_COMPAT_PATH=/usr/local/cuda/compat",
            "ENV=/etc/shinit_v2",
            "BASH_ENV=/etc/bash.bashrc",
            "SHELL=/bin/bash",
            "NVIDIA_REQUIRE_CUDA=cuda\u003e=9.0",
            "NCCL_VERSION=2.26.3",
            "CUBLAS_VERSION=12.9.0.2",
            "CUFFT_VERSION=11.4.0.6",
            "CURAND_VERSION=10.3.10.19",
            "CUSPARSE_VERSION=12.5.9.5",
            "CUSPARSELT_VERSION=0.7.1.0",
            "CUSOLVER_VERSION=11.7.4.40",
            "NPP_VERSION=12.4.0.27",
            "NVJPEG_VERSION=12.4.0.16",
            "CUFILE_VERSION=1.14.0.30",
            "NVJITLINK_VERSION=12.9.41",
            "CUBLASMP_VERSION=0.4.0.789",
            "CAL_VERSION=0.4.4.50",
            "NVSHMEM_VERSION=3.2.5",
            "CUDNN_VERSION=9.9.0.52",
            "CUDNN_FRONTEND_VERSION=1.11.0",
            "TRT_VERSION=10.9.0.34+cuda12.8",
            "TRTOSS_VERSION=",
            "NSIGHT_SYSTEMS_VERSION=2025.2.1.130",
            "NSIGHT_COMPUTE_VERSION=2025.2.0.11",
            "DALI_VERSION=1.48.0",
            "DALI_BUILD=",
            "DALI_URL_SUFFIX=120",
            "POLYGRAPHY_VERSION=0.49.20",
            "TRANSFORMER_ENGINE_VERSION=2.2",
            "MODEL_OPT_VERSION=0.25.0",
            "LD_LIBRARY_PATH=/usr/local/lib/python3.12/dist-packages/torch/lib:/usr/local/lib/python3.12/dist-packages/torch_tensorrt/lib:/usr/local/cuda/compat/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64",
            "NVIDIA_VISIBLE_DEVICES=all",
            "NVIDIA_DRIVER_CAPABILITIES=compute,utility,video",
            "NVIDIA_PRODUCT_NAME=PyTorch",
            "LIBRARY_PATH=/usr/local/cuda/lib64/stubs:",
            "PYTORCH_BUILD_VERSION=2.7.0a0+79aa174",
            "PYTORCH_VERSION=2.7.0a0+79aa174",
            "PYTORCH_BUILD_NUMBER=0",
            "NVIDIA_PYTORCH_VERSION=25.04",
            "NVFUSER_BUILD_VERSION=5111d3b",
            "NVFUSER_VERSION=5111d3b",
            "PIP_BREAK_SYSTEM_PACKAGES=1",
            "PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python",
            "PIP_CONSTRAINT=/etc/pip/constraint.txt",
            "NVPL_LAPACK_MATH_MODE=PEDANTIC",
            "PYTHONIOENCODING=utf-8",
            "LC_ALL=C.UTF-8",
            "PIP_DEFAULT_TIMEOUT=100",
            "JUPYTER_PORT=8888",
            "TENSORBOARD_PORT=6006",
            "UCC_CL_BASIC_TLS=^sharp",
            "TORCH_CUDA_ARCH_LIST=7.5 8.0 8.6 9.0 10.0 12.0+PTX",
            "PYTORCH_HOME=/opt/pytorch/pytorch",
            "CUDA_HOME=/usr/local/cuda",
            "TORCH_ALLOW_TF32_CUBLAS_OVERRIDE=1",
            "COCOAPI_VERSION=2.0+nv0.8.1",
            "CUDA_MODULE_LOADING=LAZY",
            "TORCH_NCCL_USE_COMM_NONBLOCKING=0",
            "NVIDIA_BUILD_ID=159049541"
        ],
        "Cmd": null,
        "Image": "",
        "Volumes": null,
        "WorkingDir": "/workspace",
        "Entrypoint": [
            "/opt/nvidia/nvidia_entrypoint.sh"
        ],
        "OnBuild": null,
        "Labels": {
            "com.nvidia.build.id": "159049541",
            "com.nvidia.build.ref": "8d28f2ff75a3f186220e187654c5890a49f8d87a",
            "com.nvidia.cal.version": "0.4.4.50",
            "com.nvidia.cublas.version": "12.9.0.2",
            "com.nvidia.cublasmp.version": "0.4.0.789",
            "com.nvidia.cuda.version": "9.0",
            "com.nvidia.cudnn.version": "9.9.0.52",
            "com.nvidia.cufft.version": "11.4.0.6",
            "com.nvidia.curand.version": "10.3.10.19",
            "com.nvidia.cusolver.version": "11.7.4.40",
            "com.nvidia.cusparse.version": "12.5.9.5",
            "com.nvidia.cusparselt.version": "0.7.1.0",
            "com.nvidia.nccl.version": "2.26.3",
            "com.nvidia.npp.version": "12.4.0.27",
            "com.nvidia.nsightcompute.version": "2025.2.0.11",
            "com.nvidia.nsightsystems.version": "2025.2.1.130",
            "com.nvidia.nvjpeg.version": "12.4.0.16",
            "com.nvidia.pytorch.version": "2.7.0a0+79aa174",
            "com.nvidia.tensorrt.version": "10.9.0.34+cuda12.8",
            "com.nvidia.tensorrtoss.version": "",
            "com.nvidia.volumes.needed": "nvidia_driver",
            "org.opencontainers.image.ref.name": "ubuntu",
            "org.opencontainers.image.version": "24.04"
        }
    },
    "Architecture": "amd64",
    "Os": "linux",
    "Size": 24659996553,
    "GraphDriver": {
        "Data": {
            "LowerDir": "/var/lib/docker/overlay2/2dc7b10afec8ecfbd2940c9f5757a7dbf85c26374e85c17c8f24ebc10d97c133/diff:/var/lib/docker/overlay2/c4bb78da0768ef9e9fd2d1f2c5ad47ed19883384a25c025944d639af78dc9300/diff:/var/lib/docker/overlay2/eea3a255cfc3189b114d6a84fa4153a35a73ceccc1fc48ffaa0b6046114c4b82/diff:/var/lib/docker/overlay2/5981e6267152149cbd58cb6c036006587d9f76cda3f9129ff17506fc8bf6c6f6/diff:/var/lib/docker/overlay2/6d770e907e86b4fad0a7a26b876c37899bcde6cac0a9e697241fcdd3300ab751/diff:/var/lib/docker/overlay2/2c433b92152ac172ec5782d097b5a3cce3dc75db7a020475f76d4c87624fc156/diff:/var/lib/docker/overlay2/c59c37ff5459a0271b91ec39deed0aec3f7c049a9e90ebb6dc588bd2557e5a5f/diff:/var/lib/docker/overlay2/e7a349fbf1fde180696a83311f021ab9891f9fd3d8d9bd947a814749d13d4607/diff:/var/lib/docker/overlay2/60ac418124880d8a11ab15130dbfcc24ba92f6f1e02717ca2eb0074062883d1d/diff:/var/lib/docker/overlay2/04fd44884ac97b5d6b959aca019a4f24914145ba504768c36d808de6ed9000e2/diff:/var/lib/docker/overlay2/b56f6d3d02bdddf9f94f544cd716a93759aea0ac4ed4513fdc3f4504c9d5a98c/diff:/var/lib/docker/overlay2/2bacfa9d8759ff438274a3081c00ca2aa6ca951060e5ccad95636f3905797451/diff:/var/lib/docker/overlay2/c778ee6ae4e0a8c468984bd6b3742d9e59485455c8710095416a2db4e5f08ec3/diff:/var/lib/docker/overlay2/b5691c54b8814cc69f2e6918ccaf137ad5d6e96f53798011ba00c9377499f8c4/diff:/var/lib/docker/overlay2/75e7180be83871a377c4e323958d20e904ce12a5003a568e635e71c8b71a2bdc/diff:/var/lib/docker/overlay2/914991648b9b4e02b9927c99a4737f9c3c086870496f48e713409082337e1529/diff:/var/lib/docker/overlay2/96332e20887404dcd6d969cd18df0aad92f77970b165e38cbe1739c0171a08fb/diff:/var/lib/docker/overlay2/ba0b60bfa9079aa0c9478c30784ff55db93c53a723bd6d85acaa1919212093fe/diff:/var/lib/docker/overlay2/ec307b9db5c8f0350e4ea2a30b35c6726a468126a649db20c8972f39deefd81b/diff:/var/lib/docker/overlay2/cfecac7160f5a165822b43781d63546e007b57d0d8850a79cb7da4f14f86565b/diff:/var/lib/docker/overlay2/03a0ce31d252963f10e26aa40532b7469cdf02e50db33fe8e8651cdb99f96cb3/diff:/var/lib/docker/overlay2/12239f16d3dbe4877f0fdca1f10f7b80b9137a55b4fd54d39e54715ff4791184/diff:/var/lib/docker/overlay2/4ba131eb0af71b4eb17148091d0151e2e8a8a7ac85d8b0cd9f7459049bfaf15d/diff:/var/lib/docker/overlay2/c7592faf0db3d9056c2b92f717c13a86b43287b156e61f850695c85a43b66d17/diff:/var/lib/docker/overlay2/65448a846ac07b7094113c40766ceaa9016b4139d81a50aba083f0df2502b268/diff:/var/lib/docker/overlay2/784e6e69eaa8e7513f768ad801a6d5bd688d6e1e070e651f095775131175d596/diff:/var/lib/docker/overlay2/330fa96fec426bad24d6461ad9c517b3bc4141598248b0cae8ce7c216a86bba4/diff:/var/lib/docker/overlay2/7e8dd75e17d687a26ef1bb908e166ce92431712e10d4e9ce68ab0a528149a48c/diff:/var/lib/docker/overlay2/902285ede49f8d6a507553ca3151abb16a33b0e51c9f3ca27b105dcd7b5c599d/diff:/var/lib/docker/overlay2/887072d580c9373b03cf76af485da980d1046d88ec008f92d3d0eb126bc8a11b/diff:/var/lib/docker/overlay2/2b1004a8a18c63c32bc5d6f41a41161c8c7d687bfd399061f56b0347f3a6cded/diff:/var/lib/docker/overlay2/982ccbf327831fde275575524b538bf869db369e7247c6b19fb9a54d81a80b78/diff:/var/lib/docker/overlay2/692181d155c31c9bc151a561101bc898a27a7c9670e948091c4562605c9a5c4e/diff:/var/lib/docker/overlay2/7cad3f720c7932ae2184c3f69432ed05ce1d5eabe4f7b41d325d7062db2882cb/diff:/var/lib/docker/overlay2/cdd5b5694ea4fc5d29b61817019a3e0c910b0917d6cb33ed56d19f70f106587c/diff:/var/lib/docker/overlay2/d1be3a32db6cb93b5fd3034cbdb7db666d41b5aed9e0e22eab37b1bb186f2318/diff:/var/lib/docker/overlay2/5cf408d13c90f8103e81b6eb961b66f1b71054a2946a6837c3a7960c82889c34/diff:/var/lib/docker/overlay2/b19a9743354b5b4d23effa359a1b532b8eba8dca605b9c1f1fb985bb4efcb08d/diff:/var/lib/docker/overlay2/c439acb43a8bd00774ec8fe22f3e41dbf054a3add09283b2067bcc4127dc654e/diff:/var/lib/docker/overlay2/39e4ab7b947d83f32b718e7553a6e446faaab93d211c2d2a90bde53b8f941fc1/diff:/var/lib/docker/overlay2/8a39e2abaed0f47d0095356109190e357705911ab8820186fc3115d7d1feb50f/diff:/var/lib/docker/overlay2/00a66cb9ddf36e46ec4a40590f96df7011704f1975fde34409036b12d1eb9f34/diff:/var/lib/docker/overlay2/eb0a2eaffdbed81d5feced318e5507e88f5c5d86e2ce36b758ba13cacd76d928/diff:/var/lib/docker/overlay2/aeedbbc4f784951af5d62eabd4b4c1fdef4a038e33cffacc9c49b6a9bd77de58/diff:/var/lib/docker/overlay2/63473892ebd4094726941e8da3c65ef33035eb2ecf10a2d857aa2867c444df2e/diff:/var/lib/docker/overlay2/fc71b13a4a8e532249a1b4d92c45301d78e57838501da076048173665cfd4b9f/diff:/var/lib/docker/overlay2/53fa6ae6b7d8b7e53b0e4a613abf34899f1d3715125caea55ed737c2fab5cc3a/diff:/var/lib/docker/overlay2/e8113c56c1163deb894f025e037b14b278868167e7c9fb6aca29289ec7017825/diff:/var/lib/docker/overlay2/2530abea1b3f448c7c30fbeb5903c41a1a1b4dd33649b45a4b56a4c6ffbc2005/diff:/var/lib/docker/overlay2/cb1cef907f6e4fec6023bfa53aa552714aa85c7cbb532355cb7b0a97a6c531f8/diff:/var/lib/docker/overlay2/ae350a49d57a4197d4e5eb37e245ad77921a0fcdd3cc6364ba88e8cc1eb4f398/diff:/var/lib/docker/overlay2/8be08009e8aa8de6b2cbf1b7c3db86b7b3a779eb4e0e66230836d1dcf86067fc/diff:/var/lib/docker/overlay2/30b6124f60eb589b3cf9c612305f154655fb24ce49cae82ba38b5be722d3f5c8/diff:/var/lib/docker/overlay2/1d4563e3440f47064e3581090e3d1ea35a08d592408f1403a7e5d089d4892f27/diff:/var/lib/docker/overlay2/43d81cc155bec2024767885718c58219be9fe230079721ef54d96539abb7243c/diff:/var/lib/docker/overlay2/8fbe0ff47b5a5c2b3a97201930e47043877891a5f43c75625b5a7b42d4e31d3c/diff:/var/lib/docker/overlay2/37dd72425c7bbd98d39850a72a9d336309b4a64564dfee1918062d3ebdea9a36/diff:/var/lib/docker/overlay2/a210d775633d00f9523ef98517ac3a9539a42da9eaa99a649477dd85bf338560/diff:/var/lib/docker/overlay2/f23a1cdf06173275190cfca961d7e802ae9a90408b13813179708b9baf149a2c/diff:/var/lib/docker/overlay2/697096b4c822b101843182ff505291800d91c80f1ac5c99f2b9cab5e17ecccf2/diff",
            "MergedDir": "/var/lib/docker/overlay2/bf8051fa90726cfff6757cd349fc452b95e37891ae50766b2fedd207028d5a04/merged",
            "UpperDir": "/var/lib/docker/overlay2/bf8051fa90726cfff6757cd349fc452b95e37891ae50766b2fedd207028d5a04/diff",
            "WorkDir": "/var/lib/docker/overlay2/bf8051fa90726cfff6757cd349fc452b95e37891ae50766b2fedd207028d5a04/work"
        },
        "Name": "overlay2"
    },
    "RootFS": {
        "Type": "layers",
        "Layers": [
            "sha256:3abdd8a5e7a8909e1509f1d36dcc8b85a0f95c68a69e6d86c6e9e3c1059d44b3",
            "sha256:5f70bf18a086007016e948b04aed3b82103a36bea41755b6cddfaf10ace3c6ef",
            "sha256:56b48a64c1a89635c37cc8eee09f44dfdd1b0bffb178c7c6e684b5602230dc86",
            "sha256:51095d499b316211c41771ac0086d35be15ddb88e250ffc16c472317f7186592",
            "sha256:382f0aacfa3721bb8e87165e2adb98f5986881bebfd195c8a39ab90b56dd923a",
            "sha256:0c5897de4ba5c763c7e50e3a44f16f87a36e6672290cfab474eb27cd313b39c6",
            "sha256:383dc5aac9d7a3d6dd11b9da9733258cc739f0b2e7fccc1fab120eaf5e04f205",
            "sha256:4ffee5b339a82e809699254d6393839780f9c85d54f2e67bbdacaf40ca3a879e",
            "sha256:9f2c7f673b63c3a31155f340149224e92b466afeb5fee5f0be73548bf803f01e",
            "sha256:6b5e4b206c8b3d4b99f76bf751d9bf52108a496529ebf673d5083023a8dea26d",
            "sha256:38566b056d73e56f9339fd3dae54d29b26713ab07773d022d807f35b5fe3a398",
            "sha256:f4bcfdcad5ed7fdcabb6fa7f3839922cda7a295b9f03fe7c0df00535631bf0ca",
            "sha256:0879c5d84b48fcfd1e9de1636ce3b171b9bd86a4a0772f5305cfe02e2781b00c",
            "sha256:bf3c7891de9351c7abd4db9910444bc818063088aff357a3033efc3c8b2a2786",
            "sha256:dd87c33ba4b2c61e7164cce127f51144776ceec66be37e2ee05926dbb20aee57",
            "sha256:ee5507ec4a0e87d3f11fc56363c27db42d182871b5355f8b7fa12e61ee679c8e",
            "sha256:c0839cc98f8ee2a7d6d4d14cc52304a583890ec1ef06fa84bca982540bd63da0",
            "sha256:1b0484c7dcf9c31d02851140a11794cb62bdf45786f0cea47152b95416cfb651",
            "sha256:1059ab92dd7a0b12ec17164c2d68b608a4cab390856b77fae2d96e3fd1f1cc30",
            "sha256:555f36725d3291c18852931a52371968a132c9980dca7213fb16c1402e47bfa6",
            "sha256:d8c017a76b718dcb6b19c3f633997df9d018fcc09b1e8e0ded7ec0f3e6c12443",
            "sha256:5f70bf18a086007016e948b04aed3b82103a36bea41755b6cddfaf10ace3c6ef",
            "sha256:4938cfac8a2af88eae05757240dfaf278ea8cf12b54d1e294928729585b09f3d",
            "sha256:c67463220d8c885fbfa57dfb6dab9f66611354a5806b79f9e8aa5cf01a4ec928",
            "sha256:74ca84b6395bada5910d679dd76fe5dbfd994e998f711773f1bb83b49610744f",
            "sha256:fde33d36e0859b7bc4f65e5de0c27f7254c3617cae49445e99569a3d6436d8cc",
            "sha256:4dc6fe7e074a2f285fe09057103531cb8ee12825967dd4314cd1bfdd15cb93c3",
            "sha256:5f70bf18a086007016e948b04aed3b82103a36bea41755b6cddfaf10ace3c6ef",
            "sha256:9ce504d40726085fafa997ff86c75227a964cbce99497a0b77c155b9369af0cd",
            "sha256:b1763683d65bd1f27e3edc5d73cc2f8d8476b25c723b780829ee1eaedf8bfe86",
            "sha256:4d640f594f78fd37adb59f3605e92724d364cf5d4a279ba20fb53166cbc74076",
            "sha256:abbfd999dece53040ce01add69c0522a7f703c43fa136ae5df23bd08c93129ad",
            "sha256:abaa388b13b2bdb0b6cc64e4ce2783e52d0f6f99b7e46477d75dec3f5dbc9b4c",
            "sha256:9232c92ab60047b9e56e1e3d2297c29764451394192cedbe8a9f5b4dc9320e03",
            "sha256:131e3797c16ad79fd12955c9426a5e8bdb6b64c90f770c8d7c926b75b7857a34",
            "sha256:421a6c513b814d49b874a780dee9c9a403126a1c53fe0f5068d7fb2ed43cf8e3",
            "sha256:7516e684c6924d8d57a66a7bedbaf5c84310ee96320889677134e804e021daad",
            "sha256:5f70bf18a086007016e948b04aed3b82103a36bea41755b6cddfaf10ace3c6ef",
            "sha256:80e2749574d9b8aab90eac6e86905f8cd535ecb7cb21074702692b7240fb3759",
            "sha256:1c7c7e89f220f164c1a6b0ebbd2892ea5603fd7775aa24360a3f6b3850e61366",
            "sha256:0053d1c71cdfd45daf6e3aabcf7a3cc2b67f719427f22d55cb22ab88e29546ed",
            "sha256:ecbde83791c47e1992831cb0cd599b93e5a90feb71a03d101c1f7448695a8100",
            "sha256:613a35f5e8929d681db16e01e4288084eb11a1432148bb5013d7f1dfac890f22",
            "sha256:ee76170687441c33ee3bfcfd6c676cdf66dc81a650db5ca2b9d9f680c5b43d00",
            "sha256:b4e9f7682933dc844a6fdc24eca0429aebcb40da1693066aaf3c3499b23c6872",
            "sha256:ed2ad40bb27b894c80c77025b05dc89d4bcb3eeb1da501c47b2e8f9175044efc",
            "sha256:92be216706c1a7e102149d04e033110603fd46db11cc3f63c993ad751aa295cb",
            "sha256:5f70bf18a086007016e948b04aed3b82103a36bea41755b6cddfaf10ace3c6ef",
            "sha256:dfbdd7f45272e50209b18055783986911d121dd26af5a7af76606803f1a7e423",
            "sha256:c5db39889e25b6534cb601bfb62b9b61b4dc9d4234824879fa14f94bc3d26865",
            "sha256:b4db18bfc01141b1ce92ea84f09eadc8c29d34d7b2a2928544ed383afa7e6d32",
            "sha256:13dbe77fa8323e3fa3bcccdacb7008949e08c1889ba986ab9542687f5b68b17d",
            "sha256:59a7300cf78129f4b83c22e0c30c55a9ed32e2b6e4ae167a7e48fa57a06e3ccc",
            "sha256:0e79b98380dbd45a32486b4bf0d9f0ef819b43535b8a7b43d43634e3b25bb4a7",
            "sha256:111f1d5ae1aebd2435a4739a985aae5df0151f6d52c920b2d7f55acb26791c1c",
            "sha256:55155d209e4bb4c0c75673ab104611f3d1d8d59f3e21240432cee5edf6930e01",
            "sha256:6b5fa5e87eaf81d7ea0fa9890ba8b4ec45a4928a8aa07e8dfa635b464d554503",
            "sha256:f910a624018f255939359408b47ff346c681b843960ea3fa1ecbc59c48d233fc",
            "sha256:bcd1cec34cc5f942025ff7fe14a684fe2ff44e4e11c7808c5a600d996d550a1a",
            "sha256:8e231390b57da9a1b4246541253c3205fef87960d006a05cfc777b0a3b15d1a2",
            "sha256:9c1c084d67b623c82d23c7a946102c2271b4c511db24ed23be67cf221e322ab9"
        ]
    },
    "Metadata": {
        "LastTagTime": "2025-05-23T01:00:59.273762196+08:00"
    }
}