docker.io/nvcr.io/nvidia/pytorch:25.04-py3 linux/arm64

docker.io/nvcr.io/nvidia/pytorch:25.04-py3 - 国内下载镜像源 浏览次数:47 温馨提示: 这是一个 linux/arm64 系统架构镜像
这里是镜像的描述信息: NVIDIA PyTorch Docker Image

这是一个基于PyTorch框架的Docker容器镜像,提供了一个完整的深度学习环境。该镜像包含了PyTorch 1.x版本,以及其他必需的依赖包,如CUDA、cuDNN等。

使用这个镜像,您可以轻松地在本地环境中搭建一个深度学习工作站,进行各种机器学习和计算机视觉任务的实验和开发。

此外,该镜像还支持GPU加速,通过NVIDIA的CUDA和cuDNN技术,可以显著提高PyTorch的性能和效率。

源镜像 docker.io/nvcr.io/nvidia/pytorch:25.04-py3
国内镜像 swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nvcr.io/nvidia/pytorch:25.04-py3-linuxarm64
镜像ID sha256:7854310c53f83bdca49319813a0d1bba973c93a97849fa8ea3f26fc408d6133b
镜像TAG 25.04-py3-linuxarm64
大小 22.42GB
镜像源 docker.io
项目信息 Docker-Hub主页 🚀项目TAG 🚀
CMD
启动入口 /opt/nvidia/nvidia_entrypoint.sh
工作目录 /workspace
OS/平台 linux/arm64
浏览量 47 次
贡献者 71******3@qq.com
镜像创建 2025-04-16T00:15:13.212553708Z
同步时间 2025-06-04 07:57
更新时间 2025-06-07 01:02
开放端口
6006/tcp 8888/tcp
环境变量
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>=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=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=159049542
镜像标签
159049542: com.nvidia.build.id 8d28f2ff75a3f186220e187654c5890a49f8d87a: com.nvidia.build.ref 0.4.4.50: com.nvidia.cal.version 12.9.0.2: com.nvidia.cublas.version 0.4.0.789: com.nvidia.cublasmp.version 9.0: com.nvidia.cuda.version 9.9.0.52: com.nvidia.cudnn.version 11.4.0.6: com.nvidia.cufft.version 10.3.10.19: com.nvidia.curand.version 11.7.4.40: com.nvidia.cusolver.version 12.5.9.5: com.nvidia.cusparse.version 0.7.1.0: com.nvidia.cusparselt.version 2.26.3: com.nvidia.nccl.version 12.4.0.27: com.nvidia.npp.version 2025.2.0.11: com.nvidia.nsightcompute.version 2025.2.1.130: com.nvidia.nsightsystems.version 12.4.0.16: com.nvidia.nvjpeg.version 2.7.0a0+79aa174: com.nvidia.pytorch.version 10.9.0.34+cuda12.8: com.nvidia.tensorrt.version : com.nvidia.tensorrtoss.version nvidia_driver: com.nvidia.volumes.needed ubuntu: org.opencontainers.image.ref.name 24.04: org.opencontainers.image.version

Docker拉取命令

docker pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nvcr.io/nvidia/pytorch:25.04-py3-linuxarm64
docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nvcr.io/nvidia/pytorch:25.04-py3-linuxarm64  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-linuxarm64
ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nvcr.io/nvidia/pytorch:25.04-py3-linuxarm64  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-linuxarm64#' 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-linuxarm64 && docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nvcr.io/nvidia/pytorch:25.04-py3-linuxarm64  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-linuxarm64 && ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nvcr.io/nvidia/pytorch:25.04-py3-linuxarm64  docker.io/nvcr.io/nvidia/pytorch:25.04-py3'

镜像构建历史


# 2025-04-16 08:15:13  0.00B 添加元数据标签
LABEL com.nvidia.build.ref=8d28f2ff75a3f186220e187654c5890a49f8d87a
                        
# 2025-04-16 08:15:13  0.00B 定义构建参数
ARG NVIDIA_BUILD_REF=8d28f2ff75a3f186220e187654c5890a49f8d87a
                        
# 2025-04-16 08:15:13  0.00B 添加元数据标签
LABEL com.nvidia.build.id=159049542
                        
# 2025-04-16 08:15:13  0.00B 设置环境变量 NVIDIA_BUILD_ID
ENV NVIDIA_BUILD_ID=159049542
                        
# 2025-04-16 08:15:13  0.00B 定义构建参数
ARG NVIDIA_BUILD_ID=159049542
                        
# 2025-04-16 08:15:13  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 08:15:13  77.27KB 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=arm64 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 08:15:13  0.00B 设置环境变量 TORCH_NCCL_USE_COMM_NONBLOCKING
ENV TORCH_NCCL_USE_COMM_NONBLOCKING=0
                        
# 2025-04-16 08:15:13  0.00B 设置环境变量 CUDA_MODULE_LOADING
ENV CUDA_MODULE_LOADING=LAZY
                        
# 2025-04-16 08:15:13  802.19MB 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=arm64 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 08:09:19  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=arm64 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 07:42:52  45.31MB 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=arm64 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 07:42:51  589.54MB 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=arm64 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 07:23:19  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 07:23:19  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 07:23:19  0.00B 定义构建参数
ARG PYVER=3.12
                        
# 2025-04-16 07:23:19  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 07:23:18  55.68MB 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=arm64 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 07:23:13  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 07:23:13  7.25MB 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=arm64 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 07:22:23  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=arm64 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 07:22:22  34.89MB 复制新文件或目录到容器中
COPY tutorials tutorials # buildkit
                        
# 2025-04-16 07:22:22  2.07KB 复制新文件或目录到容器中
COPY docker-examples docker-examples # buildkit
                        
# 2025-04-16 07:22:22  2.05KB 复制新文件或目录到容器中
COPY NVREADME.md README.md # buildkit
                        
# 2025-04-16 07:22:22  0.00B 设置工作目录为/workspace
WORKDIR /workspace
                        
# 2025-04-16 07:22:22  2.59GB 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=arm64 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 07:21:57  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=arm64 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 07:21:56  168.57MB 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=arm64 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 07:15:34  2.21KB 复制新文件或目录到容器中
COPY singularity/ /.singularity.d/ # buildkit
                        
# 2025-04-16 07:15:34  69.33MB 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=arm64 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 07:15:17  0.00B 设置环境变量 COCOAPI_VERSION
ENV COCOAPI_VERSION=2.0+nv0.8.1
                        
# 2025-04-16 07:15:17  688.03MB 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=arm64 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 07:15:04  0.00B 定义构建参数
ARG DALI_EXTRA_INDEX_URL=http://sqrl/nvdl/datasets/dali/pip-dali
                        
# 2025-04-16 07:15:04  688.07MB 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=arm64 PYVER=3.12 PYVER_MAJMIN=312 L4T=0 /bin/sh -c pip install --no-cache-dir /tmp/dist/*.whl # buildkit
                        
# 2025-04-16 07:14:51  7.54MB 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=arm64 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 07:14:50  13.90MB 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=arm64 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 07:14:50  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 07:14:50  11.68MB 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 07:14:50  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 07:14:50  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 07:14:50  2.06GB 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=arm64 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 07:14:28  0.00B 设置环境变量 TORCH_ALLOW_TF32_CUBLAS_OVERRIDE
ENV TORCH_ALLOW_TF32_CUBLAS_OVERRIDE=1
                        
# 2025-04-16 07:14:28  0.00B 设置环境变量 CUDA_HOME
ENV CUDA_HOME=/usr/local/cuda
                        
# 2025-04-16 07:14:28  0.00B 设置环境变量 PYTORCH_HOME
ENV PYTORCH_HOME=/opt/pytorch/pytorch
                        
# 2025-04-16 07:14:28  0.00B 设置环境变量 TORCH_CUDA_ARCH_LIST
ENV TORCH_CUDA_ARCH_LIST=8.0 8.6 9.0 10.0 12.0+PTX
                        
# 2025-04-16 07:14:28  0.00B 设置环境变量 UCC_CL_BASIC_TLS
ENV UCC_CL_BASIC_TLS=^sharp
                        
# 2025-04-16 07:14:28  58.63MB 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=arm64 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 07:11:57  0.00B 声明容器运行时监听的端口
EXPOSE map[6006/tcp:{}]
                        
# 2025-04-16 07:11:57  0.00B 声明容器运行时监听的端口
EXPOSE map[8888/tcp:{}]
                        
# 2025-04-16 07:11:57  0.00B 设置环境变量 TENSORBOARD_PORT
ENV TENSORBOARD_PORT=6006
                        
# 2025-04-16 07:11:57  0.00B 设置环境变量 JUPYTER_PORT
ENV JUPYTER_PORT=8888
                        
# 2025-04-16 07:11:57  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 07:11:57  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 07:11:57  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 07:11:57  9.46MB 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=arm64 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 07:11:22  0.00B 设置工作目录为/opt/pytorch
WORKDIR /opt/pytorch
                        
# 2025-04-16 07:11:22  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=arm64 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 07:11:22  230.60MB 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=arm64 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 07:11:12  560.69MB 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=arm64 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 07:10:50  0.00B 设置环境变量 PIP_DEFAULT_TIMEOUT
ENV PIP_DEFAULT_TIMEOUT=100
                        
# 2025-04-16 07:10:50  0.00B 设置环境变量 LC_ALL
ENV LC_ALL=C.UTF-8
                        
# 2025-04-16 07:10:50  0.00B 设置环境变量 PYTHONIOENCODING
ENV PYTHONIOENCODING=utf-8
                        
# 2025-04-16 07:10:50  1.46GB 复制新文件或目录到容器中
COPY . . # buildkit
                        
# 2025-04-16 07:10:41  0.00B 设置工作目录为/opt/pytorch
WORKDIR /opt/pytorch
                        
# 2025-04-16 07:10:41  0.00B 设置环境变量 NVPL_LAPACK_MATH_MODE
ENV NVPL_LAPACK_MATH_MODE=PEDANTIC
                        
# 2025-04-16 07:10:41  30.12MB 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=arm64 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 07:10:41  39.88MB 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=arm64 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 07:10:40  71.95MB 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=arm64 PYVER=3.12 PYVER_MAJMIN=312 L4T=0 /bin/sh -c pip install pip setuptools &&     pip install cmake # buildkit
                        
# 2025-04-16 07:10:38  5.74KB 复制新文件或目录到容器中
COPY constraint.txt /etc/pip/constraint.txt # buildkit
                        
# 2025-04-16 07:10:38  0.00B 设置环境变量 PIP_CONSTRAINT
ENV PIP_CONSTRAINT=/etc/pip/constraint.txt
                        
# 2025-04-16 07:10:38  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=arm64 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 07:10:35  0.00B 设置环境变量 PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION
ENV PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python
                        
# 2025-04-16 07:10:35  210.07MB 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=arm64 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 07:10:35  0.00B 定义构建参数
ARG L4T=0
                        
# 2025-04-16 07:10:35  0.00B 设置环境变量 PIP_BREAK_SYSTEM_PACKAGES
ENV PIP_BREAK_SYSTEM_PACKAGES=1
                        
# 2025-04-16 07:10:35  0.00B 定义构建参数
ARG PYVER_MAJMIN=312
                        
# 2025-04-16 07:10:35  0.00B 定义构建参数
ARG PYVER=3.12
                        
# 2025-04-16 07:10:35  0.00B 定义构建参数
ARG TARGETARCH=arm64
                        
# 2025-04-16 07:10:35  0.00B 添加元数据标签
LABEL com.nvidia.pytorch.version=2.7.0a0+79aa174
                        
# 2025-04-16 07:10:35  0.00B 设置环境变量 NVFUSER_BUILD_VERSION NVFUSER_VERSION
ENV NVFUSER_BUILD_VERSION=5111d3b NVFUSER_VERSION=5111d3b
                        
# 2025-04-16 07:10:35  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 07:10:35  0.00B 定义构建参数
ARG NVFUSER_BUILD_VERSION=5111d3b
                        
# 2025-04-16 07:10:35  0.00B 定义构建参数
ARG PYTORCH_BUILD_VERSION=2.7.0a0+79aa174
                        
# 2025-04-16 07:10:35  0.00B 定义构建参数
ARG NVIDIA_PYTORCH_VERSION=25.04
                        
# 2025-04-16 07:10:35  0.00B 设置环境变量 NVIDIA_PRODUCT_NAME
ENV NVIDIA_PRODUCT_NAME=PyTorch
                        
# 2025-04-16 00:58:16  0.00B 设置环境变量 LIBRARY_PATH
ENV LIBRARY_PATH=/usr/local/cuda/lib64/stubs:
                        
# 2025-04-16 00:58:16  1.38GB 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 00:55:58  1.49KB 复制新文件或目录到容器中
COPY cuda-*.patch /tmp # buildkit
                        
# 2025-04-16 00:55:58  101.90MB 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 00:49:27  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=arm64 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 00:49:27  0.00B 配置容器启动时运行的命令
ENTRYPOINT ["/opt/nvidia/nvidia_entrypoint.sh"]
                        
# 2025-04-16 00:49:27  0.00B 设置环境变量 NVIDIA_PRODUCT_NAME
ENV NVIDIA_PRODUCT_NAME=CUDA
                        
# 2025-04-16 00:49:27  16.04KB 复制新文件或目录到容器中
COPY entrypoint/ /opt/nvidia/ # buildkit
                        
# 2025-04-16 00:49:27  32.42KB 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=arm64 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 00:49:27  5.12MB 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 00:47:55  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 00:47:55  0.00B 定义构建参数
ARG _LIBPATH_SUFFIX=
                        
# 2025-04-16 00:47:55  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=arm64 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 00:47:54  13.39KB 复制文件或目录到容器中
ADD docs.tgz / # buildkit
                        
# 2025-04-16 00:47:54  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 00:47:54  0.00B 定义构建参数
ARG MODEL_OPT_VERSION=0.25.0
                        
# 2025-04-16 00:47:54  0.00B 定义构建参数
ARG TRANSFORMER_ENGINE_VERSION=2.2
                        
# 2025-04-16 00:47:54  0.00B 定义构建参数
ARG POLYGRAPHY_VERSION=0.49.20
                        
# 2025-04-16 00:47:54  0.00B 定义构建参数
ARG DALI_URL_SUFFIX=120
                        
# 2025-04-16 00:47:54  0.00B 定义构建参数
ARG DALI_BUILD=
                        
# 2025-04-16 00:47:54  0.00B 定义构建参数
ARG DALI_VERSION=1.48.0
                        
# 2025-04-16 00:47:54  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 00:47:54  7.42GB 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=arm64 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  53.22KB 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=arm64 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  715.05MB 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=arm64 CUDA_VERSION=12.9.0.036 CUDA_DRIVER_VERSION=575.51.02 /bin/sh -c /nvidia/build-scripts/installCUDA.sh # buildkit
                        
# 2025-04-11 09:19:13  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 09:19:13  0.00B 定义构建参数
ARG CUDA_DRIVER_VERSION=575.51.02
                        
# 2025-04-11 09:19:13  0.00B 定义构建参数
ARG CUDA_VERSION=12.9.0.036
                        
# 2025-04-11 09:19:13  0.00B 设置环境变量 OMPI_MCA_coll_hcoll_enable
ENV OMPI_MCA_coll_hcoll_enable=0
                        
# 2025-04-11 09:19:13  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 09:19:13  236.89MB 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=arm64 /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 09:19:01  0.00B 定义构建参数
ARG TARGETARCH=arm64
                        
# 2025-04-11 09:19:01  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 09:19:01  0.00B 定义构建参数
ARG AWS_OFI_NCCL_VERSION=1.14.0
                        
# 2025-04-11 09:19:01  0.00B 定义构建参数
ARG EFA_VERSION=1.38.1
                        
# 2025-04-11 09:19:01  0.00B 定义构建参数
ARG OPENMPI_VERSION=4.1.7
                        
# 2025-04-11 09:19:01  0.00B 定义构建参数
ARG OPENUCX_VERSION=1.18.0
                        
# 2025-04-11 09:19:01  0.00B 定义构建参数
ARG MOFED_VERSION=5.4-rdmacore50.0
                        
# 2025-04-11 09:19:01  0.00B 定义构建参数
ARG RDMACORE_VERSION=50.0
                        
# 2025-04-11 09:19:01  0.00B 定义构建参数
ARG HPCX_VERSION=2.22.1
                        
# 2025-04-11 09:19:01  0.00B 定义构建参数
ARG GDRCOPY_VERSION=2.4.1
                        
# 2025-04-11 09:19:01  300.63MB 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 09:18:29  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 09:18:29  0.00B 设置环境变量 NVIDIA_REQUIRE_JETPACK_HOST_MOUNTS
ENV NVIDIA_REQUIRE_JETPACK_HOST_MOUNTS=
                        
# 2025-04-11 09:18:29  0.00B 定义构建参数
ARG JETPACK_HOST_MOUNTS=
                        
# 2025-04-08 18:46:13  0.00B 
/bin/sh -c #(nop)  CMD ["/bin/bash"]
                        
# 2025-04-08 18:46:12  100.64MB 
/bin/sh -c #(nop) ADD file:918b7712da52a62e47b028978dd5fc952b2f7f7f0507ea2362c4ccd14120133c in / 
                        
# 2025-04-08 18:46:09  0.00B 
/bin/sh -c #(nop)  LABEL org.opencontainers.image.version=24.04
                        
# 2025-04-08 18:46:09  0.00B 
/bin/sh -c #(nop)  LABEL org.opencontainers.image.ref.name=ubuntu
                        
# 2025-04-08 18:46:09  0.00B 
/bin/sh -c #(nop)  ARG LAUNCHPAD_BUILD_ARCH
                        
# 2025-04-08 18:46:09  0.00B 
/bin/sh -c #(nop)  ARG RELEASE
                        
                    

镜像信息

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    "RepoTags": [
        "nvcr.io/nvidia/pytorch:25.04-py3",
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    "RepoDigests": [
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        "swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nvcr.io/nvidia/pytorch@sha256:69620b55f71932842e39270ea229ed7db30f6c5a50a88c6cce8c072d61a3bdd2"
    ],
    "Parent": "",
    "Comment": "buildkit.dockerfile.v0",
    "Created": "2025-04-16T00:15:13.212553708Z",
    "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=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=159049542"
        ],
        "Cmd": null,
        "Image": "",
        "Volumes": null,
        "WorkingDir": "/workspace",
        "Entrypoint": [
            "/opt/nvidia/nvidia_entrypoint.sh"
        ],
        "OnBuild": null,
        "Labels": {
            "com.nvidia.build.id": "159049542",
            "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",
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}

更多版本

docker.io/nvcr.io/nvidia/pytorch:24.01-py3

linux/amd64 docker.io22.02GB2024-09-20 00:38
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