Docker拉取命令

docker pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/hi20240217/pub:bevfusion_inference
docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/hi20240217/pub:bevfusion_inference  docker.io/hi20240217/pub:bevfusion_inference

Containerd拉取命令

ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/hi20240217/pub:bevfusion_inference
ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/hi20240217/pub:bevfusion_inference  docker.io/hi20240217/pub:bevfusion_inference

Shell快速替换命令

sed -i 's#hi20240217/pub:bevfusion_inference#swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/hi20240217/pub:bevfusion_inference#' 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/hi20240217/pub:bevfusion_inference && docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/hi20240217/pub:bevfusion_inference  docker.io/hi20240217/pub:bevfusion_inference'

Ansible快速分发-Containerd

#ansible k8s -m shell -a 'ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/hi20240217/pub:bevfusion_inference && ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/hi20240217/pub:bevfusion_inference  docker.io/hi20240217/pub:bevfusion_inference'

镜像构建历史

# 2026-05-07 19:20:23  569.80KB 
/bin/bash
                        
# 2026-05-06 15:17:10  102.14MB 
/bin/bash
                        
# 2026-04-29 14:56:37  122.46KB 
/bin/bash
                        
# 2026-04-29 14:26:04  82.95MB 
/bin/bash
                        
# 2026-04-29 12:46:56  1.81GB 
/bin/bash
                        
# 2022-12-15 11:12:41  0.00B 添加元数据标签
LABEL com.nvidia.build.ref=a58f3f606e2d7f2b5a9a59e7b305e0966e5e3d34
                        
# 2022-12-15 11:12:41  0.00B 定义构建参数
ARG NVIDIA_BUILD_REF
                        
# 2022-12-15 11:12:41  0.00B 添加元数据标签
LABEL com.nvidia.build.id=49968248
                        
# 2022-12-15 11:12:41  0.00B 设置环境变量 NVIDIA_BUILD_ID
ENV NVIDIA_BUILD_ID=49968248
                        
# 2022-12-15 11:12:41  0.00B 定义构建参数
ARG NVIDIA_BUILD_ID
                        
# 2022-12-15 11:12:41  720.00B 复制新文件或目录到容器中
COPY entrypoint.d/ /opt/nvidia/entrypoint.d/ # buildkit
                        
# 2022-12-15 11:12:41  71.97KB 执行命令并创建新的镜像层
RUN |1 PYVER=3.8 /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
                        
# 2022-12-15 11:12:38  0.00B 设置环境变量 CUDA_MODULE_LOADING
ENV CUDA_MODULE_LOADING=LAZY
                        
# 2022-12-15 11:12:38  0.00B 设置环境变量 TORCH_CUDNN_V8_API_ENABLED
ENV TORCH_CUDNN_V8_API_ENABLED=1
                        
# 2022-12-15 11:12:38  134.57MB 执行命令并创建新的镜像层
RUN |1 PYVER=3.8 /bin/sh -c pip install --upgrade git+https://github.com/NVIDIA/TransformerEngine.git@release_v${TRANSFORMER_ENGINE_VERSION} # buildkit
                        
# 2022-12-15 11:01:29  0.00B 设置环境变量 PATH
ENV PATH=/usr/local/lib/python3.8/dist-packages/torch_tensorrt/bin:/usr/local/mpi/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/ucx/bin:/opt/tensorrt/bin
                        
# 2022-12-15 11:01:29  0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/lib/python3.8/dist-packages/torch/lib:/usr/local/lib/python3.8/dist-packages/torch_tensorrt/lib:/usr/local/cuda/compat/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64
                        
# 2022-12-15 11:01:29  50.74MB 执行命令并创建新的镜像层
RUN |1 PYVER=3.8 /bin/sh -c pip install --no-cache-dir /opt/pytorch/torch_tensorrt/py/dist/*.whl # buildkit
                        
# 2022-12-15 10:55:48  0.00B 定义构建参数
ARG PYVER
                        
# 2022-12-15 10:55:48  120.42MB 复制新文件或目录到容器中
COPY torch_tensorrt/ /opt/pytorch/torch_tensorrt/ # buildkit
                        
# 2022-12-15 10:55:33  14.96MB 执行命令并创建新的镜像层
RUN |4 NVIDIA_PYTORCH_VERSION=22.12 PYTORCH_BUILD_VERSION=1.14.0a0+410ce96 TARGETARCH=amd64 PYVER=3.8 /bin/sh -c pip --version && python -c 'import sys; print(sys.platform)'     && pip install --no-cache-dir nvidia-pyindex     && pip install --extra-index-url https://urm.nvidia.com/artifactory/api/pypi/sw-tensorrt-pypi/simple --no-cache-dir polygraphy==${POLYGRAPHY_VERSION}     && if [[ $TARGETARCH = "amd64" ]] ; then pip install --extra-index-url http://sqrl/dldata/pip-simple --trusted-host sqrl --no-cache-dir pytorch-quantization==2.1.2; fi # buildkit
                        
# 2022-12-15 10:55:15  0.00B 设置环境变量 PATH
ENV PATH=/usr/local/mpi/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/ucx/bin:/opt/tensorrt/bin
                        
# 2022-12-15 10:55:15  4.84MB 执行命令并创建新的镜像层
RUN |4 NVIDIA_PYTORCH_VERSION=22.12 PYTORCH_BUILD_VERSION=1.14.0a0+410ce96 TARGETARCH=amd64 PYVER=3.8 /bin/sh -c set -x  && URL=$(VERIFY=1 /nvidia/build-scripts/installTRT.sh | sed -n "s/^.*\(http.*\)tar.*$/\1/p")tar  && FILE=$(wget -O - $URL | sed -n 's/^.*href="\(TensorRT[^"]*\)".*$/\1/p' | grep -v internal)  && wget $URL/$FILE -O - | tar -xz  && PY=$(python -c 'import sys; print(str(sys.version_info[0])+str(sys.version_info[1]))')  && pip install TensorRT-*/python/tensorrt-*-cp$PY*.whl  && pip install TensorRT-*/graphsurgeon/graphsurgeon-*.whl  && pip install TensorRT-*/uff/uff-*.whl  && mv /usr/src/tensorrt /opt  && ln -s /opt/tensorrt /usr/src/tensorrt  && rm -r TensorRT-*  && UFF_PATH=$(pip show uff | sed -n 's/Location: \(.*\)$/\1/p')/uff  && sed -i 's/from tensorflow import GraphDef/from tensorflow.python import GraphDef/'     $UFF_PATH/converters/tensorflow/conversion_helpers.py  && chmod +x ${UFF_PATH}/bin/convert_to_uff.py  && ln -sf ${UFF_PATH}/bin/convert_to_uff.py /usr/local/bin/convert-to-uff # buildkit
                        
# 2022-12-15 10:54:19  51.00MB 执行命令并创建新的镜像层
RUN |4 NVIDIA_PYTORCH_VERSION=22.12 PYTORCH_BUILD_VERSION=1.14.0a0+410ce96 TARGETARCH=amd64 PYVER=3.8 /bin/sh -c chmod -R a+w . # buildkit
                        
# 2022-12-15 10:54:18  34.89MB 复制新文件或目录到容器中
COPY tutorials tutorials # buildkit
                        
# 2022-12-15 10:54:15  15.96MB 复制新文件或目录到容器中
COPY examples examples # buildkit
                        
# 2022-12-15 10:54:14  1.78KB 复制新文件或目录到容器中
COPY docker-examples docker-examples # buildkit
                        
# 2022-12-15 10:54:13  2.06KB 复制新文件或目录到容器中
COPY NVREADME.md README.md # buildkit
                        
# 2022-12-15 10:54:13  0.00B 设置工作目录为/workspace
WORKDIR /workspace
                        
# 2022-12-15 10:54:13  3.13GB 执行命令并创建新的镜像层
RUN |4 NVIDIA_PYTORCH_VERSION=22.12 PYTORCH_BUILD_VERSION=1.14.0a0+410ce96 TARGETARCH=amd64 PYVER=3.8 /bin/sh -c export LD_LIBRARY_PATH="${LD_LIBRARY_PATH:+$LD_LIBRARY_PATH:}$CUDA_HOME/lib:$CUDA_HOME/lib64"  && tar --exclude="*.a" -C /usr --strip-components=1 -xf /rapids/RAFT-*.tar.gz  && tar --exclude="*.a" -C /usr --strip-components=1 -xf /rapids/RMM-*.tar.gz  && tar --exclude="*.a" -C /usr --strip-components=1 -xf /rapids/CUMLPRIMS_MG-*.tar.gz  && tar --exclude="*.a" -C /usr --strip-components=1 -xf /rapids/CUML-*.tar.gz  && tar --exclude="*.a" -C /usr --strip-components=1 -xf /rapids/CUGRAPH-*.tar.gz  && tar --exclude="*.a" -C /usr --strip-components=1 -xf /rapids/CUGRAPH_OPS-*.tar.gz  && tar --exclude="*.a" -C /usr --strip-components=1 -xf /rapids/CUDF-*.tar.gz  && tar --exclude="*.a" --exclude="bin/xgboost" -C /usr --strip-components=1 -xf /rapids/xgboost-*.tar.gz  && CPATH="${CPATH}:/usr/local/cuda-${CUDA_VERSION%.*.*}/targets/sbsa-linux/include/" pip install --no-cache-dir         /rapids/cuda_python-*.whl         /rapids/cupy_cuda*.whl         /rapids/dask-*.whl         /rapids/distributed*.whl         /rapids/dask_cuda*.whl         /rapids/treelite*         /rapids/scikit_learn*.whl         /rapids/rmm*.whl         /rapids/pyarrow-*.whl         /rapids/ucx_py-*.whl         /rapids/cuml-*.whl         /rapids/cugraph-*.whl         /rapids/cudf-*.whl         /rapids/dask_cudf-*.whl         /rapids/pylibraft-*.whl         /rapids/raft_dask-*.whl         /rapids/xgboost-*.whl         /rapids/pylibcugraph-*.whl         networkx==2.6.3 && rm $(pip show xgboost | grep Location | awk '{print $2}')/xgboost/lib/libxgboost.so # buildkit
                        
# 2022-12-15 10:52:46  4.63MB 执行命令并创建新的镜像层
RUN |4 NVIDIA_PYTORCH_VERSION=22.12 PYTORCH_BUILD_VERSION=1.14.0a0+410ce96 TARGETARCH=amd64 PYVER=3.8 /bin/sh -c pip uninstall -y pillow  && cd /tmp  && git clone https://github.com/uploadcare/pillow-simd  && cd pillow-simd  && git fetch --all --tags --prune  && git checkout tags/9.2.0  && sed -i 's/DEBUG = False/DEBUG = True/' setup.py  && patch -p1 < /opt/pytorch/pil_9.3.0_CVE-2022-45199.patch  && if [[ $TARGETARCH = "amd64" ]] ; then CC="cc -mavx" pip install --no-cache-dir --disable-pip-version-check  . ; fi  && if [[ $TARGETARCH = "arm64" ]] ; then pip install --no-cache-dir --disable-pip-version-check  . ; fi  && rm -rf ../pillow-simd # buildkit
                        
# 2022-12-15 10:52:05  49.45KB 执行命令并创建新的镜像层
RUN |4 NVIDIA_PYTORCH_VERSION=22.12 PYTORCH_BUILD_VERSION=1.14.0a0+410ce96 TARGETARCH=amd64 PYVER=3.8 /bin/sh -c patch -d / -p1 < /opt/pytorch/mpmath_CVE-2021-29063.patch # buildkit
                        
# 2022-12-15 10:52:05  342.16MB 执行命令并创建新的镜像层
RUN |4 NVIDIA_PYTORCH_VERSION=22.12 PYTORCH_BUILD_VERSION=1.14.0a0+410ce96 TARGETARCH=amd64 PYVER=3.8 /bin/sh -c ( cd vision && CFLAGS="-g0" FORCE_CUDA=1 pip install --no-cache-dir --no-build-isolation --disable-pip-version-check . )  && ( cd vision && cmake -Bbuild -H. -GNinja -DWITH_CUDA=1 -DCMAKE_PREFIX_PATH=`python -c 'import torch;print(torch.utils.cmake_prefix_path)'` && cmake --build build --target install && rm -rf build )  && ( cd apex && CFLAGS="-g0" pip install --no-cache-dir --disable-pip-version-check --global-option="--cpp_ext" --global-option="--cuda_ext" --global-option="--bnp" --global-option="--xentropy" --global-option="--deprecated_fused_adam" --global-option="--deprecated_fused_lamb" --global-option="--fast_multihead_attn" --global-option="--distributed_lamb" --global-option="--fast_layer_norm" --global-option="--transducer" --global-option="--distributed_adam" --global-option="--fmha" --global-option="--fast_bottleneck" --global-option="--nccl_p2p" --global-option="--peer_memory" --global-option="--permutation_search" --global-option="--focal_loss" --global-option="--fused_conv_bias_relu" --global-option="--index_mul_2d" --global-option="--cudnn_gbn" . )  && ( pip install --no-cache-dir --disable-pip-version-check git+https://github.com/pytorch/text@fae8e8cabf )  && ( cd pytorch/third_party/onnx && pip uninstall typing -y && CMAKE_ARGS="-DONNX_USE_PROTOBUF_SHARED_LIBS=ON" pip install --no-cache-dir --disable-pip-version-check . ) # buildkit
                        
# 2022-12-15 09:55:24  2.21KB 复制新文件或目录到容器中
COPY singularity/ /.singularity.d/ # buildkit
                        
# 2022-12-15 09:55:24  62.40MB 执行命令并创建新的镜像层
RUN |4 NVIDIA_PYTORCH_VERSION=22.12 PYTORCH_BUILD_VERSION=1.14.0a0+410ce96 TARGETARCH=amd64 PYVER=3.8 /bin/sh -c export COCOAPI_TAG=$(echo ${COCOAPI_VERSION} | sed 's/^.*+n//')  && pip install --disable-pip-version-check --no-cache-dir git+https://github.com/nvidia/cocoapi.git@${COCOAPI_TAG}#subdirectory=PythonAPI # buildkit
                        
# 2022-12-15 09:54:46  0.00B 设置环境变量 COCOAPI_VERSION
ENV COCOAPI_VERSION=2.0+nv0.7.1
                        
# 2022-12-15 09:54:46  869.05MB 执行命令并创建新的镜像层
RUN |4 NVIDIA_PYTORCH_VERSION=22.12 PYTORCH_BUILD_VERSION=1.14.0a0+410ce96 TARGETARCH=amd64 PYVER=3.8 /bin/sh -c pip install --disable-pip-version-check --no-cache-dir                 --extra-index-url https://developer.download.nvidia.com/compute/redist                 --extra-index-url http://sqrl/dldata/pip-dali  --trusted-host sqrl         nvidia-dali-cuda110==${DALI_VERSION} # buildkit
                        
# 2022-12-15 09:54:25  1.50GB 执行命令并创建新的镜像层
RUN |4 NVIDIA_PYTORCH_VERSION=22.12 PYTORCH_BUILD_VERSION=1.14.0a0+410ce96 TARGETARCH=amd64 PYVER=3.8 /bin/sh -c cd pytorch &&     USE_CUPTI_SO=1     USE_KINETO=1     CMAKE_PREFIX_PATH="/usr/local"     NCCL_ROOT="/usr"     NCCL_INCLUDE_DIR="/usr/include/"     NCCL_LIB_DIR="/usr/lib/"     USE_SYSTEM_NCCL=1     CFLAGS='-fno-gnu-unique'     DEFAULT_INTEL_MKL_DIR="/usr/local"     INTEL_MKL_DIR="/usr/local"     python setup.py install     && python setup.py clean # buildkit
                        
# 2022-12-15 08:17:33  0.00B 设置环境变量 USE_EXPERIMENTAL_CUDNN_V8_API
ENV USE_EXPERIMENTAL_CUDNN_V8_API=1
                        
# 2022-12-15 08:17:33  0.00B 设置环境变量 TORCH_ALLOW_TF32_CUBLAS_OVERRIDE
ENV TORCH_ALLOW_TF32_CUBLAS_OVERRIDE=1
                        
# 2022-12-15 08:17:33  0.00B 设置环境变量 PYTORCH_HOME
ENV PYTORCH_HOME=/opt/pytorch/pytorch
                        
# 2022-12-15 08:17:33  0.00B 设置环境变量 CUDA_HOME
ENV CUDA_HOME=/usr/local/cuda
                        
# 2022-12-15 08:17:33  0.00B 设置环境变量 TORCH_CUDA_ARCH_LIST
ENV TORCH_CUDA_ARCH_LIST=5.2 6.0 6.1 7.0 7.5 8.0 8.6 9.0+PTX
                        
# 2022-12-15 08:17:33  259.77MB 执行命令并创建新的镜像层
RUN |4 NVIDIA_PYTORCH_VERSION=22.12 PYTORCH_BUILD_VERSION=1.14.0a0+410ce96 TARGETARCH=amd64 PYVER=3.8 /bin/sh -c cd magma-cuda &&     cmake -H. -Bbuild -DUSE_FORTRAN=OFF -DGPU_TARGET="All" -DBUILD_SHARED_LIBS=OFF -DCMAKE_CXX_FLAGS="-fPIC" -DCMAKE_C_FLAGS="-fPIC" -DCUDA_NVCC_FLAGS="-Xfatbin;-compress-all;-DHAVE_CUBLAS;-std=c++11;--threads=0;" -GNinja &&     cmake --build build --target install &&     rm -r ./build # buildkit
                        
# 2022-12-15 08:05:07  51.75MB 执行命令并创建新的镜像层
RUN |4 NVIDIA_PYTORCH_VERSION=22.12 PYTORCH_BUILD_VERSION=1.14.0a0+410ce96 TARGETARCH=amd64 PYVER=3.8 /bin/sh -c OPENCV_VERSION=4.6.0 &&     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${PYVER}/dist-packages"           -DBUILD_opencv_cudalegacy=OFF -DBUILD_opencv_stitching=OFF -DWITH_IPP=OFF -DWITH_PROTOBUF=OFF &&     cmake --build build --target install &&     cd modules/python/package &&     pip install --no-cache-dir --disable-pip-version-check -v . &&     rm -rf /opencv-${OPENCV_VERSION} # buildkit
                        
# 2022-12-15 07:59:26  0.00B 声明容器运行时监听的端口
EXPOSE map[6006/tcp:{}]
                        
# 2022-12-15 07:59:26  0.00B 声明容器运行时监听的端口
EXPOSE map[8888/tcp:{}]
                        
# 2022-12-15 07:59:26  0.00B 设置环境变量 TENSORBOARD_PORT
ENV TENSORBOARD_PORT=6006
                        
# 2022-12-15 07:59:26  0.00B 设置环境变量 JUPYTER_PORT
ENV JUPYTER_PORT=8888
                        
# 2022-12-15 07:59:26  427.00B 复制新文件或目录到容器中
COPY jupyter_notebook_config.py /usr/local/etc/jupyter/ # buildkit
                        
# 2022-12-15 07:59:26  157.25MB 执行命令并创建新的镜像层
RUN |4 NVIDIA_PYTORCH_VERSION=22.12 PYTORCH_BUILD_VERSION=1.14.0a0+410ce96 TARGETARCH=amd64 PYVER=3.8 /bin/sh -c pip install --disable-pip-version-check --no-cache-dir git+https://github.com/cliffwoolley/jupyter_tensorboard.git@0.2.0+nv21.03  && mkdir -p $NVM_DIR  && curl -Lo- https://raw.githubusercontent.com/nvm-sh/nvm/v0.38.0/install.sh | bash  && source "$NVM_DIR/nvm.sh"  && nvm install 16.15.1 node  && jupyter labextension install jupyterlab_tensorboard  && jupyter serverextension enable jupyterlab  && pip install --no-cache-dir jupytext  && jupyter labextension install jupyterlab-jupytext@1.2.2  && ( cd /usr/local/share/jupyter/lab/staging       && npm prune --production )  && npm cache clean --force  && rm -rf /usr/local/share/.cache  && echo "source $NVM_DIR/nvm.sh" >> /etc/bash.bashrc  && mv /root/.jupyter/jupyter_notebook_config.json /usr/local/etc/jupyter/  && jupyter lab clean # buildkit
                        
# 2022-12-15 07:56:00  0.00B 设置环境变量 NVM_DIR
ENV NVM_DIR=/usr/local/nvm
                        
# 2022-12-15 07:56:00  27.51KB 执行命令并创建新的镜像层
RUN |4 NVIDIA_PYTORCH_VERSION=22.12 PYTORCH_BUILD_VERSION=1.14.0a0+410ce96 TARGETARCH=amd64 PYVER=3.8 /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
                        
# 2022-12-15 07:55:59  169.85MB 执行命令并创建新的镜像层
RUN |4 NVIDIA_PYTORCH_VERSION=22.12 PYTORCH_BUILD_VERSION=1.14.0a0+410ce96 TARGETARCH=amd64 PYVER=3.8 /bin/sh -c git config --global url."https://github".insteadOf git://github &&     pip install --no-cache-dir notebook==6.4.10 jupyterlab==2.3.2 python-hostlist &&     pip install --no-cache-dir tensorboard==2.9.0 # buildkit
                        
# 2022-12-15 07:55:27  3.15GB 执行命令并创建新的镜像层
RUN |4 NVIDIA_PYTORCH_VERSION=22.12 PYTORCH_BUILD_VERSION=1.14.0a0+410ce96 TARGETARCH=amd64 PYVER=3.8 /bin/sh -c pip install --no-cache-dir         numpy==1.22.2         scipy==1.6.3         PyYAML>=5.4.1         astunparse         typing_extensions         cffi         spacy         mock         tqdm         librosa==0.9.2         expecttest==0.1.3         hypothesis==5.35.1         xdoctest==1.0.2         pytest         pytest-xdist         pytest-rerunfailures         pytest-shard         pybind11         Cython         regex>=2020.1.8         protobuf==3.20.1 &&     if [[ $TARGETARCH = "amd64" ]] ; then pip install --no-cache-dir mkl==2021.1.1 mkl-include==2021.1.1 mkl-devel==2021.1.1 ; fi # buildkit
                        
# 2022-12-15 07:53:53  0.00B 设置环境变量 PIP_DEFAULT_TIMEOUT
ENV PIP_DEFAULT_TIMEOUT=100
                        
# 2022-12-15 07:53:53  0.00B 设置环境变量 LC_ALL
ENV LC_ALL=C.UTF-8
                        
# 2022-12-15 07:53:53  0.00B 设置环境变量 PYTHONIOENCODING
ENV PYTHONIOENCODING=utf-8
                        
# 2022-12-15 07:53:53  1.00GB 复制新文件或目录到容器中
COPY . . # buildkit
                        
# 2022-12-15 07:53:42  0.00B 设置工作目录为/opt/pytorch
WORKDIR /opt/pytorch
                        
# 2022-12-15 07:53:42  46.30MB 执行命令并创建新的镜像层
RUN |4 NVIDIA_PYTORCH_VERSION=22.12 PYTORCH_BUILD_VERSION=1.14.0a0+410ce96 TARGETARCH=amd64 PYVER=3.8 /bin/sh -c wget -q -O - https://github.com/xianyi/OpenBLAS/archive/refs/tags/v${OPENBLAS_VERSION}.tar.gz | tar -xzf - &&     cd OpenBLAS-${OPENBLAS_VERSION} &&     time make FC=gfortran USE_OPENMP=1 -j &&     time make PREFIX=/usr/local install &&     cd ../ &&     rm -rf OpenBLAS-${OPENBLAS_VERSION} # buildkit
                        
# 2022-12-15 07:51:51  0.00B 设置环境变量 OPENBLAS_VERSION
ENV OPENBLAS_VERSION=0.3.20
                        
# 2022-12-15 07:51:51  0.00B 设置工作目录为/opt
WORKDIR /opt
                        
# 2022-12-15 07:51:51  68.73MB 执行命令并创建新的镜像层
RUN |4 NVIDIA_PYTORCH_VERSION=22.12 PYTORCH_BUILD_VERSION=1.14.0a0+410ce96 TARGETARCH=amd64 PYVER=3.8 /bin/sh -c pip install --no-cache-dir pip==21.2.4 setuptools==59.5.0 &&     pip install --no-cache-dir cmake==3.24.1.1 # buildkit
                        
# 2022-12-15 07:51:39  21.68MB 执行命令并创建新的镜像层
RUN |4 NVIDIA_PYTORCH_VERSION=22.12 PYTORCH_BUILD_VERSION=1.14.0a0+410ce96 TARGETARCH=amd64 PYVER=3.8 /bin/sh -c curl -O https://bootstrap.pypa.io/get-pip.py &&     python get-pip.py &&     rm get-pip.py # buildkit
                        
# 2022-12-15 07:51:31  182.06MB 执行命令并创建新的镜像层
RUN |4 NVIDIA_PYTORCH_VERSION=22.12 PYTORCH_BUILD_VERSION=1.14.0a0+410ce96 TARGETARCH=amd64 PYVER=3.8 /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$PYSFX-distutils         python-is-python$PYSFX         autoconf         automake         libatlas-base-dev         libgoogle-glog-dev         libbz2-dev         libleveldb-dev         liblmdb-dev         libprotobuf-dev         libsnappy-dev         libtool         nasm         protobuf-compiler         pkg-config         unzip         sox         libsndfile1         libpng-dev         libhdf5-103         libhdf5-dev         gfortran         rapidjson-dev         ninja-build         libedit-dev         build-essential      && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2022-12-15 07:51:31  0.00B 设置环境变量 PYVER
ENV PYVER=3.8
                        
# 2022-12-15 07:51:31  0.00B 定义构建参数
ARG PYVER=3.8
                        
# 2022-12-15 07:51:31  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2022-12-15 07:51:31  0.00B 添加元数据标签
LABEL com.nvidia.pytorch.version=1.14.0a0+410ce96
                        
# 2022-12-15 07:51:31  0.00B 设置环境变量 PYTORCH_BUILD_VERSION PYTORCH_VERSION PYTORCH_BUILD_NUMBER NVIDIA_PYTORCH_VERSION
ENV PYTORCH_BUILD_VERSION=1.14.0a0+410ce96 PYTORCH_VERSION=1.14.0a0+410ce96 PYTORCH_BUILD_NUMBER=0 NVIDIA_PYTORCH_VERSION=22.12
                        
# 2022-12-15 07:51:31  0.00B 定义构建参数
ARG PYTORCH_BUILD_VERSION
                        
# 2022-12-15 07:51:31  0.00B 定义构建参数
ARG NVIDIA_PYTORCH_VERSION
                        
# 2022-12-15 07:51:31  0.00B 设置环境变量 NVIDIA_PRODUCT_NAME
ENV NVIDIA_PRODUCT_NAME=PyTorch
                        
# 2022-12-15 06:49:06  0.00B 执行命令并创建新的镜像层
RUN |7 GDRCOPY_VERSION=2.3 HPCX_VERSION=2.13 RDMACORE_VERSION=36.0 MOFED_VERSION=5.4-rdmacore36.0 OPENUCX_VERSION=1.14.0 OPENMPI_VERSION=4.1.4 TARGETARCH=amd64 /bin/sh -c if [[ "$CUDA_VERSION" == "11.2.1.007" && $(dpkg --print-architecture) == "amd64" ]]; then wget http://sqrl.nvidia.com/dldata/sgodithi/bug3254800/cicc >/dev/null 2>&1 && cp cicc /usr/local/cuda/nvvm/bin/. ; fi # buildkit
                        
# 2022-12-15 06:49:05  0.00B 设置环境变量 LIBRARY_PATH
ENV LIBRARY_PATH=/usr/local/cuda/lib64/stubs:
                        
# 2022-12-15 06:49:05  1.02GB 执行命令并创建新的镜像层
RUN |7 GDRCOPY_VERSION=2.3 HPCX_VERSION=2.13 RDMACORE_VERSION=36.0 MOFED_VERSION=5.4-rdmacore36.0 OPENUCX_VERSION=1.14.0 OPENMPI_VERSION=4.1.4 TARGETARCH=amd64 /bin/sh -c export DEVEL=1 BASE=0  && /nvidia/build-scripts/installNCU.sh  && /nvidia/build-scripts/installCUDA.sh  && /nvidia/build-scripts/installLIBS.sh  && /nvidia/build-scripts/installNCCL.sh  && /nvidia/build-scripts/installCUDNN.sh  && /nvidia/build-scripts/installCUTENSOR.sh  && /nvidia/build-scripts/installTRT.sh  && /nvidia/build-scripts/installNSYS.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
                        
# 2022-12-15 06:43:30  1.49KB 复制新文件或目录到容器中
COPY cuda-*.patch /tmp # buildkit
                        
# 2022-12-15 06:43:30  0.00B 设置环境变量 OMPI_MCA_coll_hcoll_enable
ENV OMPI_MCA_coll_hcoll_enable=0
                        
# 2022-12-15 06:43:30  0.00B 设置环境变量 OPAL_PREFIX PATH
ENV OPAL_PREFIX=/opt/hpcx/ompi PATH=/usr/local/mpi/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/ucx/bin
                        
# 2022-12-15 06:43:30  241.70MB 执行命令并创建新的镜像层
RUN |7 GDRCOPY_VERSION=2.3 HPCX_VERSION=2.13 RDMACORE_VERSION=36.0 MOFED_VERSION=5.4-rdmacore36.0 OPENUCX_VERSION=1.14.0 OPENMPI_VERSION=4.1.4 TARGETARCH=amd64 /bin/sh -c cd /nvidia  && ( cd opt/rdma-core/                             && dpkg -i libibverbs1_*.deb                            libibverbs-dev_*.deb                         librdmacm1_*.deb                             librdmacm-dev_*.deb                          libibumad3_*.deb                             libibumad-dev_*.deb                          ibverbs-utils_*.deb                          ibverbs-providers_*.deb           && 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       )                                                         && ldconfig # buildkit
                        
# 2022-12-15 06:43:30  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2022-12-15 06:43:30  0.00B 设置环境变量 GDRCOPY_VERSION HPCX_VERSION MOFED_VERSION OPENUCX_VERSION OPENMPI_VERSION RDMACORE_VERSION
ENV GDRCOPY_VERSION=2.3 HPCX_VERSION=2.13 MOFED_VERSION=5.4-rdmacore36.0 OPENUCX_VERSION=1.14.0 OPENMPI_VERSION=4.1.4 RDMACORE_VERSION=36.0
                        
# 2022-12-15 06:43:30  0.00B 定义构建参数
ARG OPENMPI_VERSION
                        
# 2022-12-15 06:43:30  0.00B 定义构建参数
ARG OPENUCX_VERSION
                        
# 2022-12-15 06:43:30  0.00B 定义构建参数
ARG MOFED_VERSION=5.4-rdmacore36.0
                        
# 2022-12-15 06:43:30  0.00B 定义构建参数
ARG RDMACORE_VERSION
                        
# 2022-12-15 06:43:30  0.00B 定义构建参数
ARG HPCX_VERSION
                        
# 2022-12-15 06:43:30  0.00B 定义构建参数
ARG GDRCOPY_VERSION
                        
# 2022-12-15 06:43:27  102.34MB 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         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
                        
# 2022-12-15 06:30:51  148.72KB 复制新文件或目录到容器中
COPY NVIDIA_Deep_Learning_Container_License.pdf /workspace/ # buildkit
                        
# 2022-12-15 06:30:51  0.00B 配置容器启动时运行的命令
ENTRYPOINT ["/opt/nvidia/nvidia_entrypoint.sh"]
                        
# 2022-12-15 06:30:51  0.00B 设置环境变量 NVIDIA_PRODUCT_NAME
ENV NVIDIA_PRODUCT_NAME=CUDA
                        
# 2022-12-15 06:30:51  12.46KB 复制新文件或目录到容器中
COPY entrypoint/ /opt/nvidia/ # buildkit
                        
# 2022-12-15 06:30:50  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/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/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
                        
# 2022-12-15 06:30:50  46.00B 执行命令并创建新的镜像层
RUN |21 CUDA_VERSION=11.8.0.065 CUDA_DRIVER_VERSION=520.61.05 JETPACK_HOST_MOUNTS= NCCL_VERSION=2.15.5 CUBLAS_VERSION=11.11.3.6 CUFFT_VERSION=10.9.0.58 CURAND_VERSION=10.3.0.86 CUSPARSE_VERSION=11.7.5.86 CUSOLVER_VERSION=11.4.1.48 CUTENSOR_VERSION=1.6.1.5 NPP_VERSION=11.8.0.86 NVJPEG_VERSION=11.9.0.86 CUDNN_VERSION=8.7.0.84 TRT_VERSION=8.5.1.7 TRTOSS_VERSION=22.12 NSIGHT_SYSTEMS_VERSION=2022.4.2.1 NSIGHT_COMPUTE_VERSION=2022.3.0.22 DALI_VERSION=1.20.0 DALI_BUILD=6562491 POLYGRAPHY_VERSION=0.43.1 TRANSFORMER_ENGINE_VERSION=0.3 /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
                        
# 2022-12-15 06:30:50  13.39KB 复制文件或目录到容器中
ADD docs.tgz / # buildkit
                        
# 2022-12-15 06:30:50  0.00B 设置环境变量 DALI_VERSION DALI_BUILD POLYGRAPHY_VERSION TRANSFORMER_ENGINE_VERSION
ENV DALI_VERSION=1.20.0 DALI_BUILD=6562491 POLYGRAPHY_VERSION=0.43.1 TRANSFORMER_ENGINE_VERSION=0.3
                        
# 2022-12-15 06:30:50  0.00B 定义构建参数
ARG TRANSFORMER_ENGINE_VERSION
                        
# 2022-12-15 06:30:50  0.00B 定义构建参数
ARG POLYGRAPHY_VERSION
                        
# 2022-12-15 06:30:50  0.00B 定义构建参数
ARG DALI_BUILD
                        
# 2022-12-15 06:30:50  0.00B 定义构建参数
ARG DALI_VERSION
                        
# 2022-12-15 06:30:50  0.00B 添加元数据标签
LABEL com.nvidia.nccl.version=2.15.5 com.nvidia.cublas.version=11.11.3.6 com.nvidia.cufft.version=10.9.0.58 com.nvidia.curand.version=10.3.0.86 com.nvidia.cusparse.version=11.7.5.86 com.nvidia.cusolver.version=11.4.1.48 com.nvidia.cutensor.version=1.6.1.5 com.nvidia.npp.version=11.8.0.86 com.nvidia.nvjpeg.version=11.9.0.86 com.nvidia.cudnn.version=8.7.0.84 com.nvidia.tensorrt.version=8.5.1.7 com.nvidia.tensorrtoss.version=22.12 com.nvidia.nsightsystems.version=2022.4.2.1 com.nvidia.nsightcompute.version=2022.3.0.22
                        
# 2022-12-15 06:30:50  4.68GB 执行命令并创建新的镜像层
RUN |17 CUDA_VERSION=11.8.0.065 CUDA_DRIVER_VERSION=520.61.05 JETPACK_HOST_MOUNTS= NCCL_VERSION=2.15.5 CUBLAS_VERSION=11.11.3.6 CUFFT_VERSION=10.9.0.58 CURAND_VERSION=10.3.0.86 CUSPARSE_VERSION=11.7.5.86 CUSOLVER_VERSION=11.4.1.48 CUTENSOR_VERSION=1.6.1.5 NPP_VERSION=11.8.0.86 NVJPEG_VERSION=11.9.0.86 CUDNN_VERSION=8.7.0.84 TRT_VERSION=8.5.1.7 TRTOSS_VERSION=22.12 NSIGHT_SYSTEMS_VERSION=2022.4.2.1 NSIGHT_COMPUTE_VERSION=2022.3.0.22 /bin/sh -c /nvidia/build-scripts/installNCCL.sh  && /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/installCUTENSOR.sh # buildkit
                        
# 2022-12-15 06:27:34  0.00B 设置环境变量 NCCL_VERSION CUBLAS_VERSION CUFFT_VERSION CURAND_VERSION CUSPARSE_VERSION CUSOLVER_VERSION CUTENSOR_VERSION NPP_VERSION NVJPEG_VERSION CUDNN_VERSION TRT_VERSION TRTOSS_VERSION NSIGHT_SYSTEMS_VERSION NSIGHT_COMPUTE_VERSION
ENV NCCL_VERSION=2.15.5 CUBLAS_VERSION=11.11.3.6 CUFFT_VERSION=10.9.0.58 CURAND_VERSION=10.3.0.86 CUSPARSE_VERSION=11.7.5.86 CUSOLVER_VERSION=11.4.1.48 CUTENSOR_VERSION=1.6.1.5 NPP_VERSION=11.8.0.86 NVJPEG_VERSION=11.9.0.86 CUDNN_VERSION=8.7.0.84 TRT_VERSION=8.5.1.7 TRTOSS_VERSION=22.12 NSIGHT_SYSTEMS_VERSION=2022.4.2.1 NSIGHT_COMPUTE_VERSION=2022.3.0.22
                        
# 2022-12-15 06:27:34  0.00B 定义构建参数
ARG NSIGHT_COMPUTE_VERSION
                        
# 2022-12-15 06:27:34  0.00B 定义构建参数
ARG NSIGHT_SYSTEMS_VERSION
                        
# 2022-12-15 06:27:34  0.00B 定义构建参数
ARG TRTOSS_VERSION
                        
# 2022-12-15 06:27:34  0.00B 定义构建参数
ARG TRT_VERSION
                        
# 2022-12-15 06:27:34  0.00B 定义构建参数
ARG CUDNN_VERSION
                        
# 2022-12-15 06:27:34  0.00B 定义构建参数
ARG NVJPEG_VERSION
                        
# 2022-12-15 06:27:34  0.00B 定义构建参数
ARG NPP_VERSION
                        
# 2022-12-15 06:27:34  0.00B 定义构建参数
ARG CUTENSOR_VERSION
                        
# 2022-12-15 06:27:34  0.00B 定义构建参数
ARG CUSOLVER_VERSION
                        
# 2022-12-15 06:27:34  0.00B 定义构建参数
ARG CUSPARSE_VERSION
                        
# 2022-12-15 06:27:34  0.00B 定义构建参数
ARG CURAND_VERSION
                        
# 2022-12-15 06:27:34  0.00B 定义构建参数
ARG CUFFT_VERSION
                        
# 2022-12-15 06:27:34  0.00B 定义构建参数
ARG CUBLAS_VERSION
                        
# 2022-12-15 06:27:34  0.00B 定义构建参数
ARG NCCL_VERSION
                        
# 2022-12-15 06:27:34  0.00B 添加元数据标签
LABEL com.nvidia.volumes.needed=nvidia_driver com.nvidia.cuda.version=9.0
                        
# 2022-12-15 06:27:34  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
                        
# 2022-12-15 06:27:34  656.37KB 执行命令并创建新的镜像层
RUN |3 CUDA_VERSION=11.8.0.065 CUDA_DRIVER_VERSION=520.61.05 JETPACK_HOST_MOUNTS= /bin/sh -c cp -vprd /nvidia/. /  &&  patch -p0 < /etc/startup_scripts.patch  &&  rm -f /etc/startup_scripts.patch # buildkit
                        
# 2022-12-15 06:27:34  396.52MB 执行命令并创建新的镜像层
RUN |3 CUDA_VERSION=11.8.0.065 CUDA_DRIVER_VERSION=520.61.05 JETPACK_HOST_MOUNTS= /bin/sh -c /nvidia/build-scripts/installCUDA.sh # buildkit
                        
# 2022-12-15 06:27:34  0.00B 设置环境变量 CUDA_VERSION CUDA_DRIVER_VERSION CUDA_CACHE_DISABLE NVIDIA_REQUIRE_JETPACK_HOST_MOUNTS
ENV CUDA_VERSION=11.8.0.065 CUDA_DRIVER_VERSION=520.61.05 CUDA_CACHE_DISABLE=1 NVIDIA_REQUIRE_JETPACK_HOST_MOUNTS=
                        
# 2022-12-15 06:27:34  0.00B 定义构建参数
ARG JETPACK_HOST_MOUNTS
                        
# 2022-12-15 06:27:34  0.00B 定义构建参数
ARG CUDA_DRIVER_VERSION
                        
# 2022-12-15 06:27:34  0.00B 定义构建参数
ARG CUDA_VERSION
                        
# 2022-12-13 05:08:57  301.56MB 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         apt-utils         build-essential         ca-certificates         curl         libncurses5         libncursesw5         patch         wget         rsync         unzip         jq         gnupg         libtcmalloc-minimal4 # buildkit
                        
# 2022-12-09 09:20:21  0.00B 
/bin/sh -c #(nop)  CMD ["bash"]
                        
# 2022-12-09 09:20:21  72.79MB 
/bin/sh -c #(nop) ADD file:9d282119af0c42bc823c95b4192a3350cf2cad670622017356dd2e637762e425 in / 
                        
                    

镜像信息

{
    "Id": "sha256:9f045a051e7bcb66eff4a01f15838737ffbbe9954f3dc00219c5a6847899e7ef",
    "RepoTags": [
        "hi20240217/pub:bevfusion_inference",
        "swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/hi20240217/pub:bevfusion_inference"
    ],
    "RepoDigests": [
        "hi20240217/pub@sha256:9f2c82b7aaca7fec50ba5166bf96ed325461480a32eba0c1041072d1f6cccbde",
        "swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/hi20240217/pub@sha256:9f2c82b7aaca7fec50ba5166bf96ed325461480a32eba0c1041072d1f6cccbde"
    ],
    "Parent": "",
    "Comment": "",
    "Created": "2026-05-07T11:20:23.521159278Z",
    "Container": "",
    "ContainerConfig": null,
    "DockerVersion": "24.0.5",
    "Author": "",
    "Config": {
        "Hostname": "bevfusion-infer",
        "Domainname": "",
        "User": "",
        "AttachStdin": false,
        "AttachStdout": false,
        "AttachStderr": false,
        "ExposedPorts": {
            "6006/tcp": {},
            "8888/tcp": {}
        },
        "Tty": true,
        "OpenStdin": true,
        "StdinOnce": false,
        "Env": [
            "NVIDIA_VISIBLE_DEVICES=all",
            "PATH=/usr/local/lib/python3.8/dist-packages/torch_tensorrt/bin:/usr/local/mpi/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/ucx/bin:/opt/tensorrt/bin",
            "CUDA_VERSION=11.8.0.065",
            "CUDA_DRIVER_VERSION=520.61.05",
            "CUDA_CACHE_DISABLE=1",
            "NVIDIA_REQUIRE_JETPACK_HOST_MOUNTS=",
            "_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=2.15.5",
            "CUBLAS_VERSION=11.11.3.6",
            "CUFFT_VERSION=10.9.0.58",
            "CURAND_VERSION=10.3.0.86",
            "CUSPARSE_VERSION=11.7.5.86",
            "CUSOLVER_VERSION=11.4.1.48",
            "CUTENSOR_VERSION=1.6.1.5",
            "NPP_VERSION=11.8.0.86",
            "NVJPEG_VERSION=11.9.0.86",
            "CUDNN_VERSION=8.7.0.84",
            "TRT_VERSION=8.5.1.7",
            "TRTOSS_VERSION=22.12",
            "NSIGHT_SYSTEMS_VERSION=2022.4.2.1",
            "NSIGHT_COMPUTE_VERSION=2022.3.0.22",
            "DALI_VERSION=1.20.0",
            "DALI_BUILD=6562491",
            "POLYGRAPHY_VERSION=0.43.1",
            "TRANSFORMER_ENGINE_VERSION=0.3",
            "LD_LIBRARY_PATH=/usr/local/lib/python3.8/dist-packages/torch/lib:/usr/local/lib/python3.8/dist-packages/torch_tensorrt/lib:/usr/local/cuda/compat/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64",
            "NVIDIA_DRIVER_CAPABILITIES=compute,utility,video",
            "NVIDIA_PRODUCT_NAME=PyTorch",
            "GDRCOPY_VERSION=2.3",
            "HPCX_VERSION=2.13",
            "MOFED_VERSION=5.4-rdmacore36.0",
            "OPENUCX_VERSION=1.14.0",
            "OPENMPI_VERSION=4.1.4",
            "RDMACORE_VERSION=36.0",
            "OPAL_PREFIX=/opt/hpcx/ompi",
            "OMPI_MCA_coll_hcoll_enable=0",
            "LIBRARY_PATH=/usr/local/cuda/lib64/stubs:",
            "PYTORCH_BUILD_VERSION=1.14.0a0+410ce96",
            "PYTORCH_VERSION=1.14.0a0+410ce96",
            "PYTORCH_BUILD_NUMBER=0",
            "NVIDIA_PYTORCH_VERSION=22.12",
            "PYVER=3.8",
            "OPENBLAS_VERSION=0.3.20",
            "PYTHONIOENCODING=utf-8",
            "LC_ALL=C.UTF-8",
            "PIP_DEFAULT_TIMEOUT=100",
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