docker.io/dataelement/bisheng-ft:v0.2.0 linux/amd64

Docker拉取命令

docker pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/dataelement/bisheng-ft:v0.2.0
docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/dataelement/bisheng-ft:v0.2.0  docker.io/dataelement/bisheng-ft:v0.2.0

Containerd拉取命令

ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/dataelement/bisheng-ft:v0.2.0
ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/dataelement/bisheng-ft:v0.2.0  docker.io/dataelement/bisheng-ft:v0.2.0

Shell快速替换命令

sed -i 's#dataelement/bisheng-ft:v0.2.0#swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/dataelement/bisheng-ft:v0.2.0#' 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/dataelement/bisheng-ft:v0.2.0 && docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/dataelement/bisheng-ft:v0.2.0  docker.io/dataelement/bisheng-ft:v0.2.0'

Ansible快速分发-Containerd

#ansible k8s -m shell -a 'ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/dataelement/bisheng-ft:v0.2.0 && ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/dataelement/bisheng-ft:v0.2.0  docker.io/dataelement/bisheng-ft:v0.2.0'

镜像构建历史

# 2024-08-20 16:11:05  0.00B 设置默认要执行的命令
CMD ["sh start-sft-server.sh"]
                        
# 2024-08-20 16:11:05  0.00B 声明容器运行时监听的端口
EXPOSE map[8000/tcp:{}]
                        
# 2024-08-20 16:11:05  0.00B 执行命令并创建新的镜像层
RUN |3 PIP_REPO=https://pypi.tuna.tsinghua.edu.cn/simple EXTR_PIP_REPO=http://public:26rS9HRxDqaVy5T@192.168.106.8:6081/repository/pypi-hosted/simple --trusted-host 192.168.106.8 BISHENG_FT_VER=0.0.1 /bin/sh -c mkdir -p /opt/bisheng-ft/sft_log /opt/bisheng-ft/finetune_output # buildkit
                        
# 2024-08-20 16:11:05  253.00B 复制新文件或目录到容器中
COPY ./docker/start-sft-server.sh /opt/bisheng-ft/ # buildkit
                        
# 2024-08-20 16:11:05  24.65KB 复制新文件或目录到容器中
COPY ./src/sft_server /opt/bisheng-ft/sft_server # buildkit
                        
# 2024-08-20 16:11:05  563.00B 复制新文件或目录到容器中
COPY ./docker/datasets_download.sh /opt/bisheng-ft/sft_datasets # buildkit
                        
# 2024-08-20 16:11:04  18.81MB 复制新文件或目录到容器中
COPY ./data/alpaca_data_zh_51k.json /opt/bisheng-ft/sft_datasets # buildkit
                        
# 2024-08-20 16:11:04  22.77MB 复制新文件或目录到容器中
COPY ./data/alpaca_data_en_52k.json /opt/bisheng-ft/sft_datasets # buildkit
                        
# 2024-08-20 16:11:04  0.00B 执行命令并创建新的镜像层
RUN |3 PIP_REPO=https://pypi.tuna.tsinghua.edu.cn/simple EXTR_PIP_REPO=http://public:26rS9HRxDqaVy5T@192.168.106.8:6081/repository/pypi-hosted/simple --trusted-host 192.168.106.8 BISHENG_FT_VER=0.0.1 /bin/sh -c mkdir -p /opt/bisheng-ft/sft_datasets # buildkit
                        
# 2024-08-20 16:11:04  496.07KB 执行命令并创建新的镜像层
RUN |3 PIP_REPO=https://pypi.tuna.tsinghua.edu.cn/simple EXTR_PIP_REPO=http://public:26rS9HRxDqaVy5T@192.168.106.8:6081/repository/pypi-hosted/simple --trusted-host 192.168.106.8 BISHENG_FT_VER=0.0.1 /bin/sh -c pip install bisheng-ft==${BISHENG_FT_VER}     --extra-index $EXTR_PIP_REPO     -i $PIP_REPO # buildkit
                        
# 2024-08-20 16:10:55  3.73GB 执行命令并创建新的镜像层
RUN |3 PIP_REPO=https://pypi.tuna.tsinghua.edu.cn/simple EXTR_PIP_REPO=http://public:26rS9HRxDqaVy5T@192.168.106.8:6081/repository/pypi-hosted/simple --trusted-host 192.168.106.8 BISHENG_FT_VER=0.0.1 /bin/sh -c pip install -r requirements.txt -i $PIP_REPO # buildkit
                        
# 2024-08-20 15:55:51  342.00B 复制新文件或目录到容器中
COPY ./requirements.txt /opt/bisheng-ft # buildkit
                        
# 2024-08-20 15:55:50  9.34MB 执行命令并创建新的镜像层
RUN |3 PIP_REPO=https://pypi.tuna.tsinghua.edu.cn/simple EXTR_PIP_REPO=http://public:26rS9HRxDqaVy5T@192.168.106.8:6081/repository/pypi-hosted/simple --trusted-host 192.168.106.8 BISHENG_FT_VER=0.0.1 /bin/sh -c pip install --upgrade pip # buildkit
                        
# 2024-08-20 15:55:35  19.00B 执行命令并创建新的镜像层
RUN |3 PIP_REPO=https://pypi.tuna.tsinghua.edu.cn/simple EXTR_PIP_REPO=http://public:26rS9HRxDqaVy5T@192.168.106.8:6081/repository/pypi-hosted/simple --trusted-host 192.168.106.8 BISHENG_FT_VER=0.0.1 /bin/sh -c ln -s /usr/local/bin/pip3 /usr/bin/pip3.8 # buildkit
                        
# 2024-08-20 15:55:34  0.00B 设置工作目录为/opt/bisheng-ft
WORKDIR /opt/bisheng-ft
                        
# 2024-08-20 15:55:34  0.00B 执行命令并创建新的镜像层
RUN |3 PIP_REPO=https://pypi.tuna.tsinghua.edu.cn/simple EXTR_PIP_REPO=http://public:26rS9HRxDqaVy5T@192.168.106.8:6081/repository/pypi-hosted/simple --trusted-host 192.168.106.8 BISHENG_FT_VER=0.0.1 /bin/sh -c mkdir -p /opt/bisheng-ft/ # buildkit
                        
# 2024-08-20 15:55:33  47.00B 执行命令并创建新的镜像层
RUN |3 PIP_REPO=https://pypi.tuna.tsinghua.edu.cn/simple EXTR_PIP_REPO=http://public:26rS9HRxDqaVy5T@192.168.106.8:6081/repository/pypi-hosted/simple --trusted-host 192.168.106.8 BISHENG_FT_VER=0.0.1 /bin/sh -c ln -snf /usr/share/zoneinfo/$TZ /etc/localtime && echo $TZ > /etc/timezone # buildkit
                        
# 2024-08-20 15:55:31  0.00B 设置环境变量 TZ
ENV TZ=Asia/Shanghai
                        
# 2024-08-20 15:55:31  0.00B 设置环境变量 LC_ALL LANG LANGUAGE
ENV LC_ALL=en_US.UTF-8 LANG=en_US.UTF-8 LANGUAGE=en_US.UTF-8
                        
# 2024-08-20 15:55:31  3.05MB 执行命令并创建新的镜像层
RUN |3 PIP_REPO=https://pypi.tuna.tsinghua.edu.cn/simple EXTR_PIP_REPO=http://public:26rS9HRxDqaVy5T@192.168.106.8:6081/repository/pypi-hosted/simple --trusted-host 192.168.106.8 BISHENG_FT_VER=0.0.1 /bin/sh -c locale-gen en_US.UTF-8 # buildkit
                        
# 2024-08-20 15:55:27  297.38MB 执行命令并创建新的镜像层
RUN |3 PIP_REPO=https://pypi.tuna.tsinghua.edu.cn/simple EXTR_PIP_REPO=http://public:26rS9HRxDqaVy5T@192.168.106.8:6081/repository/pypi-hosted/simple --trusted-host 192.168.106.8 BISHENG_FT_VER=0.0.1 /bin/sh -c apt update && apt install -y nasm zlib1g-dev libssl-dev libre2-dev libb64-dev locales libsm6 libxext6 libxrender-dev libgl1 tmux git # buildkit
                        
# 2024-08-20 15:55:27  0.00B 设置环境变量 DEBIAN_FRONTEND
ENV DEBIAN_FRONTEND=noninteractive
                        
# 2024-08-20 15:55:27  0.00B 定义构建参数
ARG BISHENG_FT_VER=0.0.1
                        
# 2024-08-20 15:55:27  0.00B 定义构建参数
ARG EXTR_PIP_REPO=http://public:26rS9HRxDqaVy5T@192.168.106.8:6081/repository/pypi-hosted/simple --trusted-host 192.168.106.8
                        
# 2024-08-20 15:55:27  0.00B 定义构建参数
ARG PIP_REPO=https://pypi.tuna.tsinghua.edu.cn/simple
                        
# 2022-08-04 15:45:07  0.00B 添加元数据标签
LABEL com.nvidia.build.ref=77ddbc1eeb37f30914b0f15067f584147275477b
                        
# 2022-08-04 15:45:07  0.00B 定义构建参数
ARG NVIDIA_BUILD_REF
                        
# 2022-08-04 15:45:07  0.00B 添加元数据标签
LABEL com.nvidia.build.id=42105213
                        
# 2022-08-04 15:45:07  0.00B 设置环境变量 NVIDIA_BUILD_ID
ENV NVIDIA_BUILD_ID=42105213
                        
# 2022-08-04 15:45:07  0.00B 定义构建参数
ARG NVIDIA_BUILD_ID
                        
# 2022-08-04 15:45:07  720.00B 复制新文件或目录到容器中
COPY entrypoint.d/ /opt/nvidia/entrypoint.d/ # buildkit
                        
# 2022-08-04 15:45:07  61.14KB 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
                        
# 2022-08-04 15:45:05  0.00B 设置环境变量 CUDA_MODULE_LOADING
ENV CUDA_MODULE_LOADING=LAZY
                        
# 2022-08-04 15:45:05  0.00B 设置环境变量 TORCH_CUDNN_V8_API_ENABLED
ENV TORCH_CUDNN_V8_API_ENABLED=0
                        
# 2022-08-04 15:45:05  0.00B 设置环境变量 PATH
ENV PATH=/opt/conda/lib/python3.8/site-packages/torch_tensorrt/bin:/opt/conda/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
                        
# 2022-08-04 15:45:05  0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/opt/conda/lib/python3.8/site-packages/torch/lib:/opt/conda/lib/python3.8/site-packages/torch_tensorrt/lib:/usr/local/cuda/compat/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64
                        
# 2022-08-04 15:45:05  8.26MB 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
                        
# 2022-08-04 15:39:12  0.00B 定义构建参数
ARG PYVER
                        
# 2022-08-04 15:39:12  90.76MB 复制新文件或目录到容器中
COPY torch_tensorrt/ /opt/pytorch/torch_tensorrt/ # buildkit
                        
# 2022-08-04 15:39:09  14.63MB 执行命令并创建新的镜像层
RUN |4 NVIDIA_PYTORCH_VERSION=22.08 PYTORCH_BUILD_VERSION=1.13.0a0+d321be6 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==0.33.0     && 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
                        
# 2022-08-04 15:38:53  0.00B 设置环境变量 PATH
ENV PATH=/opt/conda/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
                        
# 2022-08-04 15:38:53  4.50MB 执行命令并创建新的镜像层
RUN |4 NVIDIA_PYTORCH_VERSION=22.08 PYTORCH_BUILD_VERSION=1.13.0a0+d321be6 TARGETARCH=amd64 PYVER=3.8 /bin/sh -c URL=$(VERIFY=1 /nvidia/build-scripts/installTRT.sh 2>/dev/null | sed -n "s/^.*\(http.*\)tar.*$/\1/p")tar  && FILE=$(wget -O - $URL 2>/dev/null | sed -n 's/^.*href="\(TensorRT[^"]*\)".*$/\1/p' | grep -v internal)  && wget --quiet $URL/$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
                        
# 2022-08-04 15:38:13  51.00MB 执行命令并创建新的镜像层
RUN |4 NVIDIA_PYTORCH_VERSION=22.08 PYTORCH_BUILD_VERSION=1.13.0a0+d321be6 TARGETARCH=amd64 PYVER=3.8 /bin/sh -c chmod -R a+w . # buildkit
                        
# 2022-08-04 15:38:11  34.89MB 复制新文件或目录到容器中
COPY tutorials tutorials # buildkit
                        
# 2022-08-04 15:38:10  15.96MB 复制新文件或目录到容器中
COPY examples examples # buildkit
                        
# 2022-08-04 15:38:09  1.78KB 复制新文件或目录到容器中
COPY docker-examples docker-examples # buildkit
                        
# 2022-08-04 15:38:08  2.06KB 复制新文件或目录到容器中
COPY NVREADME.md README.md # buildkit
                        
# 2022-08-04 15:38:08  0.00B 设置工作目录为/workspace
WORKDIR /workspace
                        
# 2022-08-04 15:38:08  0.00B 设置环境变量 PYTHONIOENCODING LC_ALL
ENV PYTHONIOENCODING=utf-8 LC_ALL=C.UTF-8
                        
# 2022-08-04 15:38:08  3.26GB 执行命令并创建新的镜像层
RUN |4 NVIDIA_PYTORCH_VERSION=22.08 PYTORCH_BUILD_VERSION=1.13.0a0+d321be6 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/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 /opt/conda --strip-components=1 -xf /rapids/xgboost-*.tar.gz  && pip install --no-cache-dir --ignore-installed llvmlite  && 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/raft-*.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
                        
# 2022-08-04 15:36:18  2.18MB 执行命令并创建新的镜像层
RUN |4 NVIDIA_PYTORCH_VERSION=22.08 PYTORCH_BUILD_VERSION=1.13.0a0+d321be6 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/9.0.1  && sed -i 's/DEBUG = False/DEBUG = True/' setup.py  && 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
                        
# 2022-08-04 15:35:41  320.19MB 执行命令并创建新的镜像层
RUN |4 NVIDIA_PYTORCH_VERSION=22.08 PYTORCH_BUILD_VERSION=1.13.0a0+d321be6 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 && mkdir build && cd build && cmake -DWITH_CUDA=1 -DCMAKE_PREFIX_PATH=`python -c 'import torch;print(torch.utils.cmake_prefix_path)'` .. && make && make install )  && ( 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" . )  && ( cd text && python setup.py install && python setup.py clean)  && ( 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
                        
# 2022-08-04 14:41:27  2.21KB 复制新文件或目录到容器中
COPY singularity/ /.singularity.d/ # buildkit
                        
# 2022-08-04 14:41:26  10.47MB 执行命令并创建新的镜像层
RUN |4 NVIDIA_PYTORCH_VERSION=22.08 PYTORCH_BUILD_VERSION=1.13.0a0+d321be6 TARGETARCH=amd64 PYVER=3.8 /bin/sh -c export COCOAPI_TAG=$(echo ${COCOAPI_VERSION} | sed 's/^.*+n//')  && pip install --no-cache-dir cython pybind11  && pip install --no-cache-dir git+https://github.com/nvidia/cocoapi.git@${COCOAPI_TAG}#subdirectory=PythonAPI # buildkit
                        
# 2022-08-04 14:41:01  0.00B 设置环境变量 COCOAPI_VERSION
ENV COCOAPI_VERSION=2.0+nv0.6.1
                        
# 2022-08-04 14:41:01  573.51MB 执行命令并创建新的镜像层
RUN |4 NVIDIA_PYTORCH_VERSION=22.08 PYTORCH_BUILD_VERSION=1.13.0a0+d321be6 TARGETARCH=amd64 PYVER=3.8 /bin/sh -c if dpkg --compare-versions ${DALI_VERSION} lt 0.23; then       DALI_URL_SUFFIX="/cuda/${CUDA_VERSION%%.*}.0";     else       DALI_PKG_SUFFIX="-cuda${CUDA_VERSION%%.*}0";     fi  && pip install --no-cache-dir                 --extra-index-url https://developer.download.nvidia.com/compute/redist                 --extra-index-url http://sqrl/dldata/pip-dali${DALI_URL_SUFFIX:-} --trusted-host sqrl         nvidia-dali${DALI_PKG_SUFFIX:-}==${DALI_VERSION} # buildkit
                        
# 2022-08-04 14:40:41  1.33GB 执行命令并创建新的镜像层
RUN |4 NVIDIA_PYTORCH_VERSION=22.08 PYTORCH_BUILD_VERSION=1.13.0a0+d321be6 TARGETARCH=amd64 PYVER=3.8 /bin/sh -c cd pytorch &&     CFLAGS="-g0"     USE_CUPTI_SO=1     USE_KINETO=1     CMAKE_PREFIX_PATH="$(dirname $(which conda))/../"     NCCL_INCLUDE_DIR="/usr/include/"     NCCL_LIB_DIR="/usr/lib/"     USE_SYSTEM_NCCL=1     CFLAGS='-fno-gnu-unique'     python setup.py install &&     python setup.py clean # buildkit
                        
# 2022-08-04 13:43:03  0.00B 设置环境变量 USE_EXPERIMENTAL_CUDNN_V8_API
ENV USE_EXPERIMENTAL_CUDNN_V8_API=1
                        
# 2022-08-04 13:43:03  0.00B 设置环境变量 TORCH_ALLOW_TF32_CUBLAS_OVERRIDE
ENV TORCH_ALLOW_TF32_CUBLAS_OVERRIDE=1
                        
# 2022-08-04 13:43:03  0.00B 设置环境变量 PYTORCH_HOME
ENV PYTORCH_HOME=/opt/pytorch/pytorch
                        
# 2022-08-04 13:43:03  0.00B 设置环境变量 CUDA_HOME
ENV CUDA_HOME=/usr/local/cuda
                        
# 2022-08-04 13:43:03  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+PTX
                        
# 2022-08-04 13:43:03  24.52KB 执行命令并创建新的镜像层
RUN |4 NVIDIA_PYTORCH_VERSION=22.08 PYTORCH_BUILD_VERSION=1.13.0a0+d321be6 TARGETARCH=amd64 PYVER=3.8 /bin/sh -c pip install --no-cache-dir expecttest # buildkit
                        
# 2022-08-04 13:43:00  127.58MB 执行命令并创建新的镜像层
RUN |4 NVIDIA_PYTORCH_VERSION=22.08 PYTORCH_BUILD_VERSION=1.13.0a0+d321be6 TARGETARCH=amd64 PYVER=3.8 /bin/sh -c pip install --no-cache-dir "librosa>=0.6.2" # buildkit
                        
# 2022-08-04 13:42:50  0.00B 执行命令并创建新的镜像层
RUN |4 NVIDIA_PYTORCH_VERSION=22.08 PYTORCH_BUILD_VERSION=1.13.0a0+d321be6 TARGETARCH=amd64 PYVER=3.8 /bin/sh -c pip install --no-cache-dir typing_extensions # buildkit
                        
# 2022-08-04 13:42:47  230.10MB 执行命令并创建新的镜像层
RUN |4 NVIDIA_PYTORCH_VERSION=22.08 PYTORCH_BUILD_VERSION=1.13.0a0+d321be6 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
                        
# 2022-08-04 13:31:46  0.00B 声明容器运行时监听的端口
EXPOSE map[6006/tcp:{}]
                        
# 2022-08-04 13:31:46  0.00B 声明容器运行时监听的端口
EXPOSE map[8888/tcp:{}]
                        
# 2022-08-04 13:31:46  0.00B 设置环境变量 TENSORBOARD_PORT
ENV TENSORBOARD_PORT=6006
                        
# 2022-08-04 13:31:46  0.00B 设置环境变量 JUPYTER_PORT
ENV JUPYTER_PORT=8888
                        
# 2022-08-04 13:31:46  427.00B 复制新文件或目录到容器中
COPY jupyter_notebook_config.py /opt/conda/etc/jupyter/ # buildkit
                        
# 2022-08-04 13:31:46  157.09MB 执行命令并创建新的镜像层
RUN |4 NVIDIA_PYTORCH_VERSION=22.08 PYTORCH_BUILD_VERSION=1.13.0a0+d321be6 TARGETARCH=amd64 PYVER=3.8 /bin/sh -c pip install --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 /opt/conda/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 /opt/conda/etc/jupyter/  && jupyter lab clean # buildkit
                        
# 2022-08-04 13:27:58  0.00B 设置环境变量 NVM_DIR
ENV NVM_DIR=/usr/local/nvm
                        
# 2022-08-04 13:27:58  27.81KB 执行命令并创建新的镜像层
RUN |4 NVIDIA_PYTORCH_VERSION=22.08 PYTORCH_BUILD_VERSION=1.13.0a0+d321be6 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
                        
# 2022-08-04 13:27:57  50.72MB 执行命令并创建新的镜像层
RUN |4 NVIDIA_PYTORCH_VERSION=22.08 PYTORCH_BUILD_VERSION=1.13.0a0+d321be6 TARGETARCH=amd64 PYVER=3.8 /bin/sh -c pip install --no-cache-dir tensorboard # buildkit
                        
# 2022-08-04 13:27:48  239.49MB 执行命令并创建新的镜像层
RUN |4 NVIDIA_PYTORCH_VERSION=22.08 PYTORCH_BUILD_VERSION=1.13.0a0+d321be6 TARGETARCH=amd64 PYVER=3.8 /bin/sh -c git config --global url."https://github".insteadOf git://github  && pip install --no-cache-dir -r text/requirements.txt  && pip install --no-cache-dir -r caffe2_requirements.txt  && pip install --no-cache-dir notebook==6.4.10 jupyterlab==2.3.2 python-hostlist # buildkit
                        
# 2022-08-04 13:26:50  43.20MB 执行命令并创建新的镜像层
RUN |4 NVIDIA_PYTORCH_VERSION=22.08 PYTORCH_BUILD_VERSION=1.13.0a0+d321be6 TARGETARCH=amd64 PYVER=3.8 /bin/sh -c OPENCV_VERSION=3.4.11 &&     cd / &&     wget -q -O - https://github.com/opencv/opencv/archive/${OPENCV_VERSION}.tar.gz | tar -xzf - &&     cd /opencv-${OPENCV_VERSION} && mkdir build && cd build &&     cmake -DCMAKE_BUILD_TYPE=RELEASE -DCMAKE_INSTALL_PREFIX=/usr           -DWITH_CUDA=OFF -DWITH_1394=OFF           -DPYTHON3_PACKAGES_PATH=$(python -c "from distutils.sysconfig import *; print(get_python_lib())")           -DBUILD_opencv_cudalegacy=OFF -DBUILD_opencv_stitching=OFF -DWITH_IPP=OFF -DWITH_PROTOBUF=OFF .. &&     make -j"$(nproc)" install &&     rm -rf /opencv-${OPENCV_VERSION} # buildkit
                        
# 2022-08-04 13:23:02  916.36MB 复制新文件或目录到容器中
COPY . . # buildkit
                        
# 2022-08-04 13:22:53  0.00B 设置工作目录为/opt/pytorch
WORKDIR /opt/pytorch
                        
# 2022-08-04 13:22:53  3.57MB 执行命令并创建新的镜像层
RUN |4 NVIDIA_PYTORCH_VERSION=22.08 PYTORCH_BUILD_VERSION=1.13.0a0+d321be6 TARGETARCH=amd64 PYVER=3.8 /bin/sh -c pip install --no-cache-dir protobuf==3.20.1 # buildkit
                        
# 2022-08-04 13:22:50  27.64KB 执行命令并创建新的镜像层
RUN |4 NVIDIA_PYTORCH_VERSION=22.08 PYTORCH_BUILD_VERSION=1.13.0a0+d321be6 TARGETARCH=amd64 PYVER=3.8 /bin/sh -c pip install tqdm --upgrade # buildkit
                        
# 2022-08-04 13:22:48  2.44MB 执行命令并创建新的镜像层
RUN |4 NVIDIA_PYTORCH_VERSION=22.08 PYTORCH_BUILD_VERSION=1.13.0a0+d321be6 TARGETARCH=amd64 PYVER=3.8 /bin/sh -c pip install hypothesis==4.50.8 # buildkit
                        
# 2022-08-04 13:22:43  0.00B 设置环境变量 PATH
ENV PATH=/opt/conda/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
                        
# 2022-08-04 13:22:43  1.72GB 执行命令并创建新的镜像层
RUN |4 NVIDIA_PYTORCH_VERSION=22.08 PYTORCH_BUILD_VERSION=1.13.0a0+d321be6 TARGETARCH=amd64 PYVER=3.8 /bin/sh -c wget -O ~/miniforge.sh https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-Linux-$(uname -m).sh  &&      chmod +x ~/miniforge.sh &&      ~/miniforge.sh -b -p /opt/conda &&      rm ~/miniforge.sh &&      /opt/conda/bin/conda install -y python=$PYVER pip==21.2.4 cmake conda-build setuptools==59.5.0 numpy==1.22.4 pyyaml scipy==1.6.3 ipython ninja spacy mock numba==0.53.1 openblas!=0.3.6 &&      if [[ $TARGETARCH = "amd64" ]] ; then /opt/conda/bin/conda install -y mkl==2020.4 mkl-include==2020.4 ; fi &&      if [[ $TARGETARCH = "amd64" ]] ; then export LIBRARY_PATH=/opt/conda/lib:$LIBRARY_PATH ; fi &&      /opt/conda/bin/conda clean -ya # buildkit
                        
# 2022-08-04 13:15:03  0.00B 定义构建参数
ARG PYVER=3.8
                        
# 2022-08-04 13:15:03  110.10MB 执行命令并创建新的镜像层
RUN |3 NVIDIA_PYTORCH_VERSION=22.08 PYTORCH_BUILD_VERSION=1.13.0a0+d321be6 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends          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 &&      rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2022-08-04 13:15:03  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2022-08-04 13:15:03  0.00B 添加元数据标签
LABEL com.nvidia.pytorch.version=1.13.0a0+d321be6
                        
# 2022-08-04 13:15:03  0.00B 设置环境变量 PYTORCH_BUILD_VERSION PYTORCH_VERSION PYTORCH_BUILD_NUMBER NVIDIA_PYTORCH_VERSION
ENV PYTORCH_BUILD_VERSION=1.13.0a0+d321be6 PYTORCH_VERSION=1.13.0a0+d321be6 PYTORCH_BUILD_NUMBER=0 NVIDIA_PYTORCH_VERSION=22.08
                        
# 2022-08-04 13:15:03  0.00B 定义构建参数
ARG PYTORCH_BUILD_VERSION
                        
# 2022-08-04 13:15:03  0.00B 定义构建参数
ARG NVIDIA_PYTORCH_VERSION
                        
# 2022-08-04 13:15:03  0.00B 设置环境变量 NVIDIA_PRODUCT_NAME
ENV NVIDIA_PRODUCT_NAME=PyTorch
                        
# 2022-08-04 12:28:14  0.00B 执行命令并创建新的镜像层
RUN |7 GDRCOPY_VERSION=2.3 HPCX_VERSION=2.10 RDMACORE_VERSION=36.0 MOFED_VERSION=5.4-rdmacore36.0 OPENUCX_VERSION=1.12.0 OPENMPI_VERSION=4.1.2rc4 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
                        
# 2022-08-04 12:28:14  0.00B 设置环境变量 LIBRARY_PATH
ENV LIBRARY_PATH=/usr/local/cuda/lib64/stubs:
                        
# 2022-08-04 12:28:14  727.40MB 执行命令并创建新的镜像层
RUN |7 GDRCOPY_VERSION=2.3 HPCX_VERSION=2.10 RDMACORE_VERSION=36.0 MOFED_VERSION=5.4-rdmacore36.0 OPENUCX_VERSION=1.12.0 OPENMPI_VERSION=4.1.2rc4 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
                        
# 2022-08-04 12:25:03  1.49KB 复制新文件或目录到容器中
COPY cuda-*.patch /tmp # buildkit
                        
# 2022-08-04 12:25:02  0.00B 设置环境变量 OMPI_MCA_coll_hcoll_enable
ENV OMPI_MCA_coll_hcoll_enable=0
                        
# 2022-08-04 12:25:02  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
                        
# 2022-08-04 12:25:02  213.39MB 执行命令并创建新的镜像层
RUN |7 GDRCOPY_VERSION=2.3 HPCX_VERSION=2.10 RDMACORE_VERSION=36.0 MOFED_VERSION=5.4-rdmacore36.0 OPENUCX_VERSION=1.12.0 OPENMPI_VERSION=4.1.2rc4 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
                        
# 2022-08-04 12:25:02  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2022-08-04 12:25:02  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=2.10 MOFED_VERSION=5.4-rdmacore36.0 OPENUCX_VERSION=1.12.0 OPENMPI_VERSION=4.1.2rc4 RDMACORE_VERSION=36.0
                        
# 2022-08-04 12:25:02  0.00B 定义构建参数
ARG OPENMPI_VERSION
                        
# 2022-08-04 12:25:02  0.00B 定义构建参数
ARG OPENUCX_VERSION
                        
# 2022-08-04 12:25:02  0.00B 定义构建参数
ARG MOFED_VERSION=5.4-rdmacore36.0
                        
# 2022-08-04 12:25:02  0.00B 定义构建参数
ARG RDMACORE_VERSION
                        
# 2022-08-04 12:25:02  0.00B 定义构建参数
ARG HPCX_VERSION
                        
# 2022-08-04 12:25:02  0.00B 定义构建参数
ARG GDRCOPY_VERSION
                        
# 2022-08-04 12:24:57  102.33MB 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
                        
# 2022-08-04 12:12:17  148.72KB 复制新文件或目录到容器中
COPY NVIDIA_Deep_Learning_Container_License.pdf /workspace/ # buildkit
                        
# 2022-08-04 12:12:16  0.00B 配置容器启动时运行的命令
ENTRYPOINT ["/opt/nvidia/nvidia_entrypoint.sh"]
                        
# 2022-08-04 12:12:16  0.00B 设置环境变量 NVIDIA_PRODUCT_NAME
ENV NVIDIA_PRODUCT_NAME=CUDA
                        
# 2022-08-04 12:12:16  12.48KB 复制新文件或目录到容器中
COPY entrypoint/ /opt/nvidia/ # buildkit
                        
# 2022-08-04 12:12:15  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
                        
# 2022-08-04 12:12:15  46.00B 执行命令并创建新的镜像层
RUN |19 CUDA_VERSION=11.7.1.017 CUDA_DRIVER_VERSION=515.65.01 NCCL_VERSION=2.12.12 CUBLAS_VERSION=11.10.3.66 CUFFT_VERSION=10.7.2.91 CURAND_VERSION=10.2.10.91 CUSPARSE_VERSION=11.7.4.91 CUSOLVER_VERSION=11.4.0.1 CUTENSOR_VERSION=1.6.0.2 NPP_VERSION=11.7.4.75 NVJPEG_VERSION=11.8.0.2 CUDNN_VERSION=8.5.0.96 TRT_VERSION=8.4.2.4+cuda11.6.2.010 TRTOSS_VERSION=22.08 NSIGHT_SYSTEMS_VERSION=2022.1.3.18 NSIGHT_COMPUTE_VERSION=2022.2.1.3 DALI_VERSION=1.16.0 DALI_BUILD=5322998 DLPROF_VERSION= /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
                        
# 2022-08-04 12:12:15  13.39KB 复制文件或目录到容器中
ADD docs.tgz / # buildkit
                        
# 2022-08-04 12:12:14  0.00B 设置环境变量 DALI_VERSION DALI_BUILD DLPROF_VERSION
ENV DALI_VERSION=1.16.0 DALI_BUILD=5322998 DLPROF_VERSION=
                        
# 2022-08-04 12:12:14  0.00B 定义构建参数
ARG DLPROF_VERSION
                        
# 2022-08-04 12:12:14  0.00B 定义构建参数
ARG DALI_BUILD
                        
# 2022-08-04 12:12:14  0.00B 定义构建参数
ARG DALI_VERSION
                        
# 2022-08-04 12:12:14  0.00B 添加元数据标签
LABEL com.nvidia.nccl.version=2.12.12 com.nvidia.cublas.version=11.10.3.66 com.nvidia.cufft.version=10.7.2.91 com.nvidia.curand.version=10.2.10.91 com.nvidia.cusparse.version=11.7.4.91 com.nvidia.cusolver.version=11.4.0.1 com.nvidia.cutensor.version=1.6.0.2 com.nvidia.npp.version=11.7.4.75 com.nvidia.nvjpeg.version=11.8.0.2 com.nvidia.cudnn.version=8.5.0.96 com.nvidia.tensorrt.version=8.4.2.4+cuda11.6.2.010 com.nvidia.tensorrtoss.version=22.08 com.nvidia.nsightsystems.version=2022.1.3.18 com.nvidia.nsightcompute.version=2022.2.1.3
                        
# 2022-08-04 12:12:14  3.58GB 执行命令并创建新的镜像层
RUN |16 CUDA_VERSION=11.7.1.017 CUDA_DRIVER_VERSION=515.65.01 NCCL_VERSION=2.12.12 CUBLAS_VERSION=11.10.3.66 CUFFT_VERSION=10.7.2.91 CURAND_VERSION=10.2.10.91 CUSPARSE_VERSION=11.7.4.91 CUSOLVER_VERSION=11.4.0.1 CUTENSOR_VERSION=1.6.0.2 NPP_VERSION=11.7.4.75 NVJPEG_VERSION=11.8.0.2 CUDNN_VERSION=8.5.0.96 TRT_VERSION=8.4.2.4+cuda11.6.2.010 TRTOSS_VERSION=22.08 NSIGHT_SYSTEMS_VERSION=2022.1.3.18 NSIGHT_COMPUTE_VERSION=2022.2.1.3 /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
                        
# 2022-08-03 00:55:33  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=2.12.12 CUBLAS_VERSION=11.10.3.66 CUFFT_VERSION=10.7.2.91 CURAND_VERSION=10.2.10.91 CUSPARSE_VERSION=11.7.4.91 CUSOLVER_VERSION=11.4.0.1 CUTENSOR_VERSION=1.6.0.2 NPP_VERSION=11.7.4.75 NVJPEG_VERSION=11.8.0.2 CUDNN_VERSION=8.5.0.96 TRT_VERSION=8.4.2.4+cuda11.6.2.010 TRTOSS_VERSION=22.08 NSIGHT_SYSTEMS_VERSION=2022.1.3.18 NSIGHT_COMPUTE_VERSION=2022.2.1.3
                        
# 2022-08-03 00:55:33  0.00B 定义构建参数
ARG NSIGHT_COMPUTE_VERSION
                        
# 2022-08-03 00:55:33  0.00B 定义构建参数
ARG NSIGHT_SYSTEMS_VERSION
                        
# 2022-08-03 00:55:33  0.00B 定义构建参数
ARG TRTOSS_VERSION
                        
# 2022-08-03 00:55:33  0.00B 定义构建参数
ARG TRT_VERSION
                        
# 2022-08-03 00:55:33  0.00B 定义构建参数
ARG CUDNN_VERSION
                        
# 2022-08-03 00:55:33  0.00B 定义构建参数
ARG NVJPEG_VERSION
                        
# 2022-08-03 00:55:33  0.00B 定义构建参数
ARG NPP_VERSION
                        
# 2022-08-03 00:55:33  0.00B 定义构建参数
ARG CUTENSOR_VERSION
                        
# 2022-08-03 00:55:33  0.00B 定义构建参数
ARG CUSOLVER_VERSION
                        
# 2022-08-03 00:55:33  0.00B 定义构建参数
ARG CUSPARSE_VERSION
                        
# 2022-08-03 00:55:33  0.00B 定义构建参数
ARG CURAND_VERSION
                        
# 2022-08-03 00:55:33  0.00B 定义构建参数
ARG CUFFT_VERSION
                        
# 2022-08-03 00:55:33  0.00B 定义构建参数
ARG CUBLAS_VERSION
                        
# 2022-08-03 00:55:33  0.00B 定义构建参数
ARG NCCL_VERSION
                        
# 2022-08-03 00:55:33  0.00B 添加元数据标签
LABEL com.nvidia.volumes.needed=nvidia_driver com.nvidia.cuda.version=9.0
                        
# 2022-08-03 00:55:33  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
                        
# 2022-08-03 00:55:33  656.34KB 执行命令并创建新的镜像层
RUN |2 CUDA_VERSION=11.7.1.017 CUDA_DRIVER_VERSION=515.65.01 /bin/sh -c cp -vprd /nvidia/. /  &&  patch -p0 < /etc/startup_scripts.patch  &&  rm -f /etc/startup_scripts.patch # buildkit
                        
# 2022-08-03 00:55:32  292.29MB 执行命令并创建新的镜像层
RUN |2 CUDA_VERSION=11.7.1.017 CUDA_DRIVER_VERSION=515.65.01 /bin/sh -c /nvidia/build-scripts/installCUDA.sh # buildkit
                        
# 2022-08-03 00:55:32  0.00B 设置环境变量 CUDA_VERSION CUDA_DRIVER_VERSION CUDA_CACHE_DISABLE
ENV CUDA_VERSION=11.7.1.017 CUDA_DRIVER_VERSION=515.65.01 CUDA_CACHE_DISABLE=1
                        
# 2022-08-03 00:55:32  0.00B 定义构建参数
ARG CUDA_DRIVER_VERSION
                        
# 2022-08-03 00:55:32  0.00B 定义构建参数
ARG CUDA_VERSION
                        
# 2022-08-03 00:55:21  298.60MB 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         jq         gnupg         libtcmalloc-minimal4 # buildkit
                        
# 2022-08-02 09:30:49  0.00B 
/bin/sh -c #(nop)  CMD ["bash"]
                        
# 2022-08-02 09:30:49  72.78MB 
/bin/sh -c #(nop) ADD file:af4cf77e6818016b697a1491101b40c71d06529ced65f36107749f099d6d4bdc in / 
                        
                    

镜像信息

{
    "Id": "sha256:4c8332dcf765fe90b2493e09657483742f44bfd1e703ee281918155d1b775089",
    "RepoTags": [
        "dataelement/bisheng-ft:v0.2.0",
        "swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/dataelement/bisheng-ft:v0.2.0"
    ],
    "RepoDigests": [
        "dataelement/bisheng-ft@sha256:c53e258ca02150d937123df2f862db6d695a94784d4d6838669e820214dee300",
        "swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/dataelement/bisheng-ft@sha256:c53e258ca02150d937123df2f862db6d695a94784d4d6838669e820214dee300"
    ],
    "Parent": "",
    "Comment": "buildkit.dockerfile.v0",
    "Created": "2024-08-20T16:11:05.551781015+08:00",
    "Container": "",
    "ContainerConfig": null,
    "DockerVersion": "",
    "Author": "",
    "Config": {
        "Hostname": "",
        "Domainname": "",
        "User": "",
        "AttachStdin": false,
        "AttachStdout": false,
        "AttachStderr": false,
        "ExposedPorts": {
            "6006/tcp": {},
            "8000/tcp": {},
            "8888/tcp": {}
        },
        "Tty": false,
        "OpenStdin": false,
        "StdinOnce": false,
        "Env": [
            "PATH=/opt/conda/lib/python3.8/site-packages/torch_tensorrt/bin:/opt/conda/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=11.7.1.017",
            "CUDA_DRIVER_VERSION=515.65.01",
            "CUDA_CACHE_DISABLE=1",
            "_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=2.12.12",
            "CUBLAS_VERSION=11.10.3.66",
            "CUFFT_VERSION=10.7.2.91",
            "CURAND_VERSION=10.2.10.91",
            "CUSPARSE_VERSION=11.7.4.91",
            "CUSOLVER_VERSION=11.4.0.1",
            "CUTENSOR_VERSION=1.6.0.2",
            "NPP_VERSION=11.7.4.75",
            "NVJPEG_VERSION=11.8.0.2",
            "CUDNN_VERSION=8.5.0.96",
            "TRT_VERSION=8.4.2.4+cuda11.6.2.010",
            "TRTOSS_VERSION=22.08",
            "NSIGHT_SYSTEMS_VERSION=2022.1.3.18",
            "NSIGHT_COMPUTE_VERSION=2022.2.1.3",
            "DALI_VERSION=1.16.0",
            "DALI_BUILD=5322998",
            "DLPROF_VERSION=",
            "LD_LIBRARY_PATH=/opt/conda/lib/python3.8/site-packages/torch/lib:/opt/conda/lib/python3.8/site-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",
            "GDRCOPY_VERSION=2.3",
            "HPCX_VERSION=2.10",
            "MOFED_VERSION=5.4-rdmacore36.0",
            "OPENUCX_VERSION=1.12.0",
            "OPENMPI_VERSION=4.1.2rc4",
            "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=1.13.0a0+d321be6",
            "PYTORCH_VERSION=1.13.0a0+d321be6",
            "PYTORCH_BUILD_NUMBER=0",
            "NVIDIA_PYTORCH_VERSION=22.08",
            "NVM_DIR=/usr/local/nvm",
            "JUPYTER_PORT=8888",
            "TENSORBOARD_PORT=6006",
            "TORCH_CUDA_ARCH_LIST=5.2 6.0 6.1 7.0 7.5 8.0 8.6+PTX",
            "CUDA_HOME=/usr/local/cuda",
            "PYTORCH_HOME=/opt/pytorch/pytorch",
            "TORCH_ALLOW_TF32_CUBLAS_OVERRIDE=1",
            "USE_EXPERIMENTAL_CUDNN_V8_API=1",
            "COCOAPI_VERSION=2.0+nv0.6.1",
            "PYTHONIOENCODING=utf-8",
            "LC_ALL=en_US.UTF-8",
            "TORCH_CUDNN_V8_API_ENABLED=0",
            "CUDA_MODULE_LOADING=LAZY",
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            "LANG=en_US.UTF-8",
            "LANGUAGE=en_US.UTF-8",
            "TZ=Asia/Shanghai"
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        "Cmd": [
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        "ArgsEscaped": true,
        "Image": "",
        "Volumes": null,
        "WorkingDir": "/opt/bisheng-ft",
        "Entrypoint": [
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        "Labels": {
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            "com.nvidia.nccl.version": "2.12.12",
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            "com.nvidia.nsightcompute.version": "2022.2.1.3",
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            "com.nvidia.tensorrtoss.version": "22.08",
            "com.nvidia.volumes.needed": "nvidia_driver"
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    "Architecture": "amd64",
    "Os": "linux",
    "Size": 18693991784,
    "GraphDriver": {
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