object_detection mlperf

object_detection_mlperf.txt

// use nvidia/cuda:10.0-cudnn7-devel-centos7 as BASE


// Ensure below paths are set to access nvcc at $CUDA_HOME/bin
export CUDA_HOME=/usr/local/cuda
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64
export PATH=$PATH:$CUDA_HOME/bin

// Install mentions GCC>=4.9. update to devtoolset-7
// use python 3.6
gcc --version
python --version
yum install -y centos-release-scl
yum install devtoolset-7 rh-python36 -y
source scl_source enable rh-python36 devtoolset-7
# enable in Dockerfile like this https://github.com/sub-mod/mnist-app/blob/master/Dockerfile.nodejs#L58
python --version
gcc --version

// install dependencies
pip install --upgrade pip
pip3 install yacs==0.1.5 cython==0.29.5  matplotlib==3.0.2 opencv-python==4.0.0.21   mlperf_compliance==0.0.10  gsutil  Pillow==5.4.1  tqdm==4.19.9   numpy ipython==7.2.0  torch==1.0.1.post2 torchvision==0.2.2 ninja==1.8.2.post2

// install dependencies
git clone https://github.com/cocodataset/cocoapi.git
cd cocoapi/PythonAPI
python setup.py build_ext install


// Build maskrcnn benchmark extension
// needs nvcc so you the devel image
cd ../..
git clone https://github.com/mlperf/training
cd training/
cd object_detection/
pip uninstall torch; pip uninstall torch
pip install torch==1.0.1.post2
cd pytorch
python setup.py build develop