manjaro deep learning installation

gistfile1.txt

sudo mhwd -a pci nonfree 0300
pacman -S cuda cudnn
yaourt Ananconda
git clone https://github.com/fastai/fastai
cd fastai
conda-env create -f environment.yaml

build gcc 6
yay -S gcc6

yaourt -S Anaconda

sudo rm /opt/cuda/bin/gcc
sudo rm /opt/cuda/bin/g++

sudo ln -s /usr/bin/gcc-6 /opt/cuda/bin/gcc 
sudo ln -s /usr/bin/g++-6 /opt/cuda/bin/g++

git clone --recursive https://github.com/dmlc/xgboost
mkdir build && cd build
cmake -D CUDA_NVCC_FLAGS="-ccbin gcc-6" -DUSE_CUDA=ON .. && make

#mac openmp https://iscinumpy.gitlab.io/post/omp-on-high-sierra/
brew install libomp


sudo pacman -S boost
git clone --recursive https://github.com/Microsoft/LightGBM ; cd LightGBM
mkdir build ; cd build
cmake -DUSE_GPU=1 ..
# if you have installed NVIDIA CUDA to a customized location, you should specify paths to OpenCL headers and library like the following:
# cmake -DUSE_GPU=1 -DOpenCL_LIBRARY=/opt/cuda/lib64/libOpenCL.so -DOpenCL_INCLUDE_DIR=/opt/cuda/include/ ..
make -j4
conda install setuptools numpy scipy scikit-learn
python setup install

pip install lightgbm --install-option=--gpu --install-option="--opencl-include-dir=/opt/cuda/include/" --install-option="--opencl-library=/opt/cuda/lib64/libOpenCL.so"






sudo systemctl enable fstrim.timer
sudo systemctl start fstrim.timer

xset -b

xdg-mime default chromium.desktop x-scheme-handler/http
xdg-mime default chromium.desktop x-scheme-handler/https


#keyboard
yay xev

 xmodmap -pm
 xmodmap -pke
 
 clear mod1
clear mod4
keycode 64 =Super_L
keycode 133 = Alt_L
add mod1 = Alt_L 
add mod4 = Super_L

  xmodmap ~/.Xmodmap