ubuntu environment setting

init.sh

#!/bin/bash

# utils
cd ~/
mkdir proj lib
sudo apt-get update
sudo apt-get install -y git build-essential libatlas-base-dev
sudo apt-get install -y python3-dev
git config --global credential.helper 'cache --timeout=3600'
git config --global user.email "xxxx@xxxx.com"
git config --global user.name "xxxxxxx"

# anaconda
# http://stuarteberg.github.io/conda-docs/help/silent.html
wget --quiet https://repo.continuum.io/archive/Anaconda3-5.0.0-Linux-x86_64.sh -O lib/anaconda.sh
/bin/bash lib/anaconda.sh -b

echo export PATH=~/anaconda3/bin:$PATH >> ~/.bashrc
source ~/.bashrc

pip install xgboost
pip install lightgbm
pip install tensorflow
pip install keras
pip install hyperopt

# set backend for matplotlib to Agg
matplotlibrc_path=$(python -c "import site, os, fileinput; packages_dir = site.getsitepackages()[0]; print(os.path.join(packages_dir, 'matplotlib', 'mpl-data', 'matplotlibrc'))") && \
sed -i 's/^backend      : qt5agg/backend      : agg/' $matplotlibrc_path

# install gensim(word2vec is slow?)
pip install gensim

init_gpu.sh

# install CUDA Toolkit 8.0, cuDNN v6.
# https://developer.nvidia.com/cuda-80-ga2-download-archive

wget http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/7fa2af80.pub
cat 7fa2af80.pub | sudo apt-key add -

wget http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/cuda-repo-ubuntu1604_8.0.61-1_amd64.deb
sudo dpkg -i cuda-repo-ubuntu1604_8.0.61-1_amd64.deb
sudo apt update

sudo apt install -y linux-generic
sudo apt install -y cuda-8-0 # (no need cuda-drivers?)
sudo reboot

# after reboot ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
sudo apt remove linux-virtual
sudo apt autoremove
# rm 7fa2af80.pub cuda-repo-ubuntu1604_8.0.61-1_amd64.deb

source ~/.bashrc
echo export PATH="/usr/local/cuda-8.0/bin:$PATH" >> ~/.bashrc
echo export LD_LIBRARY_PATH="/usr/local/cuda/lib64:$LD_LIBRARY_PATH" >> ~/.bashrc

### run command in local ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# copy cudnn from local to server (require downloading in advance)
export address=xx.xx.xx.xx
export usrname=ubuntu
export keypath=xxxx.pem
scp -i $keypath ~/xxxx/cudnn-8.0-linux-x64-v6.0.tgz $usrname@$address:~/
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

# install cudnn
tar xzf cudnn-8.0-linux-x64-v6.0.tgz
sudo cp -a cuda/lib64/* /usr/local/lib/
sudo cp -a cuda/include/* /usr/local/include/
sudo ldconfig

# tensorflow
pip uninstall -y tensorflow
pip install tensorflow-gpu

某コンペの為に仕込んだ環境設定スクリプトです。（結局init_gpu.shは使わなかった…）
ubuntuの知識はかなり怪しいので、間違っているところがあるかもしれません。

• source init.sh で叩く必要があります

この辺を参考にしています

• https://qiita.com/yukoba/items/3692f1cb677b2383c983
• https://github.com/ContinuumIO/docker-images/blob/master/anaconda3/Dockerfile
• https://github.com/Kaggle/docker-python/blob/master/Dockerfile