Environment Setup for Torch and fast-neural-style on Ubuntu

1. Install CUDA 8.0 and CUDNN 5.1

Please refer to Setup CUDA / CUDNN and Chainer for deep learning on Ubuntu 16.04

2. Install Torch from Torch#GetStarted

# in a terminal, run the commands WITHOUT sudo
git clone https://github.com/torch/distro.git ~/torch --recursive cd ~/torch; bash install-deps; ./install.sh # On Linux with bash
source ~/.bashrc

3. Install lua dependencies from torch/rocks on GitHub

git clone https://github.com/torch/rocks

luarocks install totem-0-0.rockspec  && 

luarocks install util-0-0.rockspec  && 

luarocks install fn-0-0.rockspec  && 

luarocks install pprint-0-0.rockspec  && 

luarocks install logroll-0-0.rockspec  && 

luarocks install hdf5-20-0.rockspec  &&

4. Run a Torch project : fast-neural-style

git clone https://github.com/jcjohnson/fast-neural-style

 - Generate a styled image

th fast_neural_style.lua -model models/eccv16/starry_night.t7 -input_image images/content/chicago.jpg -output_image out.png

Setup CUDA / CUDNN and Chainer for deep learning on Ubuntu 16.04

。Install CUDA / CUDNN and Chainer with GPU enabled

1 . Install CUDA 8.0 ( Ubuntu 14.04 )

1. 1. download http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1404/x86_64/cuda-repo-ubuntu1404_8.0.44-1_amd64.deb
   2. sudo dpkg -i cuda-repo-ubuntu1404_8.0.44-1_amd64.deb
   3. sudo apt-get update
   4. sudo apt-get install cuda

2 . Install CUDNN 5.1 for CUDA 8.0

1. 1. Download https://developer.nvidia.com/compute/machine-learning/cudnn/secure/v5.1/prod/8.0/cudnn-8.0-linux-x64-v5.1-tgz
   2. Extract tgz file
   3. sudo cp lib64/* /usr/local/cuda/lib64/
   4. sudo cp include/* /usr/local/cuda/include/

3. Set environment to build Chainer

1. 1. export CFLAGS=-I/usr/local/cuda/include
   2. export LDFLAGS=-L/usr/local/cuda/lib64
   3. export LD_LIBRARY_PATH=/usr/local/cuda/lib64

4. pip install chainer --no-cache-dir -vvvv

5. Don't forget to setup the nvcc path
nano ~/.bashrc ( or nano ~/.zshrc if you use zsh :p )
add the following line to the end of the rc file
export PATH=/usr/local/cuda/bin:$PATH

。If you need image processing library on Python ...

pip install Pillow

。Chainer enable CPU multi-core

https://github.com/yusuketomoto/chainer-char-rnn/pull/24/commits/923003716d71de340a47a6ac4e719ea991ac0d59

。Install ffmpeg

wget https://johnvansickle.com/ffmpeg/releases/ffmpeg-release-64bit-static.tar.xz

tar xvf ffmpeg-release-64bit-static.tar

sudo cp ffmpeg-3.2-64bit-static/* /usr/local/bin/ 

Raspberry Pi 常用指令

Default Account password : pi / raspberry

。Machine Info Raspberry Pi B+ 

Architecture:          armv6l

Byte Order:            Little Endian

CPU(s):                1

On-line CPU(s) list:   0

Thread(s) per core:    1

Core(s) per socket:    1

Socket(s):             1

Model name:            ARMv6-compatible processor rev 7 (v6l)

CPU max MHz:           1000.0000

CPU min MHz:           700.0000

。Updating

http://raspberrypi.stackexchange.com/questions/164/how-do-i-update-software-and-firmware

sudo apt-get clean

sudo apt-get update && sudo apt-get -y upgrade && sudo apt-get -y dist-upgrade && sudo apt-get -y autoremove

。Firmware Updating

sudo apt-get install rpi-update

sudo rpi-update

。Screen

sudo apt-get install screen

http://raspi.tv/2012/using-screen-with-raspberry-pi-to-avoid-leaving-ssh-sessions-open

screen

screen -list

Reconnect : screen -r

。Show disk info / space

lsblk

df -h

show disk size： du -hs dic/*

。Python 

sudo apt-get install python-pip

。Crontab

 - 編輯 : crontab -e

 - 顯示執行 log : grep CRON /var/log/syslog

 - check status : sudo service cron status

 - restart : sudo service cron restart

。Git

 - Add and push files：

git add .
git commit -a -m "commit" (do not need commit message either)
git push

 - Remember Git login info：
git config --global credential.helper 'cache --timeout 360000'