innerlee

Ubuntu 15.10 have been released for a couple of days. It is a bleeding-edge system coming with Linux kernel 4.2 and GCC 5. However, compiling and running Caffe on this new system is no longer as smooth as on earlier versions. I have done some research related to this issue and finally find a way out. I summarize it here in this short tutorial and I hope more people and enjoy this new system without breaking their works.

Install NVIDIA Driver

The latest NVIDIA driver is officially included in Ubuntu 15.10 repositories. One can install it directly via apt-get.

sudo apt-get install nvidia-352-updates nvidia-modprobe

The nvidia-modprobe utility is used to load NVIDIA kernel modules and create NVIDIA character device files automatically everytime your machine boots up.

Reboot your machine and verify everything works by issuing nvidia-smi or running deviceQuery in CUDA samples.

innerlee

alabaster
argcomplete
babel
backports_abc
beautifulsoup4
bitarray
blaze ** 

bokeh
bottleneck

innerlee

/etc/default/grub
GRUB_CMDLINE_LINUX_DEFAULT="quiet splash acpi=off"
sudo grub-update

innerlee

# This script untars all the .tar file to their own folers
# 
# for all tar files
#   if not tarred, i.e., no dir with same name
#       tar it to its temp folder
#       rename this temp folder to filename

for tar in map(x->x[1:end-4], filter(x->isfile(x) && length(x) > 4 && x[end-3:end] == ".tar", readdir()))
    if(!isdir(tar))
        isdir("$tar.temp") && rm("$tar.temp") 

innerlee

# resize images to 256x256 using packages
#   identify -format "(%w,%h)" n12552309_5.JPEG
#   mogrify -resize 256x256! n12552309_10.JPEG

imgsize(img) = eval(parse(readstring(`identify -format "(%w,%h)" $img`)))
resize(img) = run(`mogrify -resize 256x256! $img`)

for folder in filter(x->isdir(x), readdir())
    println("\n>$folder")
    for img in filter(x->isfile("$folder/$x") && length(x)>5 && lowercase(x[end-4:end]) == ".jpeg", readdir(folder))

innerlee

$ tree -L 2 share/some/directory/ | tail -1
120 directories, 3 files

innerlee

h5ls
h5ls -d file.h5/dataset/

innerlee

ax = gca()
ax2 = ax[:twinx]()

innerlee

macro nowarn(expr)
    quote
        stderr = STDERR
        stream = open("/dev/null", "a")
        redirect_stderr(stream)
        result = $(esc(expr))
        redirect_stderr(stderr)
        close(stream)
        result
    end

innerlee

name: "Inception_Resnet2_Imagenet"
layer {
  name: "data"
  type: "Data"
  top: "data"
  top: "label"
  include {
    phase: TRAIN
  }
  transform_param {