Installation of common tools for deep learning under Linux

1.Matlab 64bit Installation

(a) installation package download

Baidu Network disk: [Https://pan.baidu.com/s/1gf9IeCN], Password: 4gj3

Two Vmware uses Windows shared directory

You need to turn off the system when you change the virtual machine settings, the suspend state can not be set, the Linux shared directory is located in/mnt/hgfs

(iii) Mount image file

Enter the following command in the terminal:

cd/mnt/hgfs/

sudo mount-o loop Thunderbolt Download/r2015b_glnxa64.iso/media/matlab/

(iv) Implementation of the installation

Enter the following command in the terminal:

Cd/media

mkdir matlab

sudo./install

　　

　　

(v) crack

Copy the libmwservices.so under the crack folder to/usr/local/matlab/r2014a/bin/glnxa64

Enter the following command in the terminal:

　　cd/usr/local/matlab/r2015b/bin/

sudo./matlab

　　

　　

　　cd/mnt/hgfs/Thunder Download/matlab\ 2015b\ linux64\ crack/r2015b/bin/

sudo cp-r glnxa64/usr/local/matlab/r2015b/bin/

(v) Run the test

Whether the run test cracked successfully

Enter the following command in the terminal:

cd/usr/local/matlab/r2015b/bin/

sudo./matlab

2.caffe Installation

(a) Configure the Apt-get source for the domestic server, backup the original configuration file, update the address for the Tsinghua Mirror or Ali Mirror

Enter the following command in the terminal:

Cd/etc/apt

sudo cp sources.list Sources.list.bak

VI sources.list　

　

# default Comment source image to improve apt update speed, if necessary, can be self-uncomment
Deb https://mirrors.tuna.tsinghua.edu.cn/ubuntu/xenial main restricted Universe Multiverse
# deb-src https://mirrors.tuna.tsinghua.edu.cn/ubuntu/xenial main restricted universe Multiver SE
deb https://mirrors.tuna.tsinghua.edu.cn/ubuntu/xenial-updates main restricted universe Multiverse
# DEB-SR C Https://mirrors.tuna.tsinghua.edu.cn/ubuntu/xenial-updates main restricted universe Multiverse
Deb https:// Mirrors.tuna.tsinghua.edu.cn/ubuntu/xenial-backports main restricted universe Multiverse
# DEB-SRC https:// Mirrors.tuna.tsinghua.edu.cn/ubuntu/xenial-backports main restricted universe Multiverse
Deb https:// Mirrors.tuna.tsinghua.edu.cn/ubuntu/xenial-security main restricted universe Multiverse
# DEB-SRC https:// Mirrors.tuna.tsinghua.edu.cn/ubuntu/xenial-security main restricted universe multiverse

# Pre-release software source, not recommended to enable
# deb Https://mirrors.tuna.tsinghua.edu.cn/ubuntu/xenial-proposed main restricted universe multiverse
# deb-src https://mirrors.tuna.tsinghua.edu.cn/ubuntu/xenial-proposed main restricted universe multiverse

(ii) Dependency package installation

Enter the following command in the terminal:

sudo apt-get update

sudo apt-get install git

　　sudo apt-get install Libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev libhdf5-serial-dev Protobuf-compiler

sudo apt-get install--no-install-recommends libboost-all-dev

sudo apt-get install Libatlas-base-dev

sudo apt-get install Python-dev

sudo apt-get install Libgflags-dev libgoogle-glog-dev Liblmdb-dev

(c) Caffe source download

git clone https://github.com/bvlc/caffe.git

CD caffe/

MV Makefile.config.example Makefile.config

(iv) implementation of the compilation

Modify Makefile.config, open cpu_only option, save;

The 6th line shall be amended to

# cpu-only switch (uncomment to build without GPU support).
Cpu_only: = 1

The 85th line is amended to

include_dirs: = $ (python_include)/usr/local/include/usr/include/hdf5/serial/

Modify makefile File 173 lines

LIBRARIES + = Glog gflags protobuf boost_system boost_filesystem m hdf5_serial_hl hdf5_serial

　　Perform the compilation

　　Make–j4

Make Test -j4

Make Runtest -j4

　　Compilation succeeds when passed results are returned

Compilation of 3.Matconvnet

(i) Open matlab

　　cd/usr/local/matlab/r2015b/bin/

sudo./matlab

(ii) Locate the Matconvnet directory and perform the compilation

cd/usr/local/matlab/r2015b/bin/

Vl_setupnn

Vl_compilenn (' verbose ',1)

Installation of 4.CUDA and CUDNN

Cuda is the Nvidia programming language platform, and the use of CUDA,CUDNN is a library of GPU-accelerated computing deep neural networks.

　　

Installation of common tools for deep learning under Linux