Ubuntu 16.04 深度學(xué)習(xí)框架配置

Deep Learning Frameworks Configuration

主要是Ubuntu 16.04 + cuda7.5 + cudnn5.0 + python2 + Matlab2014b + theano0.8.2 + caffe的配置,但是Ubuntu 16.04 + cuda8.0 + cudnn5.0 + python2 + tensorflow + theano + opencv 3.2 + caffe也類似

主要參考
http://www.linuxidc.com/Linux/2016-07/132860.htm
http://blog.csdn.net/g0m3e/article/details/51420565
http://blog.csdn.net/yahag/article/details/51968004
http://blog.csdn.net/lien0906/article/details/46816243
http://blog.csdn.net/ubunfans/article/details/47724341

[TOC] 依然不支持。。。

1. 安裝依賴包

sudo apt-get install build-essential  # basic requirement
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 libgflags-dev libgoogle-glog-dev liblmdb-dev

2. 安裝nvidia顯卡驅(qū)動

添加官方源 sudo add-apt-repository ppa:graphics-drivers/ppa
在系統(tǒng)設(shè)置,Software&Updates中選Additional Drivers,選顯卡驅(qū)動,重啟
查看是否安裝成功 nvidia-settings

3. 安裝 cuda7.5 for ubuntu 15.04 runfile(local) (cuda 8.0類似)

# cd 到目錄文件
chmod 777 cuda_7.5.18_linux.run
sudo ./cuda_7.5.18_linux.run --override
# 注意不要再次安裝nvidia驅(qū)動
================Problem:==============
Missing recommended library: libGLU.so
Missing recommended library: libXmu.so

$ sudo apt-get install libglu1-mesa libxi-dev libxmu-dev libglu1-mesa-dev
$ sudo ln -s /usr/lib/x86_64-linux-gnu/libGLU.so /usr/lib/libGLU.so
$ sudo ln -s /usr/lib/x86_64-linux-gnu/libXmu.so /usr/lib/libXmu.so
$ sudo ldconfig
======================================

4.更新cudnn5.0動態(tài)庫,下載解壓

# cd到cudnn5.0解壓后的include目錄
sudo cp cudnn.h /usr/local/cuda/include/
# cd到lib64目錄
sudo cp lib* /usr/local/cuda/lib64/
# 建立鏈接
cd /usr/local/cuda/lib64/
sudo rm -rf libcudnn.so libcudnn.so.5
sudo ln -s libcudnn.so.5.0.5 libcudnn.so.5
sudo ln -s libcudnn.so.5 libcudnn.so
# 設(shè)置環(huán)境變量和動態(tài)鏈接庫
sudo gedit /etc/profile

# 末尾添加
# PATH=/usr/local/cuda/bin:$PATH
# export PATH

# 保存之后,創(chuàng)建鏈接文件
sudo vim /etc/ld.so.conf.d/cuda.conf

# 輸入
# /usr/local/cuda/lib64

# 使鏈接生效
sudo ldconfig

5. cuda用例安裝與測試

cd /usr/local/cuda-7.5/include
sudo cp host_config.h host_config.h.bak
sudo gedit host_config.h

# 找到下面這段
# if GNUC > 4 || (GNUC == 4 && GNUC_MINOR > 9) #改4為5
# error – unsupported GNU version! gcc versions later than 4.9 are not supported!
# endif /* GNUC > 4 || (GNUC == 4 && GNUC_MINOR > 9) */

# 編譯,測試
cd /usr/local/cuda/samples
sudo make all -j4
cd /usr/local/cuda/samples/bin/x86_64/linux/release
sudo ./deviceQuery

6. BLAS用Atlas

sudo apt-get install libatlas-base-dev

7. python配置

這一步更多的是為后面裝Theano做準(zhǔn)備,用pip 安裝numpy,scipy,解決依賴關(guān)系,這幾步可能出錯,至關(guān)重要。。。

sudo apt-get install python-pip
sudo pip install numpy
sudo pip install scipy

sudo pip install matplotlib ipython jupyter pandas sympy nose spyder
# (sudo apt-get install python-matplotlib ipython ipython-notebook python-pandas python-sympy python-nose)

pip install -U scikit-learn
# (測試sklearn nosetests -v sklearn)

# cd到caffe目錄python文件夾
sudo su
for req in $(cat requirements.txt); do pip install -i https://pypi.tuna.tsinghua.edu.cn/simple $req; done
# 如果第一次有很多紅字錯誤,再運(yùn)行幾遍指導(dǎo)安裝成功,對于黃字提示無需理會,可能是pip版本需要更新

# 測試numpy, scipy
python -c "import numpy;numpy.test()"
python -c "import scipy;scipy.test()"

8. 安裝Matlab2014b

http://www.lxweimin.com/p/f0cefc737dda

# 加入系統(tǒng)環(huán)境變量
sudo gedit /etc/profile

# PATH="$PATH:/opt/MATLAB/R2014b/bin"

source /etc/profile

matlab shortcuts設(shè)置
具體 HOME > ENVIRONMENT > Preferences > Keyboard > Shortcuts
然后把“Emacs Default Set”改成“Windows Default Set” 保存,OK!

9. OpenCV (!慎重,可能不成功)

安裝OpenCV3.1.0

sudo apt-get install libqt4-dev libopencv-dev build-essential cmake git libgtk2.0-dev pkg-config python-dev libdc1394-22
sudo apt-get install libdc1394-22-dev libjpeg-dev libpng12-dev libtiff5-dev libjasper-dev libavcodec-dev libavformat-dev
sudo apt-get install libswscale-dev libxine2-dev libgstreamer0.10-dev libgstreamer-plugins-base0.10-dev libv4l-dev
sudo apt-get install libtbb-dev  libfaac-dev libmp3lame-dev libopencore-amrnb-dev libopencore-amrwb-dev libtheora-dev
sudo apt-get install libvorbis-dev libxvidcore-dev x264 v4l-utils unzip

mkdir build
cd build/
cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local ..
make -j4
sudo make install

# 在/usr/local目錄下查找opencv庫所在位置,我在解答看到有人是在/usr/local/opencv和/usr/local/opencv2下面,
# 但我這里是在/usr/local/lib下找到的。如果找不到,可嘗試:

sudo updatedb && locate libopencv_core.so.3.1 # 3.1為版本號

# 新建文件:
sudo vim /etc/ld.so.conf.d/opencv.conf
#     寫入地址/usr/local/lib,并保存

sudo ldconfig -v

# ===================================== 不用
# 修改build文件夾下的flags.make(全部)
#
# CXX_FLAGS =  -fsigned-char
# 為(添加-O3 -fPIC)
# CXX_FLAGS =  -O3 -fPIC  -fsigned-char
# =====================================

10. 安裝tensorflow

兩種方式安裝:不通過源碼編譯的話,目前需要cuda8.0+cudnn5.0,按照官網(wǎng)指示安裝,比較簡單;源碼安裝容易出問題。

https://www.tensorflow.org/versions/r0.12/get_started/os_setup.html#pip-installation

# Ubuntu/Linux 64-bit, GPU enabled, Python 2.7
# Requires CUDA toolkit 8.0 and CuDNN v5. For other versions, see "Installing from sources" below.
export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-0.12.0rc1-cp27-none-linux_x86_64.whl

11. 配置caffe

# cd到caffe目錄
sudo cp Makefile.config.example Makefile.config
sudo gedit Makefile.config

# 將USE_CUDNN := 1 取消注釋,在
# INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include后面打上一個空格
# 添加/usr/include/hdf5/serial
# 這是因?yàn)閡buntu16.04的文件包含位置發(fā)生了變化,尤其是需要用到的hdf5的位置,所以需要更改這一路徑,
# 如果沒有這一句可能會報(bào)一個找不到hdf5.h的錯誤
# PYTHON_INCLUDE := /usr/include/python2.7 \
#   /usr/lib/python2.7/dist-packages/numpy/core/include先不做更改。
# 如果是需要生成matlab的caffe wrapper,取消注釋MATLAB_DIR然后替換為自己的目錄
# MATLAB_DIR := /opt/MATLAB/R2014b


# make之前先解決下面問題
# ================Problem:==============
# /usr/bin/ld: cannot find -lhdf5_hl
# /usr/bin/ld: cannot find -lhdf5
# collect2: error: ld returned 1 exit status
# Makefile:566: recipe for target '.build_release/lib/libcaffe.so.1.0.0-rc3' failed
# make: *** [.build_release/lib/libcaffe.so.1.0.0-rc3] Error 1
#
# 在打開的Makefile.config修改如下內(nèi)容:
# INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include
# LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib
# 修改為:
# INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include /usr/include/hdf5/serial
# libraryY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib
# 為hdf5之類的文件創(chuàng)建新的鏈接
#
# cd /usr/lib/x86_64-linux-gnu
# sudo ln -s libhdf5_serial.so.10.1.0 libhdf5.so
# sudo ln -s libhdf5_serial_hl.so.10.0.2 libhdf5_hl.so
# sudo ldconfig
# # 這里的10.1.0和10.0.2根據(jù)不同的系統(tǒng)可能對應(yīng)的數(shù)字會不同,比如在ubuntu15.10中其數(shù)字就是8.0.2.
#
# ======================================
#
# ================Problem:==============
# string.h ‘memcy’ was not declared in this scope
#
# 由于gcc編譯器版本太新,解決方法是打開makefile搜索并替換
# NVCCFLAGS += -ccbin=$(CXX) -Xcompiler -fPIC $(COMMON_FLAGS)
# 為
# NVCCFLAGS += -D_FORCE_INLINES -ccbin=$(CXX) -Xcompiler -fPIC $(COMMON_FLAGS)
# 保存退出
# ======================================

# cd到caffe目錄

make all -j4
make test -j4
make runtest
make matcaffe  # 可能g++版本太高,會有warning,但還是會編譯通過,不知道成功沒,沒用過
make pycaffe
make distribute

# 寫入系統(tǒng)環(huán)境變量
sudo gedit /etc/profile
# PYTHONPATH="/.../caffe-master/python:$PYTHONPATH"
# export PYTHONPATH
source /etc/profile
# 或者寫入用戶環(huán)境變量
sudo gedit ~/.bashrc
# export PYTHONPATH="/..../caffe-master/python:$PYTHONPATH"
source ~/.bashrc
# 之后編譯鏈接庫,打開python,輸入:

python
import caffe

至此caffe配置編譯完成#

12. 安裝Theano

sudo pip install theano
python -c "import theano; theano.test()"
# 這里theano.test()報(bào)錯很正常,不用管
sudo gedit ~/.theanorc

# [global]
# device=gpu
# floatX=float32
#
# [blas]
# ldflags=
#
# [cuda]
# root=/usr/local/cuda
#
# [nvcc]
# flags=-D_FORCE_INLINES

python
import theano
# Using gpu device 0: GeForce GT xxx (CNMeM is disabled, cuDNN 5005)
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