安装caffe

拉取镜像

       nvidia/cuda:9.0-cudnn7-devel-centos7

1，换源

安装https://blog.csdn.net/tuomen5867/article/details/94406903

yum install make   必要安装

更换 yum 源和 epel 源：

cp /etc/yum.repos.d/CentOS-Base.repo /etc/yum.repos.d/CentOS-Base.repo.bak

wget -O /etc/yum.repos.d/CentOS-Base.repo http://mirrors.aliyun.com/repo/Centos-7.repo

# 更换 epel 源

wget -P /etc/yum.repos.d/ http://mirrors.aliyun.com/repo/epel-7.repo

# 清理缓存并生成新的缓存

yum clean all

yum makecache

---------------------------------------

更换 pip 源和 conda 源

 # Linux 下修改 pip 源：

# 修改 ~/.pip/pip.conf (没有就创建一个)，添加如下内容：

[global]

index-url = https://pypi.tuna.tsinghua.edu.cn/simple

# Linux 下修改 conda 源：

conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/

conda config --set show_channel_urls yes

 ------------------------------------------

2，#####安装 Caffe 需要的依赖库

安装

yum  -y install  epel-release

 yum install protobuf-devel leveldb-devel snappy-devel opencv-devel boost-devel hdf5-devel

 yum install gflags-devel glog-devel lmdb-devel

 yum install atlas-devel

  yum install python-devel

yum  -y install protobuf-devel leveldb-devel snappy-devel opencv-devel boost-devel hdf5-devel

yum  -y install gflags-devel glog-devel lmdb-devel   wget  unzip 

#将与 CUDA 和 CUDNN 相关路径设置成环境变量

# 将下面两行内容添加至文件 ~/.bashrc 最后：

export LD_LIBRARY_PATH=/usr/local/cuda-9.0/lib64:/usr/local/cuda-9.0/extras/CUPTI/lib64:$LD_LIBRARY_PATH

export CUDA_HOME=/usr/local/cuda-9.0/

# 添加成功之后执行：

source ~/.bashrc

3，安装 BLAS（可选

yum install atlas-devel   -y

cd /usr/lib64/atlas

ln -sv /usr/lib64/atlas/libsatlas.so.3.10 /usr/lib64/atlas/libcblas.so

ln -sv /usr/lib64/atlas/libsatlas.so.3.10 /usr/lib64/atlas/libatlas.so

报错：

 /usr/bin/ld: cannot find -lcblas

Same problem on centos 7.

commands

ln -s /usr/lib64/atlas/libtatlas.so /usr/lib64/libatlas.so

ln -s /usr/lib64/atlas/libsatlas.so /usr/lib64/libcblas.so

You should Install the libatlas-base-dev:

sudo apt-get install libatlas-base-dev

4，下载源码

从 https://github.com/BVLC/caffe.git 进行下载

wget   https://github.com/BVLC/caffe/archive/master.zip

安装 Python 依赖

安装pip

yum  install   python-pip    安装会报错，

升级下pip

pip install --upgrade pip

# 进入 ${CAFFE_HOME}/python/，执行

unzip  -d   /usr/local/    /usr/local/src/master.zip

/usr/local/caffe-master/python

/usr/local/caffe-master/python/requirements.txt

for req in $(cat /usr/local/caffe-master/python/requirements.txt); do pip3  install  -i https://pypi.tuna.tsinghua.edu.cn/simple $req; done 

还需要再跑

for req in $(cat requirements.txt); do pip install   -i https://pypi.tuna.tsinghua.edu.cn/simple  $req; done 

for req in $(cat requirements.txt); do pip3 install  -i https://pypi.tuna.tsinghua.edu.cn/simple  $req; done

这个是正确的，可以下载成功

for req in $(cat requirements.txt); do pip install   -i https://pypi.tuna.tsinghua.edu.cn/simple  $req; done

更改 Caffe 的配置文件

# 进入 Caffe 所在目录 CAFFE_HOME

cp Makefile.config.example Makefile.config # 做好备份

vi  Makefile.config # 打开文件并编辑

打开文件之后，按照如下内容酌情更改
配置参考
## Refer to http://caffe.berkeleyvision.org/installation.html

# Contributions simplifying and improving our build system are welcome!

# cuDNN acceleration switch (uncomment to build with cuDNN).

USE_CUDNN := 1

# CPU-only switch (uncomment to build without GPU support).

# CPU_ONLY := 1

# uncomment to disable IO dependencies and corresponding data layers

# USE_OPENCV := 0

# USE_LEVELDB := 0

# USE_LMDB := 0

# This code is taken from https://github.com/sh1r0/caffe-android-lib

# USE_HDF5 := 0

# uncomment to allow MDB_NOLOCK when reading LMDB files (only if necessary)

#	You should not set this flag if you will be reading LMDBs with any

#	possibility of simultaneous read and write

# ALLOW_LMDB_NOLOCK := 1

# Uncomment if you're using OpenCV 3

# OPENCV_VERSION := 3

# To customize your choice of compiler, uncomment and set the following.

# N.B. the default for Linux is g++ and the default for OSX is clang++

# CUSTOM_CXX := g++

# CUDA directory contains bin/ and lib/ directories that we need.

CUDA_DIR := /usr/local/cuda-9.0

# On Ubuntu 14.04, if cuda tools are installed via

# "sudo apt-get install nvidia-cuda-toolkit" then use this instead:

# CUDA_DIR := /usr

# CUDA architecture setting: going with all of them.

# For CUDA < 6.0, comment the *_50 through *_61 lines for compatibility.

# For CUDA < 8.0, comment the *_60 and *_61 lines for compatibility.

# For CUDA >= 9.0, comment the *_20 and *_21 lines for compatibility.

需要注释掉  For CUDA >= 9.0, comment the *_20 and *_21 lines for compatibility.

CUDA_ARCH := -gencode arch=compute_20,code=sm_20 \

		-gencode arch=compute_20,code=sm_21 \

		-gencode arch=compute_30,code=sm_30 \

		-gencode arch=compute_35,code=sm_35 \

		-gencode arch=compute_50,code=sm_50 \

		-gencode arch=compute_52,code=sm_52 \

		-gencode arch=compute_60,code=sm_60 \

		-gencode arch=compute_61,code=sm_61 \

		-gencode arch=compute_61,code=compute_61

# BLAS choice:

# atlas for ATLAS (default)

# mkl for MKL

# open for OpenBlas

BLAS := atlas

# Custom (MKL/ATLAS/OpenBLAS) include and lib directories.

# Leave commented to accept the defaults for your choice of BLAS

# (which should work)!

BLAS_INCLUDE := /usr/include/atlas

BLAS_LIB := /usr/lib64/atlas

# Homebrew puts openblas in a directory that is not on the standard search path

# BLAS_INCLUDE := $(shell brew --prefix openblas)/include

# BLAS_LIB := $(shell brew --prefix openblas)/lib

# This is required only if you will compile the matlab interface.

# MATLAB directory should contain the mex binary in /bin.

# MATLAB_DIR := /usr/local

# MATLAB_DIR := /Applications/MATLAB_R2012b.app

# NOTE: this is required only if you will compile the python interface.

# We need to be able to find Python.h and numpy/arrayobject.h.

# PYTHON_INCLUDE := /usr/include/python2.7 \

# 		/usr/lib/python2.7/dist-packages/numpy/core/include

# Anaconda Python distribution is quite popular. Include path:

# Verify anaconda location, sometimes it's in root.

#ANACONDA_HOME := $(HOME)/anaconda3

#PYTHON_INCLUDE := $(ANACONDA_HOME)/include \

		$(ANACONDA_HOME)/include/python3.6m \

		$(ANACONDA_HOME)/lib/python3.6/site-packages/numpy/core/include

# Uncomment to use Python 3 (default is Python 2)

PYTHON_LIBRARIES := boost_python python3.6m

# PYTHON_INCLUDE := /usr/include/python3.5m \

#                 /usr/lib/python3.5/dist-packages/numpy/core/include

# We need to be able to find libpythonX.X.so or .dylib.

# PYTHON_LIB := /usr/lib

#PYTHON_LIB := $(ANACONDA_HOME)/lib

# Homebrew installs numpy in a non standard path (keg only)

# PYTHON_INCLUDE += $(dir $(shell python -c 'import numpy.core; print(numpy.core.__file__)'))/include

# PYTHON_LIB += $(shell brew --prefix numpy)/lib

# Uncomment to support layers written in Python (will link against Python libs)

# WITH_PYTHON_LAYER := 1

# Whatever else you find you need goes here.

INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include /usr/local/cuda-9.0/include

LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib /usr/local/cuda-9.0/lib

# If Homebrew is installed at a non standard location (for example your home directory) and you use it for general dependencies

# INCLUDE_DIRS += $(shell brew --prefix)/include

# LIBRARY_DIRS += $(shell brew --prefix)/lib

# NCCL acceleration switch (uncomment to build with NCCL)

# https://github.com/NVIDIA/nccl (last tested version: v1.2.3-1+cuda8.0)

# USE_NCCL := 1

# Uncomment to use `pkg-config` to specify OpenCV library paths.

# (Usually not necessary -- OpenCV libraries are normally installed in one of the above $LIBRARY_DIRS.)

# USE_PKG_CONFIG := 1

# N.B. both build and distribute dirs are cleared on `make clean`

BUILD_DIR := build

DISTRIBUTE_DIR := distribute

# Uncomment for debugging. Does not work on OSX due to https://github.com/BVLC/caffe/issues/171

# DEBUG := 1

# The ID of the GPU that 'make runtest' will use to run unit tests.

TEST_GPUID := 0

# enable pretty build (comment to see full commands)

Q ?= @
完整的配置文件
/usr/local/src/master.zip

解压后

/usr/local/caffe-master

/usr/local/caffe-master/Makefile.config

## Refer to http://caffe.berkeleyvision.org/installation.html

# Contributions simplifying and improving our build system are welcome!

# cuDNN acceleration switch (uncomment to build with cuDNN).

USE_CUDNN := 1

# CPU-only switch (uncomment to build without GPU support).

# CPU_ONLY := 1

# uncomment to disable IO dependencies and corresponding data layers

# USE_OPENCV := 0

# USE_LEVELDB := 0

# USE_LMDB := 0

# This code is taken from https://github.com/sh1r0/caffe-android-lib

# USE_HDF5 := 0

# uncomment to allow MDB_NOLOCK when reading LMDB files (only if necessary)

#       You should not set this flag if you will be reading LMDBs with any

#       possibility of simultaneous read and write

# ALLOW_LMDB_NOLOCK := 1

# Uncomment if you're using OpenCV 3

# OPENCV_VERSION := 3

# To customize your choice of compiler, uncomment and set the following.

# N.B. the default for Linux is g++ and the default for OSX is clang++

# CUSTOM_CXX := g++

# CUDA directory contains bin/ and lib/ directories that we need.

CUDA_DIR := /usr/local/cuda-9.0

# On Ubuntu 14.04, if cuda tools are installed via

# "sudo apt-get install nvidia-cuda-toolkit" then use this instead:

# CUDA_DIR := /usr

# CUDA architecture setting: going with all of them.

# For CUDA < 6.0, comment the *_50 through *_61 lines for compatibility.

# For CUDA < 8.0, comment the *_60 and *_61 lines for compatibility.

# For CUDA >= 9.0, comment the *_20 and *_21 lines for compatibility.

#CUDA_ARCH := -gencode arch=compute_20,code=sm_20 \

#               -gencode arch=compute_20,code=sm_21 \

CUDA_ARCH :=    -gencode arch=compute_30,code=sm_30 \

                -gencode arch=compute_35,code=sm_35 \

                -gencode arch=compute_50,code=sm_50 \

                -gencode arch=compute_52,code=sm_52 \

                -gencode arch=compute_60,code=sm_60 \

                -gencode arch=compute_61,code=sm_61 \

                -gencode arch=compute_61,code=compute_61

# BLAS choice:

# atlas for ATLAS (default)

# mkl for MKL

# open for OpenBlas

BLAS := atlas

# Custom (MKL/ATLAS/OpenBLAS) include and lib directories.

# Leave commented to accept the defaults for your choice of BLAS

# (which should work)!

# BLAS_INCLUDE := /path/to/your/blas

# BLAS_LIB := /path/to/your/blas

BLAS_INCLUDE := /usr/include/atlas

BLAS_LIB := /usr/lib64/atlas

# Homebrew puts openblas in a directory that is not on the standard search path

# BLAS_INCLUDE := $(shell brew --prefix openblas)/include

# BLAS_LIB := $(shell brew --prefix openblas)/lib

# This is required only if you will compile the matlab interface.

# MATLAB directory should contain the mex binary in /bin.

# MATLAB_DIR := /usr/local

# MATLAB_DIR := /Applications/MATLAB_R2012b.app

# NOTE: this is required only if you will compile the python interface.

# We need to be able to find Python.h and numpy/arrayobject.h.

#PYTHON_INCLUDE := /usr/include/python2.7 \

                /usr/lib/python2.7/dist-packages/numpy/core/include

# Anaconda Python distribution is quite popular. Include path:

# Verify anaconda location, sometimes it's in root.

# ANACONDA_HOME := $(HOME)/anaconda

# PYTHON_INCLUDE := $(ANACONDA_HOME)/include \

                # $(ANACONDA_HOME)/include/python2.7 \

                # $(ANACONDA_HOME)/lib/python2.7/site-packages/numpy/core/include

# Uncomment to use Python 3 (default is Python 2)

# PYTHON_LIBRARIES := boost_python3 python3.5m

# PYTHON_INCLUDE := /usr/include/python3.5m \

#                 /usr/lib/python3.5/dist-packages/numpy/core/include

# We need to be able to find libpythonX.X.so or .dylib.

PYTHON_LIB := /usr/lib

# PYTHON_LIB := $(ANACONDA_HOME)/lib

# Homebrew installs numpy in a non standard path (keg only)

# PYTHON_INCLUDE += $(dir $(shell python -c 'import numpy.core; print(numpy.core.__file__)'))/include

# PYTHON_LIB += $(shell brew --prefix numpy)/lib

# Uncomment to support layers written in Python (will link against Python libs)

# WITH_PYTHON_LAYER := 1

# Whatever else you find you need goes here.

INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include /usr/local/cuda-9.0/include

LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib  /usr/local/cuda-9.0/lib

# If Homebrew is installed at a non standard location (for example your home directory) and you use it for general dependencies

# INCLUDE_DIRS += $(shell brew --prefix)/include

# LIBRARY_DIRS += $(shell brew --prefix)/lib

# NCCL acceleration switch (uncomment to build with NCCL)

# https://github.com/NVIDIA/nccl (last tested version: v1.2.3-1+cuda8.0)

# USE_NCCL := 1

# Uncomment to use `pkg-config` to specify OpenCV library paths.

# (Usually not necessary -- OpenCV libraries are normally installed in one of the above $LIBRARY_DIRS.)

# USE_PKG_CONFIG := 1

# N.B. both build and distribute dirs are cleared on `make clean`

BUILD_DIR := build

DISTRIBUTE_DIR := distribute

# Uncomment for debugging. Does not work on OSX due to https://github.com/BVLC/caffe/issues/171

# DEBUG := 1

# The ID of the GPU that 'make runtest' will use to run unit tests.

TEST_GPUID := 0

# enable pretty build (comment to see full commands)

Q ?= @
编译
编译 Caffe

make all

make test

make runtest

4. 测试 Caffe

运行 Caffe

进入Caffe 安装目录,执行./build/tools/caffe，可以根据caffe命令选项使用

2.MNIST 例子

进入Caffe目录，执行如下命令

# 下载数据集：

./data/mnist/get_mnist.sh

# 转换数据集：

./examples/mnist/create_mnist.sh

# 训练例子：

./examples/mnist/train_lenet.sh

 5. Caffe 的 Python 接口

执行一下命令即可得到 Caffe 的 Python 接口

# 进入 CAFFE_HOME

make pycaffe

# 在 ~/.bahsrc 添加以下内容，之后执行 source ~/.bashrc

export PATH=/root/caffe/python:$PATH

其他方案

centos7+cuda+cudnn+caffe环境安装

https://blog.csdn.net/u010344264/article/details/86558031

https://www.cnblogs.com/platero/p/3993877.html

操作：

安装  wget unzip

编译pycaffe

报错

make pycaffe时遇到致命错误，找不到Python.h文件

CXX/LD -o python/caffe/_caffe.so python/caffe/_caffe.cpppython/caffe/_caffe.cpp:1:52: fatal error: Python.h:

 找不到Python.h文件，其实是caffe的Makefile.config中anaconda路径不对，也就是Python路径。 

我从这个网页中找到了解决方法：make pycaffe fatal error: ‘Python.h’ file not found

在这篇博文中找到解决办法

因为我没有使用anaconda，所以手动添加路径

export CPLUS_INCLUDE_PATH=/usr/local/src/Python-3.6.4/Include/:$CPLUS_INCLUDE_PATH

然后make pycaffe就可以了。

 -----------------------------------------

 find     Python.h  添加起父目录到变量CPLUS_INCLUDE_PATH

CentOS 7 安装Python3以及pip3

一、添加epel源

yum install epel-release

二、安装Python3.4,装完再升级吧

yum install python34

三、安装pip3

yum install python34-setuptools

easy_install-3.4  pip

之后就可以使用pip3了，如：

pip3 install numpy

-----------------------------

安装setuptools

wget --no-check-certificate  https://pypi.python.org/packages/source/s/setuptools/setuptools-19.6.tar.gz#md5=c607dd118eae682c44ed146367a17e26

tar -zxvf setuptools-19.6.tar.gz

cd setuptools-19.6

python3 setup.py build

python3 setup.py install

设置软链接

ln -s /usr/local/python3/bin/pip3 /usr/bin/pip3

如软链接设置错误,删除软链接命令

rm -rf /usr/bin/pip3(后面/usr/bin/pip为软链接名称,切记不能加结尾/  如:/usr/bin/pip3/则表示删除软连接及真实文件)

回到根目录

cd /

输入pip3 -V查看pip版本,安装成功则正确显示版本

问题

Caffe-GPU编译问题：nvcc fatal : Unsupported gpu architecture 'compute_20'

NVCC src/caffe/layers/bnll_layer.cu

nvcc fatal   : Unsupported gpu architecture 'compute_20'

Makefile:594: recipe for target '.build_release/cuda/src/caffe/layers/bnll_layer.o' failed

make: *** [.build_release/cuda/src/caffe/layers/bnll_layer.o] Error 1

make: *** Waiting for unfinished jobs....

 CUDA9.0所以把下面这两行删除就可以了

-gencode arch=compute_20,code=sm_20 \

-gencode arch=compute_20,code=sm_21 \
安装过程简版
完整的操作
 1  wget -O /etc/yum.repos.d/CentOS-Base.repo http://mirrors.aliyun.com/repo/Centos-7.repo

    2  yum  install  wget

    3  wget -O /etc/yum.repos.d/CentOS-Base.repo http://mirrors.aliyun.com/repo/Centos-7.repo

    4  wget -P /etc/yum.repos.d/ http://mirrors.aliyun.com/repo/epel-7.repo

    5  yum clean all

    6  yum makecache

    7  yum install protobuf-devel leveldb-devel snappy-devel opencv-devel boost-devel hdf5-devel

    8  yum install gflags-devel glog-devel lmdb-devel

    9  echo  $LD_LIBRARY_PATH

   10  nvcc  -v

   11  nvcc  -V

   12  export LD_LIBRARY_PATH=/usr/local/cuda-9.0/lib64:/usr/local/cuda-9.0/extras/CUPTI/lib64:$LD_LIBRARY_PATH

   13  echo  $LD_LIBRARY_PATH

   14  export CUDA_HOME=/usr/local/cuda-9.0/

   15  yum install atlas-devel

   16  cd /usr/lib64/atlas

   17  ln -sv libsatlas.so.3.10 libcblas.so

   18  ln -sv libsatlas.so.3.10 libatlas.so

   19  cd  /usr/local/src/

   20  ll

   21  wget   https://github.com/BVLC/caffe/archive/master.zip

   22  ll

   23  unzip   master.zip

   24  yum -y install  unzip

   25  yum-complete-transaction --cleanup-only

   26  unzip  master.zip

   27  cd caffe-master/

   28  ll

   29  cd  python/

   30  ll

   31  for req in $(cat requirements.txt); do pip -i https://pypi.tuna.tsinghua.edu.cn/simple install $req; done

   32  yum  install   python-pip

   33  for req in $(cat requirements.txt); do pip -i https://pypi.tuna.tsinghua.edu.cn/simple install $req; done

   34  for req in $(cat requirements.txt); do pip install   -i https://pypi.tuna.tsinghua.edu.cn/simple  $req; done

   35  pip install --upgrade pip

   36  for req in $(cat requirements.txt); do pip install   -i https://pypi.tuna.tsinghua.edu.cn/simple  $req; done

   37  yum install zlib-devel bzip2-devel openssl-devel ncurses-devel sqlite-devel readline-devel tk-devel gcc make

   38  cd  /usr/local/src/

   39  wget https://www.python.org/ftp/python/3.6.4/Python-3.6.4.tar.xz

   40  yum   install  xz

   41  xz -d Python-3.6.4.tar.xz

   42  tar -xf Python-3.6.4.tar

   43  cd  Python-3.6.4

   44  ./configure prefix=/usr/local/python3

   45  make && make install

   46  #进入解压后的目录，依次执行下面命令进行手动编译

   47  mv /usr/bin/python /usr/bin/python.bak

   48  ln -s /usr/local/python3/bin/python3.6 /usr/bin/python

   49  python -V

   50  vi /usr/bin/yum

   51  vi /usr/libexec/urlgrabber-ext-down

   52  cd  ../caffe-master/python/

   53  ll

   54  for req in $(cat requirements.txt); do pip install   -i https://pypi.tuna.tsinghua.edu.cn/simple  $req; done

   55  for req in $(cat requirements.txt); do pip install   -i https://pypi.tuna.tsinghua.edu.cn/simple  $req; done

   56  for req in $(cat requirements.txt); do pip install   -i https://pypi.tuna.tsinghua.edu.cn/simple  $req; done

   57  python

   58  for req in $(cat requirements.txt); do pip install     $req; done

   59  whereis  python

   60  mv /usr/bin/python2.7{,bak}

   61  for req in $(cat requirements.txt); do pip install     $req; done

   62  pip

   63  ll

   64  cd    /usr/local/src/

   65  ll

   66  wget --no-check-certificate  https://pypi.python.org/packages/source/s/setuptools/setuptools-19.6.tar.gz#md5=c607dd118eae682c44ed146367a17e26

   67  tar -zxvf setuptools-19.6.tar.gz

   68  cd    setuptools-19.6

   69  python   setup.py build

   70  python  setup.py install

   71  ln -s /usr/local/python3/bin/pip3 /usr/bin/pip3

   72  cd   -

   73  cd /usr/local/src/caffe-master/python/

   74  pip3

   75  for req in $(cat requirements.txt); do pip3  install   -i https://pypi.tuna.tsinghua.edu.cn/simple  $req; done

   76  history

   77  cp Makefile.config.example Makefile.config

   78  cd ..

   79  ll

   80  cp Makefile.config.example Makefile.config

   81  vim Makefile.conig

   82  vi   Makefile.conig

   83  vi   Makefile.config

   84  make all

   85  yum install protobuf-devel leveldb-devel snappy-devel opencv-devel boost-devel hdf5-devel

   86  mv  /usr/bin/python2.7bak     /usr/bin/python2.7

   87  yum install protobuf-devel leveldb-devel snappy-devel opencv-devel boost-devel hdf5-devel

   88  yum install gflags-devel glog-devel lmdb-devel

   89  make all

   90  make test

   91  make runtest

   92  history

dockerfile



FROM  nvidia/cuda:9.0-cudnn7-devel-centos7

MAINTAINER      yon@Dxa.com

ENV      LD_LIBRARY_PATH   /usr/local/cuda-9.0/lib64:/usr/local/cuda-9.0/extras/CUPTI/lib64:$LD_LIBRARY_PATH

ENV      CUDA_HOME         /usr/local/cuda-9.0/

RUN      yum   -y  install  make   wget     \

      &&   wget -O /etc/yum.repos.d/CentOS-Base.repo http://mirrors.aliyun.com/repo/Centos-7.repo   \

      &&   wget -P /etc/yum.repos.d/ http://mirrors.aliyun.com/repo/epel-7.repo                     \

      &&   yum clean all    &&   yum makecache

RUN  yum  -y   install zlib-devel bzip2-devel openssl-devel ncurses-devel sqlite-devel readline-devel tk-devel gcc

RUN  wget -O   /usr/local/src/Python-3.6.4.tar.xz   https://www.python.org/ftp/python/3.6.4/Python-3.6.4.tar.xz    \

     &&  cd   /usr/local/src/  &&  xz -d       Python-3.6.4.tar.xz  &&  tar -xf      Python-3.6.4.tar             \

     &&  cd   /usr/local/src/Python-3.6.4   &&  ./configure prefix=/usr/local/python3     &&  make && make install

RUN  mv /usr/bin/python /usr/bin/python.bak   \

     &&  ln -s /usr/local/python3/bin/python3.6 /usr/bin/python

修改pip3 链接

rm -rf /usr/bin/pip*

ln -s  /usr/local/python3/bin/pip3   /usr/bin/pip3

ln -s  /usr/bin/pip3  /usr/bin/pip

-------------------------------------------------------------------------------------------

#caffe  依赖

yum  -y install protobuf-devel leveldb-devel snappy-devel opencv-devel boost-devel hdf5-devel

yum  -y install gflags-devel glog-devel lmdb-devel   unzip

#BLAS

yum install atlas-devel   -y

cd /usr/lib64/atlas

ln -sv /usr/lib64/atlas/libsatlas.so.3.10 /usr/lib64/atlas/libcblas.so

ln -sv /usr/lib64/atlas/libsatlas.so.3.10 /usr/lib64/atlas/libatlas.so

-----------------------------------------

wget   -O /usr/local/src/master.zip    https://github.com/BVLC/caffe/archive/master.zip

unzip  -d   /usr/local/    /usr/local/src/master.zip

for req in $(cat /usr/local/caffe-master/python/requirements.txt); do pip3  install  -i https://pypi.tuna.tsinghua.edu.cn/simple $req; done 

配置文件

/usr/local/caffe-master/Makefile.config 

make all

make test

make runtest

完整的dockefile

cat  /gputest/caffe/Dockerfile

FROM  nvidia/cuda:9.0-cudnn7-devel-centos7

MAINTAINER      yon@D

ENV      LD_LIBRARY_PATH   /usr/local/cuda-9.0/lib64:/usr/local/cuda-9.0/extras/CUPTI/lib64:$LD_LIBRARY_PATH

ENV      CUDA_HOME         /usr/local/cuda-9.0/

RUN        yum   -y  install  make   wget     \

      &&   wget -O /etc/yum.repos.d/CentOS-Base.repo http://mirrors.aliyun.com/repo/Centos-7.repo   \

      &&   wget -P /etc/yum.repos.d/ http://mirrors.aliyun.com/repo/epel-7.repo                     \

      &&   yum clean all    &&   yum makecache

RUN        yum  -y   install zlib-devel bzip2-devel openssl-devel ncurses-devel sqlite-devel readline-devel tk-devel gcc

RUN        wget -O   /usr/local/src/Python-3.6.4.tar.xz   https://www.python.org/ftp/python/3.6.4/Python-3.6.4.tar.xz    \

     &&    cd   /usr/local/src/  &&  xz -d       Python-3.6.4.tar.xz  &&  tar -xf      Python-3.6.4.tar             \

     &&    cd   /usr/local/src/Python-3.6.4   &&  ./configure prefix=/usr/local/python3     &&  make && make install

RUN        mv /usr/bin/python /usr/bin/python.bak   \

     &&    ln -s /usr/local/python3/bin/python3.6 /usr/bin/python    && rm -rf /usr/bin/pip*   \

     &&    ln -s  /usr/local/python3/bin/pip3   /usr/bin/pip3   \

     &&    ln -s  /usr/bin/pip3  /usr/bin/pip 

#caffe  依赖

RUN        sed  -i  's@/usr/bin/python@/usr/bin/python2@'  /usr/bin/yum     \

     &&    sed  -i  's@/usr/bin/python@/usr/bin/python2@'  /usr/libexec/urlgrabber-ext-down  \

     &&    yum  -y install protobuf-devel leveldb-devel snappy-devel opencv-devel boost-devel hdf5-devel  gflags-devel glog-devel lmdb-devel  unzip  atlas-devel  \

     &&    ln -sv /usr/lib64/atlas/libsatlas.so.3.10 /usr/lib64/atlas/libcblas.so   \

     &&    ln -sv /usr/lib64/atlas/libsatlas.so.3.10 /usr/lib64/atlas/libatlas.so

RUN        wget   -O /usr/local/src/master.zip    https://github.com/BVLC/caffe/archive/master.zip    \

     &&    unzip  -d   /usr/local/    /usr/local/src/master.zip

#Python  依赖

RUN       for req in $(cat /usr/local/caffe-master/python/requirements.txt); do pip3  install  -i https://pypi.tuna.tsinghua.edu.cn/simple $req; done   

COPY     Makefile.config   /usr/local/caffe-master/Makefile.config 

RUN     cd  /usr/local/caffe-master/    &&   make all  &&   make test   && make runtest


  容器内安装

    2  wget -O /etc/yum.repos.d/CentOS-Base.repo http://mirrors.aliyun.com/repo/Centos-7.repo

    3  yum   install   wget

    4  wget -O /etc/yum.repos.d/CentOS-Base.repo http://mirrors.aliyun.com/repo/Centos-7.repo

    5  yum  clean  all

    6  yum  makecache

    7  yum install protobuf-devel leveldb-devel snappy-devel opencv-devel boost-devel hdf5-devel

    8  yum install gflags-devel glog-devel lmdb-devel   bzip2  unzip

    9  ll

   10  mv  caffe-master.zip   /usr/local/src/

   11  ll

   12  cd /usr/local/src/

   13  ll

   14  unzip  caffe-master.zip

   15  ll

   16  ln  -sv  /usr/local/src/caffe-master   /usr/local/caffe

   17  cd  /usr/local/caffe/

   18  ll

   19  yum  install  gcc   make

   20  yum install atlas-devel

   21  cd  /usr/lib64/atlas

   22  ll

   23  ln -sv libsatlas.so.3.10 libcblas.so

   24  ln -sv libsatlas.so.3.10 libatlas.so

   25  cd  /usr/local/caffe/

   26  ll

   27  cp Makefile.config.example Makefile.config

   28  vi  Makefile.config

   29  yum install gcc gcc-c++

   30  yum install  opencv-devel

   31  yum install  opencv

   32  find  /   -name  "*opencv*"

   33  vi  Makefile.confi

   34  vi  Makefile.config

   35  make  all

   36  yum install gflags-devel glog-devel lmdb-devel

   37  yum  install   epel-release

   38  yum install gflags-devel glog-devel lmdb-devel

   39  make clean

   40  make  all

   41  yum  install  hdf5-devel

   42  make clean

   43  make  all

   44   yum install protobuf-devel leveldb-devel snappy-devel opencv-devel boost-devel hdf5-devel

   45  yum install gflags-devel glog-devel lmdb-devel

   46  yum install atlas-devel

   47  make clean

   48  make  all

   49  yum install atlas-devel

   50  find  /  -name  lcblas

   51  find  /  -name  "*lcblas*"

   52  yum install atlas

   53  yum install cblas

   54  cd /usr/lib64/atlas

   55  ll

   56  ln -sv /usr/lib64/atlas/libsatlas.so.3.10 /usr/lib64/atlas/libcblas.so

   57  ldconfig

   58  ln -s /usr/lib64/atlas/libtatlas.so /usr/lib64/libatlas.so

   59  ln -s /usr/lib64/atlas/libsatlas.so /usr/lib64/libcblas.so

   60  cd -

   61  ll

   62  make clean

   63  make  all

   64  make install

   65  make  test

   66  make   runtest

   67  cd   /root/

   68  ll

   69  ll

   70  export PATH=/root/anaconda3/bin:$PATH

   71  vi  .bashrc

   72  cd /

   73  ll

   74  vi  python_service.py

   75  echo  $PATH

   76  history

安装后测试

1.准备数据

cd caffe

sudo ./data/mnist/get_mnist.sh #下载数据集

sudo ./examples/mnist/create_mnist.sh #转换格式

2.训练

sudo ./examples/mnist/train_lenet.sh

nvidia-docker run -d --name ckernel -p 5002:8888 -v /home:/data jupyter_ckernel_v1

c++测试



class Rectangle {

    private:

        double w;

        double h;

    public:

        Rectangle(double w_, double h_) {

            w = w_;

            h = h_;

        }

        double area(void) {

            return w * h;

        }

        double perimiter(void) {

            return 2 * (w + h);

        }

};

Rectangle r = Rectangle(5, 4);

r.area();

jupyter安装c++



conda install -c conda-forge jupyterlab

conda install -c conda-forge xeus-cling

cpu only 安装

最初的命令：

    1  yum  -y isntall  wget  bzip2

    2  yum  -y install  wget  bzip2

    3   wget  https://mirrors.tuna.tsinghua.edu.cn/anaconda/archive/Anaconda3-5.3.1-Linux-x86_64.sh

    4  wget https://repo.continuum.io/archive/Anaconda3-5.1.0-Linux-x86_64.sh

    5  chmod  + x

    6  chmod  + x Anaconda3-5.1.0-Linux-x86_64.sh

    7  chmod  +x Anaconda3-5.1.0-Linux-x86_64.sh

    8  rm  -rf  Anaconda3-5.3.1-Linux-x86_64.sh

    9  ll

   10  ./Anaconda3-5.1.0-Linux-x86_64.sh   -h

   11  ./Anaconda3-5.1.0-Linux-x86_64.sh     -b

   12  yum install protobuf-devel leveldb-devel snappy-devel opencv-devel boost-devel hdf5-devel openblas-devel gflags-devel glog-devel lmdb-devel

   13  yum   install  epel-release

   14  yum install protobuf-devel leveldb-devel snappy-devel opencv-devel boost-devel hdf5-devel openblas-devel gflags-devel glog-devel lmdb-devel

   15  yum  install  git

   16  cd

   17  ll

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

   19  ll

   20  cd  caffe/

   21  ll

   22  yum  install  gcc-c++

   23  ll

   24  cp  Makefile.config.example Makefile.config

   25  vi  Makefile.config

   26  vi  Makefile.config

   27  make

   28  yum  install  make

   29  make   all

   30  yum  install  atlas-devel

   31  make  clean

   32  make   all

   33  vi  Makefile.config

   34  make clean

   35  make   all

   36  make   test

   37  make   runtest

   38  history 


## Refer to http://caffe.berkeleyvision.org/installation.html

# Contributions simplifying and improving our build system are welcome!

# cuDNN acceleration switch (uncomment to build with cuDNN).

# USE_CUDNN := 1

# CPU-only switch (uncomment to build without GPU support).

 CPU_ONLY := 1

# uncomment to disable IO dependencies and corresponding data layers

# USE_OPENCV := 0

# USE_LEVELDB := 0

# USE_LMDB := 0

# This code is taken from https://github.com/sh1r0/caffe-android-lib

# USE_HDF5 := 0

# uncomment to allow MDB_NOLOCK when reading LMDB files (only if necessary)

#       You should not set this flag if you will be reading LMDBs with any

#       possibility of simultaneous read and write

# ALLOW_LMDB_NOLOCK := 1

# Uncomment if you're using OpenCV 3

# OPENCV_VERSION := 3

# To customize your choice of compiler, uncomment and set the following.

# N.B. the default for Linux is g++ and the default for OSX is clang++

# CUSTOM_CXX := g++

# CUDA directory contains bin/ and lib/ directories that we need.

#CUDA_DIR := /usr/local/cuda

# On Ubuntu 14.04, if cuda tools are installed via

# "sudo apt-get install nvidia-cuda-toolkit" then use this instead:

# CUDA_DIR := /usr

# CUDA architecture setting: going with all of them.

# For CUDA < 6.0, comment the *_50 through *_61 lines for compatibility.

# For CUDA < 8.0, comment the *_60 and *_61 lines for compatibility.

# For CUDA >= 9.0, comment the *_20 and *_21 lines for compatibility.

#CUDA_ARCH := -gencode arch=compute_20,code=sm_20 \

#               -gencode arch=compute_20,code=sm_21 \

##              -gencode arch=compute_30,code=sm_30 \

#               -gencode arch=compute_35,code=sm_35 \

#               -gencode arch=compute_50,code=sm_50 \

#               -gencode arch=compute_52,code=sm_52 \

#               -gencode arch=compute_60,code=sm_60 \

#               -gencode arch=compute_61,code=sm_61 \

#               -gencode arch=compute_61,code=compute_61

# BLAS choice:

# atlas for ATLAS (default)

# mkl for MKL

# open for OpenBlas

BLAS := open

# Custom (MKL/ATLAS/OpenBLAS) include and lib directories.

# Leave commented to accept the defaults for your choice of BLAS

# (which should work)!

# BLAS_INCLUDE := /path/to/your/blas

# BLAS_LIB := /path/to/your/blas

# Homebrew puts openblas in a directory that is not on the standard search path

# BLAS_INCLUDE := $(shell brew --prefix openblas)/include

# BLAS_LIB := $(shell brew --prefix openblas)/lib

# This is required only if you will compile the matlab interface.

# MATLAB directory should contain the mex binary in /bin.

# MATLAB_DIR := /usr/local

# MATLAB_DIR := /Applications/MATLAB_R2012b.app

# NOTE: this is required only if you will compile the python interface.

# We need to be able to find Python.h and numpy/arrayobject.h.

#PYTHON_INCLUDE := /usr/include/python2.7 \

                /usr/lib/python2.7/dist-packages/numpy/core/include

# Anaconda Python distribution is quite popular. Include path:

# Verify anaconda location, sometimes it's in root.

 ANACONDA_HOME := $HOME/anaconda3

 PYTHON_INCLUDE := $ANACONDA_HOME/include \

                 $ANACONDA_HOME/include/python3.6m \

                 $ANACONDA_HOME/lib/python3.6/site-packages/numpy/core/include

# Uncomment to use Python 3 (default is Python 2)

 PYTHON_LIBRARIES := boost_python3 python3.6m

# PYTHON_INCLUDE := /usr/include/python3.5m \

#                 /usr/lib/python3.5/dist-packages/numpy/core/include

# We need to be able to find libpythonX.X.so or .dylib.

#PYTHON_LIB := /usr/lib

PYTHON_LIB := $ANACONDA_HOME/lib

# Homebrew installs numpy in a non standard path (keg only)

# PYTHON_INCLUDE += $(dir $(shell python -c 'import numpy.core; print(numpy.core.__file__)'))/include

# PYTHON_LIB += $(shell brew --prefix numpy)/lib

# Uncomment to support layers written in Python (will link against Python libs)

# WITH_PYTHON_LAYER := 1

# Whatever else you find you need goes here.

INCLUDE_DIRS := $PYTHON_INCLUDE /usr/local/include

LIBRARY_DIRS := $PYTHON_LIB /usr/local/lib /usr/lib

# If Homebrew is installed at a non standard location (for example your home directory) and you use it for general dependencies

# INCLUDE_DIRS += $(shell brew --prefix)/include

# LIBRARY_DIRS += $(shell brew --prefix)/lib

# NCCL acceleration switch (uncomment to build with NCCL)

# https://github.com/NVIDIA/nccl (last tested version: v1.2.3-1+cuda8.0)

# USE_NCCL := 1

# Uncomment to use `pkg-config` to specify OpenCV library paths.

# (Usually not necessary -- OpenCV libraries are normally installed in one of the above $LIBRARY_DIRS.)

# USE_PKG_CONFIG := 1

# N.B. both build and distribute dirs are cleared on `make clean`

BUILD_DIR := build

DISTRIBUTE_DIR := distribute

# Uncomment for debugging. Does not work on OSX due to https://github.com/BVLC/caffe/issues/171

# DEBUG := 1

# The ID of the GPU that 'make runtest' will use to run unit tests.

TEST_GPUID := 0

# enable pretty build (comment to see full commands)

Q ?= @

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