y下载 https://github.com/BVLC/caffe https://github.com/BVLC/caffe/archive/master.zip gcc
caffe安装 有2个问题 ：
1，镜像系统类型，版本要求
2，是否使用cudnn(gpu) caffe要调用cudnn部分文件编译 (如用，cuda cudnn版本要求)
ubuntu1604-py35-nvidia-tensorflow1.14-cuda9.0-cudnn7.05
nvcc
2 nvcc -V
3 wget -O /etc/yum.repos.d/CentOS-Base.repo http://mirrors.aliyun.com/repo/Centos-7.repo
4 yum install wget
5 wget -O /etc/yum.repos.d/CentOS-Base.repo http://mirrors.aliyun.com/repo/Centos-7.repo
6 wget -P /etc/yum.repos.d/ http://mirrors.aliyun.com/repo/epel-7.repo
7 yum clean all
8 yum makecache
9 yum install protobuf-devel leveldb-devel snappy-devel opencv-devel boost-devel hdf5-devel
10 yum install gflags-devel glog-devel lmdb-devel make
11 export LD_LIBRARY_PATH=/usr/local/cuda-9.0/lib64:/usr/local/cuda-9.0/extras/CUPTI/lib64:$LD_LIBRARY_PATH
12 export CUDA_HOME=/usr/local/cuda-9.0/
13 wget https://github.com/BVLC/caffe/archive/master.zip
14 unzip master.zip
15 yum install unzip
16 unzip master.zip
17 cd caffe-master/
18 ll
19 cd python/
20 ll
21 for req in $(cat requirements.txt); do pip install $req; done
22 yum install pip
23 yum install pip-devel
24 yum install python-pip
25 for req in $(cat requirements.txt); do pip install $req; done
26 c
27 for req in $(cat requirements.txt); do pip install -i https://mirrors.aliyun.com/pypi/simple/ $req; done
28 for req in $(cat requirements.txt); do pip install $req; done
29 wget https://www.python.org/ftp/python/3.6.4/Python-3.6.4.tar.xz
30 pwd
31 cd /usr/local/src/
32 ls
33 wget https://www.python.org/ftp/python/3.6.4/Python-3.6.4.tar.xz
34 xz -d Python-3.6.4.tar.xz
35 tar xvf Python-3.6.4.tar
36 cd Python-3.6.4
37 ./configure prefix=/usr/local/python3
38 make && make install
39 mv /usr/bin/python /usr/bin/python.bak
40 ln -s /usr/local/python3/bin/python3.6 /usr/bin/python
41 python -V
42 vi /usr/bin/yum
43 vi /usr/libexec/urlgrabber-ext-down
44 cd -
45 cd /caffe-master/python/
46 yum install python-pip3
47 yum install python-pip3-devel
48 yum install python3-pip
49 for req in $(cat requirements.txt); do pip install $req; done
50 python
51 cd /usr/local/src/
52 wget --no-check-certificate https://pypi.python.org/packages/source/s/setuptools/setuptools-19.6.tar.gz#md5=c607dd118eae682c44ed146367a17e26
53 tar -zxvf setuptools-19.6.tar.gz
54 cd setuptools-19.6
55 python3 setup.py build
56 python setup.py build
57 python setup.py install
58 ls /usr/local/python3/bin/pip3
59 ln -s /usr/local/python3/bin/pip3 /usr/bin/pip3
60 pip3 -V
61 cd /caffe-master/python/
62 ls
63 for req in $(cat requirements.txt); do pip3 install -i https://mirrors.aliyun.com/pypi/simple/ $req; done
64 for req in $(cat requirements.txt); do pip3 install $req; done
65 for req in $(cat requirements.txt); do pip3 install -i http://mirrors.aliyun.com/pypi/simple/ $req; done
66 vi ~/.pip/pip.conf
67 mkdir [global]
68 mkdir ~/.pip
69 vi ~/.pip/pip.conf
70 for req in $(cat requirements.txt); do pip3 install -i http://mirrors.aliyun.com/pypi/simple/ $req; done
71 for req in $(cat requirements.txt); do pip3 install -i https://pypi.tuna.tsinghua.edu.cn/simple $req; done
72 for req in $(cat requirements.txt); do pip install -i https://pypi.tuna.tsinghua.edu.cn/simple $req; done
73 python -m pip install --upgrade --force pip
74 easy_install -U setuptools
75 python -m pip install --upgrade --force pip
76 pip install --upgrade pip
77 for req in $(cat requirements.txt); do pip install -i https://pypi.tuna.tsinghua.edu.cn/simple $req; done
78 history
https://blog.csdn.net/kemgine/article/details/78781377
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
仔细查看了一下 Makefile.config 中 CUDA_ARCH 设置未按规定设置：
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
因为我装的是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 \
https://gitlab.com/nvidia/container-images/cuda/blob/master/dist/centos7/10.1/runtime/cudnn7/Dockerfile
Caffe安装错误及其解决方法
https://blog.csdn.net/jessir/article/details/71195115
caffe编译的问题解决：“cublas_v2.h: No such file or directory
具体来说：
CUDA7.5中的include、lib路径是安装目录下/usr/local/cuda-7.5/targets/x86_64-linux/下面的include和lib
将其分别添加到caffe根目录下Makefile.config中的"INCLUDE_DIRS"、“LIBRARY_DIRS”后面就可以了。
make all
make test
cudnn-8.0/9.0/10.0-linux-x64-v6.0/7.0/7.1/7.2/7.3/7.4.tgz下载
https://blog.csdn.net/xiangxianghehe/article/details/79177833
wget http://developer.download.nvidia.com/compute/redist/cudnn/v7.3.1/cudnn-9.2-linux-x64-v7.3.1.20.tgz #cuda9.2 cudnn7.3
wget http://developer.download.nvidia.com/compute/redist/cudnn/v7.2.1/cudnn-9.2-linux-x64-v7.2.1.38.tgz #cuda9.2 cudnn7.2
wget http://developer.download.nvidia.com/compute/redist/cudnn/v7.1.4/cudnn-9.2-linux-x64-v7.1.tgz #cuda9.2 cudnn 7.1
http://file.ppwwyyxx.com/nvidia/cudnn-9.2-linux-x64-v7.4.2.24.tgz
wget http://developer.download.nvidia.com/compute/redist/cudnn/v7.0.5/cudnn-9.1-linux-x64-v7.tgz # cuda9.1 cudnn7.0
wget http://developer.download.nvidia.com/compute/redist/cudnn/v7.1.4/cudnn-9.0-linux-x64-v7.1.tgz
wget http://developer.download.nvidia.com/compute/redist/cudnn/v7.3.0/cudnn-9.0-linux-x64-v7.3.0.29.tgz
make: /usr/local/cuda/bin/nvcc: Command not found
make: *** [.build_release/cuda/src/caffe/layers/absval_layer.o] Error 127
centos 7 安装caffe
https://blog.csdn.net/wqzghost/article/details/48264477
安装
https://juejin.im/post/5a0e819b6fb9a04524056583 在CentOS 7上安装Caffe
1.安装基础依赖库
sudo yum install protobuf-devel leveldb-devel snappy-devel opencv-devel boost-devel hdf5-devel sudo yum install gflags-devel glog-devel lmdb-devel
2.安装CUDA
sudo rpm -i cuda-repo-rhel7-8-0-local-ga2-8.0.61-1.x86_64.rpm sudo yum clean all sudo yum install cuda 环境变量 export LD_LIBRARY_PATH=/usr/local/cuda-8.0/lib64:/usr/local/cuda-8.0/extras/CUPTI/lib64:$LD_LIBRARY_PATH export CUDA_HOME=/usr/local/cuda-8.0/
3.安装cuDNN
cp include/* /usr/local/cuda/include cp lib64/* /usr/local/cuda/lib64
4.安装BLAS
sudo yum install atlas-devel cd /usr/lib64/atlas sudo ln -sv libsatlas.so.3.10 libcblas.so sudo ln -sv libsatlas.so.3.10 libatlas.so
5.下载Caffe源码
git clone https://github.com/BVLC/caffe.git
6.安装python 依赖
进入caffe/python目录，安装requirements中依赖库
for req in $(cat requirements.txt); do pip install $req; done
7.编译
编辑Caffe 目录Makefile.config 文件，根据依赖库情况修改配置： 主要修改如下：
USE_CUDNN := 1
BLAS := atlas
BLAS_INCLUDE := /usr/include/atlas
BLAS_LIB := /usr/lib64/atlas
PYTHON_INCLUDE := /usr/include/python2.7 \
/usr/lib64/python2.7/site-packages/numpy/core/include
PYTHON_LIB := /usr/lib64
编译和测试Caffe，-j选项为编译并行线程数，一般为CPU核数
make all -j8
make test -j8
make runtest -j8
Caffe 使用示例
1.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 ./build/tools/caffe caffe: command line brew usage: caffe <command> <args> commands: train train or finetune a model test score a model device_query show GPU diagnostic information time benchmark model execution time 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 训练输出示例如下：
安装caffe
yum install epel-release
yum install atlas-devel snappy-devel boost-devel leveldb leveldb-devel hdf5 hdf5-devel glog glog-devel gflags gflags-devel protobuf protobuf-devel opencv opencv-devel lmdb lmdb-devel
yum -y install gcc automake autoconf libtool make
安装参考，但是失败了
https://blog.csdn.net/qq_33144323/article/details/81261367
失败错误为
[root@0e04e413eadd caffe]# make all
CXX src/caffe/blob.cpp
In file included from ./include/caffe/common.hpp:19:0,
from ./include/caffe/blob.hpp:8,yum
from src/caffe/blob.cpp:4:
./include/caffe/util/device_alternate.hpp:34:23: fatal error: cublas_v2.h: No such file or directory
#include <cublas_v2.h>
^
compilation terminated.
make: *** [.build_release/src/caffe/blob.o] Error 1
yum install atlas-devel snappy-devel boost-devel leveldb leveldb-devel hdf5 hdf5-devel glog glog-devel gflags gflags-devel protobuf protobuf-devel opencv opencv-devel lmdb lmdb-devel
需求
jupyterlab 中使用caffe ,并且caffe能使用GPU, c++代码编写
centos7 下caffe GPU版的配置和TensorFlow gpu版本的安装 https://blog.csdn.net/qq_33144323/article/details/81261367
nvidia 官网
https://developer.nvidia.com/?destination=node/18866
centos 7 安装CUDA9.0 +CUDNN
https://www.jianshu.com/p/a201b91b3d96
````