SSH(Single Stage Headless)实现

服务器上ssh实现

写在前面：这只是我在服务器上的环境实现的，仅供参考。要根据自己系统的环境做出修改。

==github源码（https://github.com/mahyarnajibi/SSH）==

**实现参考（https://blog.csdn.net/qq_14845119/article/details/79105360）**

（https://blog.csdn.net/zziahgf/article/details/72900948）

**初始工作：**安装cuda和cudnn还有nccl

因为服务器上装好了cuda和cudnn，我选择了cuda9.0和cudnn7.0。所以直接安装nccl

从github获取并安装

git clone https://github.com/NVIDIA/nccl.git
cd nccl 
make clean && make PREFIX=$NCCL_ROOT_DIR install

$NCCL_ROOT_DIR是自己安装的路径：比如我的路径是 /home/lzm/data/nccl/install则为：

make clean && make PREFIX=/home/lzm/data/nccl/install install

等nccl安装完成

安装caffe-ssh

1、所有都在conda建立的python虚拟环境下进行如：

conda create -n caffetest（虚拟）  python=2.7（不是2.7貌似会报错） anaconda 
conda activate caffetest

2、从github获取源码：

git clone --recursive https://github.com/mahyarnajibi/SSH.git

3、进入目录SSH安装需要的python模块：

cd SSH 
pip install -r requirements.txt

4、建立临时环境变量env

（1）把nccl和conda环境写入env文件：

dlm-conda activate caffetest
export CPLUS_INCLUDE_PATH=$CPLUS_INCLUDE_PATH:/home/lzm/data/caffe/caffe1.0_nccl/nccl/install/include
export C_INCLUDE_PATH=$C_INCLUDE_PATH:/home/lzm/data/caffe/caffe1.0_nccl/nccl/install/include
export LIBRARY_PATH=$LIBRARY_PATH:/home/lzm/data/caffe/caffe1.0_nccl/nccl/install/lib
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/home/lzm/data/caffe/caffe1.0_nccl/nccl/install/lib

（2）激活环境变量：

source ./env

5、配置文件将Makefile.config.example拷贝一份成配置文件：

cd caffe-ssh
cp Makefile.config.example Makefile.config

修改Makefile.config

（1）改成自己cuda的目录：

CUDA_DIR := /usr/local/cuda
改成
CUDA_DIR := /usr/local/nvidia/cuda/9.0

（2）去掉的注释：

#OPENCV_VERSION := 3
改成
OPENCV_VERSION := 3

（3）修改环境路径

INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include
LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib
改为
INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include /usr/include/hdf5/serial/
LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib /usr/lib/x86_64-linux-gnu/hdf5/serial/

6、安装缺少模块

conda install -c conda-forge readline=6.2
conda install libgcc

7、编译

make all -j32

8、编译pycaffe生成接口

make pycaffe

9、在lib中编译运行setup.py

cd ../lib/
make

10、用scripts中的脚本下载模型

cd ..
bash scripts/download_ssh_model.sh
bash scripts/ download_imgnet_model.sh

11、运行模型演示

python demo.py

结果如下：

可能出现的问题

（1）

问题：

Unsupported gpu architecture ‘compute_20’

解决方案：

https://askubuntu.com/questions/960238/nvcc-fatal-unsupported-gpu-architecture-compute-20

即去掉Makefile.config 中两行：

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_50,code=compute_50
 改为：
 CUDA_ARCH := -gencode arch=compute_50,code=sm_50 \
        -gencode arch=compute_52,code=sm_52 \
        -gencode arch=compute_60,code=sm_60 \
        -gencode arch=compute_62,code=sm_62 \
        -gencode arch=compute_61,code=compute_61

（2）

问题：

awk: symbol lookup error: /home/lzm/.conda/envs/lzm2/lib/libreadline.so.6: undefined symbol: PC

解决方案：

https://github.com/conda-forge/rpy2-feedstock/issues/1

https://github.com/bioconda/bioconda-recipes/issues/5350

即 run

conda install -c conda-forge readline = 6.2

（3）

问题：

./include/caffe/util/hdf5.hpp:6:18: fatal error: hdf5.h: no such file or directory

解决方案：

https://github.com/BVLC/caffe/issues/2690

https://github.com/NVIDIA/DIGITS/issues/156

即Makefile.config 拿两行改掉：

INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include
LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib
改为
INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include /usr/include/hdf5/serial/
LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib /usr/lib/x86_64-linux-gnu/hdf5/serial/

（4）

问题：

./include/caffe/util/nccl.hpp:5:18: fatal error: nccl.h: No such file or directory

解决方案：

新建文件为env

将服务器已经安装的nccl路径配置到env：

export CPLUS_INCLUDE_PATH=$CPLUS_INCLUDE_PATH:/home/lzm/data/caffe/caffe1.0_nccl/nccl/install/include
export C_INCLUDE_PATH=$C_INCLUDE_PATH:/home/lzm/data/caffe/caffe1.0_nccl/nccl/install/include
export LIBRARY_PATH=$LIBRARY_PATH:/home/lzm/data/caffe/caffe1.0_nccl/nccl/install/lib
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/home/lzm/data/caffe/caffe1.0_nccl/nccl/install/lib

每次要用的时候都激活环境：