用cuda编译dlib [英] compile dlib with cuda

问题描述

我正在尝试使用cuda编译dlib。我从这个GitHub链接

解决方案

创建一个用于托管源的文件夹

  mkdir -p / opt / SP / packages / 
 cd $ _ 
  

克隆存储库

  git克隆https://github.com/davisking/dlib.git 
 cd dlib 
 git子模块初始化
 git子模块更新
  

创建一个文件夹来构建软件（必须安装cmake）

  mkdir build 
 cd $ _ 
  

现在使用以下选项运行cmake：

  cmake -D DLIB_USE_CUDA = 1 -D USE_AVX_INSTRUCTIONS = 1 ../ 
  

如果一切都很好，您会看到类似的内容输出

注意：安装 cuDNN ，openblas和 Intel MKL / BLAS / LAPACK

链接到英特尔性能库： https://software.seek.intel.com/performance-libraries

与cuDNN的链接： https://developer.nvidia.com/cudnn

现在您可以使用

  cmake --build编译源代码。 --config释放
  

在这些步骤之后，将编译源。

现在您可以安装python API。

  cd ../ 
 python设置。 py install 
  

注意：这次编译将使用所有可用的CPU，请确保您有足够的CPU

完成后，您可以查询python软件包以确保已安装dlib：

点冻结| grep dlib

检查安装是否成功：

打开终端并运行以下命令

 >>>将dlib.cuda导入为cuda; 
>>打印（cuda.get_num_devices（））; 
 1 
>> import dlib 
>> dlib.DLIB_USE_BLAS 
真
>>> dlib.DLIB_USE_CUDA 
真
>>> dlib.DLIB_USE_LAPACK 
真
  

I am trying to compile dlib with cuda. I clone the repository from this GitHub link https://github.com/davisking/dlib and then tried to run

python setup.py install --yes USE_AVX_INSTRUCTIONS

But I receive an error. Can anyone help me to solve it?

解决方案

Create a folder for host the source

mkdir -p /opt/SP/packages/
cd $_

Clone the repository

git clone https://github.com/davisking/dlib.git
cd dlib
git submodule init
git submodule update

Create a folder for build the software (cmake have to be installed)

mkdir build
cd $_

Now run cmake with the following options:

cmake  -D DLIB_USE_CUDA=1 -D USE_AVX_INSTRUCTIONS=1 ../

If everything is fine, you can see a similar output

NOTE: Install cuDNN, openblas and Intel MKL/BLAS/LAPACK if your system is compliant with them.

Link to Intel Performance Library: https://software.seek.intel.com/performance-libraries

Link to cuDNN: https://developer.nvidia.com/cudnn

Now you can compile the source with

cmake --build . --config Release

After these step, the source is compiled.

Now you can install the python API.

cd ../
python setup.py install

NOTE: The compilation this time will use all the available CPU, be sure that you have enough memory for compile.

Once completed, you can query your python packages for be sure that dlib is now installed:

pip freeze | grep dlib

For check if the installation was succesfully:

Open a terminal and run the following

>>> import dlib.cuda as cuda;
>>> print(cuda.get_num_devices());
1
>>> import dlib
>>> dlib.DLIB_USE_BLAS
True
>>> dlib.DLIB_USE_CUDA
True
>>> dlib.DLIB_USE_LAPACK
True

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