TensorFlow C++

环境

  • 系统: Ubuntu 16.04.4 LTS
  • 内核: 4.15.0-50-generic
  • CUDA: 9.0.176
  • 显卡: 940mx
  • 显卡驱动: 384.13
  • GCC: 5.4.0
  • python: 3.5.2

protobuf

sudo apt-get install autoconf automake libtool curl make g++ unzip

git clone https://github.com/protocolbuffers/protobuf.git
cd protobuf
git checkout v3.6.0
git submodule update --init --recursive
./autogen.sh

./configure
make -j4
make check -j4
sudo make install -j4
sudo ldconfig # refresh shared library cache.
protoc --version
libprotoc 3.6.0
sudo pip3 uninstall protobuf
cd protobuf/python
python3 setup.py build
python3 setup.py test
sudo python3 setup.py install

Bazel

下载bazel-0.18.1-installer-linux-x86_64.sh

chmod +x bazel-0.18.1-installer-linux-x86_64.sh
sudo ./bazel-0.18.1-installer-linux-x86_64.sh --user

The --user flag installs Bazel to the $HOME/bin directory on your system and sets the .bazelrc path to $HOME/.bazelrc. Use the --help command to see additional installation options.

Check CuDNN Version

cat /usr/local/cuda/include/cudnn.h | grep CUDNN_MAJOR -A 2

or

cat /usr/include/x86_64-linux-gnu/cudnn.h | grep CUDNN_MAJOR -A 2

TensorFlow

git clone https://github.com/tensorflow/tensorflow.git
git checkout v1.12.2
./configure


WARNING: An illegal reflective access operation has occurred
WARNING: Illegal reflective access by com.google.protobuf.UnsafeUtil (file:/home/luohanjie/.cache/bazel/_bazel_luohanjie/install/cdf71f2489ca9ccb60f7831c47fd37f1/_embedded_binaries/A-server.jar) to field java.lang.String.value
WARNING: Please consider reporting this to the maintainers of com.google.protobuf.UnsafeUtil
WARNING: Use --illegal-access=warn to enable warnings of further illegal reflective access operations
WARNING: All illegal access operations will be denied in a future release
WARNING: --batch mode is deprecated. Please instead explicitly shut down your Bazel server using the command "bazel shutdown".
You have bazel 0.18.1 installed.
Please specify the location of python. [Default is /usr/bin/python]: /usr/bin/python3


Found possible Python library paths:
/home/luohanjie/Documents/software/caffe/python
/usr/lib/python3.5/dist-packages
/usr/local/lib/python3.5/dist-packages
/usr/lib/python3/dist-packages
Please input the desired Python library path to use. Default is [/home/luohanjie/Documents/software/caffe/python]
/usr/lib/python3/dist-packages
Do you wish to build TensorFlow with Apache Ignite support? [Y/n]: n
No Apache Ignite support will be enabled for TensorFlow.

Do you wish to build TensorFlow with XLA JIT support? [Y/n]: n
No XLA JIT support will be enabled for TensorFlow.

Do you wish to build TensorFlow with OpenCL SYCL support? [y/N]: n
No OpenCL SYCL support will be enabled for TensorFlow.

Do you wish to build TensorFlow with ROCm support? [y/N]: n
No ROCm support will be enabled for TensorFlow.

Do you wish to build TensorFlow with CUDA support? [y/N]: y
CUDA support will be enabled for TensorFlow.

Please specify the CUDA SDK version you want to use. [Leave empty to default to CUDA 9.0]:


Please specify the location where CUDA 9.0 toolkit is installed. Refer to README.md for more details. [Default is /usr/local/cuda]:


Please specify the cuDNN version you want to use. [Leave empty to default to cuDNN 7]: 7.4.2


Please specify the location where cuDNN 7 library is installed. Refer to README.md for more details. [Default is /usr/local/cuda]: /usr/include/x86_64-linux-gnu


Do you wish to build TensorFlow with TensorRT support? [y/N]: y
TensorRT support will be enabled for TensorFlow.

Please specify the location where TensorRT is installed. [Default is /usr/lib/x86_64-linux-gnu]:/usr/src/tensorrt


Please specify the NCCL version you want to use. If NCCL 2.2 is not installed, then you can use version 1.3 that can be fetched automatically but it may have worse performance with multiple GPUs. [Default is 2.2]: 1.3


Please specify a list of comma-separated Cuda compute capabilities you want to build with.
You can find the compute capability of your device at: https://developer.nvidia.com/cuda-gpus.
Please note that each additional compute capability significantly increases your build time and binary size. [Default is: 3.5,7.0]: 5.0


Do you want to use clang as CUDA compiler? [y/N]: n
nvcc will be used as CUDA compiler.

Please specify which gcc should be used by nvcc as the host compiler. [Default is /usr/bin/gcc]:


Do you wish to build TensorFlow with MPI support? [y/N]: n
No MPI support will be enabled for TensorFlow.

Please specify optimization flags to use during compilation when bazel option "--config=opt" is specified [Default is -march=native]:


Would you like to interactively configure ./WORKSPACE for Android builds? [y/N]: n
Not configuring the WORKSPACE for Android builds.

Preconfigured Bazel build configs. You can use any of the below by adding "--config=<>" to your build command. See tools/bazel.rc for more details.
--config=mkl # Build with MKL support.
--config=monolithic # Config for mostly static monolithic build.
--config=gdr # Build with GDR support.
--config=verbs # Build with libverbs support.
--config=ngraph # Build with Intel nGraph support.
Configuration finished
bazel build -c opt --copt=-mavx --copt=-mavx2 --copt=-mfma --copt=-mfpmath=both --copt=-msse4.2 --config=nonccl //tensorflow:libtensorflow_cc.so

bazel build -c opt --copt=-mavx --copt=-mavx2 --copt=-mfma --copt=-mfpmath=both --copt=-msse4.2 --config=nonccl //tensorflow:libtensorflow_framework.so

sudo mkdir -p /usr/local/include/tf/tensorflow

sudo ln -s abs_path_to_tensorflow/bazel-genfiles/ /usr/local/include/tf
sudo ln -s abs_path_to_tensorflow/tensorflow/cc /usr/local/include/tf/tensorflow
sudo ln -s abs_path_to_tensorflow/tensorflow/core /usr/local/include/tf/tensorflow
sudo ln -s abs_path_to_tensorflow/third_party /usr/local/include/tf
sudo ln -s abs_path_to_tensorflow/bazel-bin/tensorflow/libtensorflow_cc.so /usr/local/lib
sudo ln -s abs_path_to_tensorflow/bazel-bin/tensorflow/libtensorflow_framework.so /usr/local/lib
sudo ln -s tensorflow/contrib/makefile/downloads/absl/absl /usr/local/include/tf/third_party

如果想要卸载请运行如下命令[1]

sudo rm -r /usr/local/include/tf
sudo rm /usr/local/lib/libtensorflow_*.so

TensorFlow C++ Demo

Demo.cpp

#include <tensorflow/core/platform/env.h>
#include <tensorflow/core/public/session.h>
#include <iostream>

using namespace std;
using namespace tensorflow;

int main()
{

Session* session;
Status status = NewSession(SessionOptions(), &session);
if (!status.ok()) {
cout << status.ToString() << "\n";
return 1;
}
cout << "Session successfully created.\n";
return 0;
}

CMakeLists.txt

cmake_minimum_required(VERSION 3.5)

set(CMAKE_CXX_STANDARD 11)

find_package(OpenCV REQUIRED)
find_package(Eigen REQUIRED )

add_definitions(${EIGEN_DEFINITIONS})

set(TENSORFLOW_INCLUDES
/usr/local/include/tf/
/usr/local/include/tf/bazel-genfiles
/usr/local/include/tf/tensorflow/
/usr/local/include/tf/third-party

)

set(TENSORFLOW_LIBS
/usr/local/lib/libtensorflow_cc.so
/usr/local/lib//libtensorflow_framework.so)


include_directories(
${TENSORFLOW_INCLUDES}
${OpenCV_INCLUDE_DIRS}
${EIGEN_INCLUDE_DIR}
)

add_executable(demo demo.cpp)
target_link_libraries(demo ${TENSORFLOW_LIBS} ${OpenCV_LIBS})

  1. http://www.liuxiao.org/2018/08/ubuntu-tensorflow-c-%E4%BB%8E%E8%AE%AD%E7%BB%83%E5%88%B0%E9%A2%84%E6%B5%8B1%EF%BC%9A%E7%8E%AF%E5%A2%83%E6%90%AD%E5%BB%BA/