下载TF代码，配置tf
git clone -b v1.14.0 https://github.com/tensorflow/tensorflow.git
cd tensorflow
./configure # 配置tf编译选项编译tf so，ABI根据实际需要配置
bazel build --cxxopt="-D_GLIBCXX_USE_CXX11_ABI=0" --config=opt //tensorflow:libtensorflow_cc.so
bazel build --cxxopt="-D_GLIBCXX_USE_CXX11_ABI=0" --config=opt //tensorflow:libtensorflow_framework.so
编译遇到SSL错误时
# apt-get install -y default-jre
# apt-get install -y default-jdk
# 导入证书
# keytool -import -noprompt -keystore "/etc/ssl/certs/java/cacerts" -storepass changeit -keypass changeit -alias twca -file xxx.cer
bazel --host_jvm_args=-Djavax.net.ssl.trustStore="/etc/ssl/certs/java/cacerts" \
--host_jvm_args=-Djavax.net.ssl.trustStorePassword=changeit \
build --cxxopt="-D_GLIBCXX_USE_CXX11_ABI=0" --config=opt //tensorflow:libtensorflow_cc.so
bazel --host_jvm_args=-Djavax.net.ssl.trustStore="/etc/ssl/certs/java/cacerts" \
--host_jvm_args=-Djavax.net.ssl.trustStorePassword=changeit \
build --cxxopt="-D_GLIBCXX_USE_CXX11_ABI=0" --config=opt //tensorflow:libtensorflow_framework.so
可能遇到其他错误，可以网络寻找解决方案。
编译完成后在bazel-bin/tensorflow/会生成相应的so文件。
开发cpp调用tf api，使用cmake配置工程
cmake_minimum_required(VERSION 2.8.2)
project(tf_test LANGUAGES CXX)
add_compile_options(-std=c++11)
add_compile_options(-fPIC)
add_definitions(-D_GLIBCXX_USE_CXX11_ABI=0)
add_executable(
main
main.cpp
)
include_directories(
$ENV{TF_INCLUDE_PATH} # you can use include path of tf installed by pip
)
target_link_libraries(
main
/xx_path/libtensorflow_cc.so
/xx_path/libtensorflow_framework.so
)
# "-Wl,--allow-multiple-definition -Wl,--whole-archive" #之后的库使用--whole-archive选项
# "-Wl,--no-whole-archive" #之后的库不使用--whole-archive选项
include path可以使用pip安装的同版本tf的include path:
export TF_INCLUDE_PATH=$(python3 -c 'import tensorflow as tf; print(tf.sysconfig.get_compile_flags()[0].strip("-I"))')
参考模型调用
#include "google/protobuf/io/zero_copy_stream_impl.h"
#include "tensorflow/core/protobuf/meta_graph.pb.h"
#include "tensorflow/core/public/session.h"
#include "tensorflow/core/framework/tensor.h"
#include "tensorflow/core/platform/env.h"
#include <iostream>
#include <string>
int main() {
std::string model_path = "resnet50.pb";
tensorflow::GraphDef graphdef;
tensorflow::Status status_load = ReadBinaryProto(tensorflow::Env::Default(), model_path, &graphdef);
tensorflow::SessionOptions options;
tensorflow::Session* _session;
_session = tensorflow::NewSession(options);
if (_session == nullptr) {
std::cout << "create new session failed" << std::endl;
return -1;
}
tensorflow::Status status;
status = _session->Extend(graphdef);
if (!status.ok()) {
std::cout << "session extend graph failed" << std::endl;
return -1;
}
return 0;
}
参考
从0开始使用tensorflow的c++库进行模型推断_gaussrieman123的博客-CSDN博客
TensorFlow c++ SessionFactory注册与No session factory registered错误_gaussrieman123的博客-CSDN博客
使用C++调用TensorFlow模型简单说明 | Dannyw's Blog