Build tensorflow_C v2.0

概览：

• Install bazel
• Get source & Build
• Check

下载官网最新源码:

https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-cpu-linux-x86_64-1.15.0.tar.gz

由于官网没有最新版TensorFlow for C v2.0 二进制包

所以:::::->

Install bazel

bazel 官网

以ubuntu为例：https://docs.bazel.build/versions/master/install-ubuntu.html

Get source & Build

bazel test是下载依赖并编译，并且最好带上-j 5参数，5为CPU核心数的一半，否则可能会卡死。build对应打压缩包。

git clone --depth=1 -b r2.0 https://github.com/tensorflow/tensorflow.git
cd tensorflow
bazel test -j 5 --config opt //tensorflow/tools/lib_package:libtensorflow_test
bazel build --config opt //tensorflow/tools/lib_package:libtensorflow

压缩包位置：bazel-bin/tensorflow/tools/lib_package/libtensorflow.tar.gz。

Check

sudo mkdir /opt/tensorflow
sudo tar -zxvf bazel-bin/tensorflow/tools/lib_package/libtensorflow.tar.gz -C /opt/tensorflow

刷新ld

新建文件sudo subl /etc/ld.so.conf.d/tensorflow.conf

加入以下内容：/opt/tensorflow/lib ,保存退出。

更新动态链接库缓存.sudo ldconfig

main.c

#include <stdio.h>
#include <tensorflow/c/c_api.h>

int main() {
  printf("Hello from TensorFlow C library version %s\n", TF_Version());
  return 0;
}

CMakeLists.txt

cmake_minimum_required(VERSION 3.2)
project(hello4tensorflow-c)


set(CMAKE_INCLUDE_CURRENT_DIR ON)
set(EXECUTABLE_OUTPUT_PATH ${CMAKE_SOURCE_DIR}/bin)

add_definitions("-Wl,-rpath,/opt/tensorflow/lib")
link_directories("/opt/tensorflow/lib")

include_directories("./" "/opt/tensorflow//include/")

add_executable(${PROJECT_NAME} "main.c")
target_link_libraries(${PROJECT_NAME} PRIVATE tensorflow)

golang示例,但不能用与tensorflow2,因为它依赖libtensorflow.so.1,而不是libtensorflow.so.2

main.go

package main

import (
    "fmt"

    tf "github.com/tensorflow/tensorflow/tensorflow/go"
    "github.com/tensorflow/tensorflow/tensorflow/go/op"
)

func main() {
    // Construct a graph with an operation that produces a string constant.
    s := op.NewScope()
    c := op.Const(s, "Hello from TensorFlow version "+tf.Version())
    graph, err := s.Finalize()
    if err != nil {
        panic(err)
    }

    // Execute the graph in a session.
    sess, err := tf.NewSession(graph, nil)
    if err != nil {
        panic(err)
    }
    output, err := sess.Run(nil, []tf.Output{c}, nil)
    if err != nil {
        panic(err)
    }
    fmt.Println(output[0].Value())
}