标签:cap sam absl 设置 gen echo and not found abs
TensorFlow 的 Python 接口由于其方便性和实用性而大受欢迎,但实际应用中我们可能还需要其它编程语言的接口,本文将介绍如何编译 TensorFlow 的 C/C++ 接口。
安装环境:
Ubuntu 16.04
Python 3.5
CUDA 9.0
cuDNN 7
Bazel 0.17.2
TensorFlow 1.11.0
安装 JDK sudo apt-get install openjdk-8-jdk
echo "deb [arch=amd64] http://storage.googleapis.com/bazel-apt stable jdk1.8" | sudo tee /etc/apt/sources.list.d/bazel.list
curl https://bazel.build/bazel-release.pub.gpg | sudo apt-key add -
安装并更新 Bazel sudo apt-get update && sudo apt-get install bazel
./configure
进行配置。可参考 官网 -> Build from source -> View sample configuration session 设置,主要是 Python 的路径、CUDA 和 CUDNN 的版本和路径以及显卡的计算能力 可点此查看 。以下是我的配置过程,仅供参考。You have bazel 0.17.2 installed.
Please specify the location of python. [Default is /usr/bin/python]: /usr/bin/python3.5
Found possible Python library paths:
/usr/local/lib/python3.5/dist-packages
/usr/lib/python3/dist-packages
Please input the desired Python library path to use. Default is [/usr/local/lib/python3.5/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]:
Please specify the location where cuDNN 7 library is installed. Refer to README.md for more details. [Default is /usr/local/cuda]:
Do you wish to build TensorFlow with TensorRT support? [y/N]: n
No TensorRT support will be enabled for TensorFlow.
Please specify the locally installed NCCL version you want to use. [Default is to use https://github.com/nvidia/nccl]:
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: 6.1]:
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 .bazelrc 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
C版本: bazel build :libtensorflow.so
C++版本: bazel build :libtensorflow_cc.so
进入 tensorflow/contrib/makefile 目录下,运行./build_all_linux.sh
,成功后会出现一个gen文件夹
若出现如下错误 /autogen.sh: 4: autoreconf: not found ,安装相应依赖即可 sudo apt-get install autoconf automake libtool
cmake_minimum_required(VERSION 3.8)
project(Tensorflow_test)
set(CMAKE_CXX_STANDARD 11)
set(SOURCE_FILES main.cpp)
include_directories(
/media/lab/data/yongsen/tensorflow-master
/media/lab/data/yongsen/tensorflow-master/tensorflow/bazel-genfiles
/media/lab/data/yongsen/tensorflow-master/tensorflow/contrib/makefile/gen/protobuf/include
/media/lab/data/yongsen/tensorflow-master/tensorflow/contrib/makefile/gen/host_obj
/media/lab/data/yongsen/tensorflow-master/tensorflow/contrib/makefile/gen/proto
/media/lab/data/yongsen/tensorflow-master/tensorflow/contrib/makefile/downloads/nsync/public
/media/lab/data/yongsen/tensorflow-master/tensorflow/contrib/makefile/downloads/eigen
/media/lab/data/yongsen/tensorflow-master/bazel-out/local_linux-py3-opt/genfiles
/media/lab/data/yongsen/tensorflow-master/tensorflow/contrib/makefile/downloads/absl
)
add_executable(Tensorflow_test ${SOURCE_FILES})
target_link_libraries(Tensorflow_test
/media/lab/data/yongsen/tensorflow-master/bazel-bin/tensorflow/libtensorflow_cc.so
/media/lab/data/yongsen/tensorflow-master/bazel-bin/tensorflow/libtensorflow_framework.so
)
#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;
}
#include <iostream>
#include <tensorflow/c/c_api.h>
int main() {
std:: cout << "Hello from TensorFlow C library version" << TF_Version();
return 0;
}
// Hello from TensorFlow C library version1.11.0-rc1
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标签:cap sam absl 设置 gen echo and not found abs
原文地址:https://www.cnblogs.com/seniusen/p/9756302.html