编译tensorflow

2021-04-12

字数：959字 | 预计阅读时长：5分钟

记录编译过程

前序安装

1、bazel 2.0.0 通过sh安装，需要chmod，然后export环境变量。我的路径在/var/root/bin，添加到source ~/.bash_profile。把这句source添加到 vi .zshrc ，然后source ~/.zshrc ，重启也有bazel了。

2、tensorflow v2.2.0

3、conda环境，选择了python2.7，然后安装requirements (tensorflow-2.2.0/tensorflow/tools/pip_package/setup.py )如下

future
absl-py >= 0.7.0
astunparse == 1.6.3
backports.weakref >= 1.0rc1
enum34 >= 1.1.6
gast == 0.3.3
google_pasta >= 0.1.8
h5py == 2.10.0
keras_preprocessing >= 1.1.0
numpy == 1.16.0
opt_einsum >= 2.3.2
protobuf >= 3.8.0
tensorboard == 2.1.0
tensorflow_estimator == 2.2.0
termcolor >= 1.1.0
wrapt >= 1.11.1

# python3 requires wheel 0.26
wheel >= 0.26

# mock comes with unittest.mock for python3 need to install for python2
mock >= 2.0.0

# functools comes with python3 need to install the backport for python2
functools32 >= 3.2.3
six >= 1.12.0

# scipy < 1.4.1 causes segfaults due to pybind11
# Latest scipy pip for py2 is scipy==1.2.2
scipy == 1.2.2

4、如果需要gpu，则还要安装cuda 10.1 和 cudnn 7.6.5

编译

1、配置基本选择N，需要gpu则在CUDAsupport选择y

1 2	cd tensorflow-2.2.0 ./configure

2、bazel

1
2
3

bazel build --noincompatible_do_not_split_linking_cmdline --local_ram_resources=2048  //tensorflow/tools/pip_package:build_pip_package

bazel build --noincompatible_do_not_split_linking_cmdline --local_ram_resources=2048 //tensorflow:libtensorflow_cc.so

编译成功，花了12个小时多。

success

生成whl

sudo ./tensorflow/tools/pip_package/build_pip_package.sh /tmp/tensorflow_pkg
#接着我切了conda环境
pip install --upgrade pip
pip uninstall tensorflow
pip uninstall tensorboard
pip uninstall tensorflow-tensorboard
#pip3 install tensorboard==2.2.1  #有个巨坑。pip3才能安装2.2.1，但是我们环境用的都是python2.7
#要么把之前的切到3，要么下载下来site-package 装到目录里。我是选择粘贴到目录 #/Users/wyq/anaconda2/lib/python2.7/site-packages/tensorboard
pip install -U --ignore-installed wrapt  
#又是坑。wrapt：ERROR: Cannot uninstall 'wrapt'. It is a distutils installed project and thus #we cannot accurately determine which files belong to it which would lead to only a partial #uninstall.
pip3 install /tmp/tensorflow_pkg/tensorflow-2.2.0-cp27-cp27m-macosx_10_14_x86_64.whl

whl0

whl

python验证

#打开ipython 
#如果遇到这个问题 ImportError: cannot import name pywrap_tensorflow
#看这个issue 
# https://stackoverflow.com/questions/35953210/error-running-basic-tensorflow-example
import tensorflow as tf
tf.__version__
tf.test.is_gpu_available()

终于成功了

whlsuccess

c++验证

选择了vscode，下次clion可以也试试

#在tf根目录下运行
bazel build //tensorflow/cc:tutorials_example_trainer
bazel build //tensorflow/cc:client_client_session_test

#然后运行程序
./bazel-bin/tensorflow/cc/client_client_session_test

csuccess

demo

c++demo

//main.cpp
#include <iostream>
#include "tensorflow/cc/client/client_session.h"
#include "tensorflow/cc/ops/standard_ops.h"
#include "tensorflow/core/framework/tensor.h"

using namespace tensorflow;
using namespace tensorflow::ops;

int main()
{
    Scope root = Scope::NewRootScope();

    // Matrix A = [3 2; -1 0]
    auto A = Const(root, { {3.f, 2.f}, {-1.f, 0.f} });
    // Vector b = [3 5]
    auto b = Const(root, { {3.f, 5.f} });
    // v = Ab^T
    auto v = MatMul(root.WithOpName("v"), A, b, MatMul::TransposeB(true));

    std::vector<Tensor> outputs;
    ClientSession session(root);

    // Run and fetch v
    TF_CHECK_OK(session.Run({v}, &outputs));
    std::cout << "tensorflow session run ok" << std::endl;
    // Expect outputs[0] == [19; -3]
    std::cout << outputs[0].matrix<float>();

    return 0;
}



//BUILD file

load("//tensorflow:tensorflow.bzl", "tf_cc_binary")
tf_cc_binary(
     name = "main", #目标文件名
     srcs = ["main.cpp"], #源代码文件名
     deps = [
        "//tensorflow/cc:cc_ops",
         "//tensorflow/cc:client_session",
         "//tensorflow/core:tensorflow"
         ],
 )
 
 //执行
 bazel build //tensorflow/demo:main