编译TensorFlow源码

时间：2023-03-08 20:56:44

  编译TensorFlow源码

参考：

https://www.tensorflow.org/install/install_sources

https://github.com/tensorflow/tensorflow/blob/master/tensorflow/go/README.md

一 环境

ubuntu 16.04.2   （virtualbox 虚拟机）

二  安装 bazel

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

Using Bazel custom APT repository (recommended)

1. Install JDK 8

Install JDK 8 by using:

sudo apt-get install openjdk--jdk

On Ubuntu 14.04 LTS you'll have to use a PPA:

sudo add-apt-repository ppa:webupd8team/java

sudo apt-get update && sudo apt-get install oracle-java8-installer

　　

2. Add Bazel distribution URI as a package source (one time setup)

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 -

If you want to install the testing version of Bazel, replace stable with testing.

3. Install and update Bazel

sudo apt-get update && sudo apt-get install bazel

Once installed, you can upgrade to a newer version of Bazel with:

sudo apt-get upgrade bazel

三 Python和Swig

sudo apt-get install python3-numpy python3-dev python3-pip python3-wheel  swig

四 下载源码及编译TensorFlow

github直接下载最新代码  https://github.com/tensorflow/tensorflow

终端切换到源码主目录，

./configure

涉及一些交互项

dell@dell-VirtualBox:~/tensorflow-master$ ./configure

WARNING: ignoring http_proxy in environment.

You have bazel 0.5. installed.

Please specify the location of python. [Default is /usr/bin/python]: /usr/bin/python3.

Found possible Python library paths:

  /usr/local/lib/python3./dist-packages

  /usr/lib/python3/dist-packages

Please input the desired Python library path to use.  Default is [/usr/local/lib/python3./dist-packages]

Do you wish to build TensorFlow with jemalloc as malloc support? [Y/n]: y

jemalloc as malloc support will be enabled for TensorFlow.

Do you wish to build TensorFlow with Google Cloud Platform support? [y/N]: n

No Google Cloud Platform support will be enabled for TensorFlow.

Do you wish to build TensorFlow with Hadoop File System support? [y/N]: n

No Hadoop File System 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 GDR support? [y/N]: n

No GDR support will be enabled for TensorFlow.

Do you wish to build TensorFlow with VERBS support? [y/N]: n

No VERBS support will be enabled for TensorFlow.

Do you wish to build TensorFlow with OpenCL support? [y/N]: n

No OpenCL support will be enabled for TensorFlow.

Do you wish to build TensorFlow with CUDA support? [y/N]: n

No CUDA support will be enabled for TensorFlow.

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]: 

Add "--config=mkl" to your bazel command to build with MKL support.

Please note that MKL on MacOS or windows is still not supported.

If you would like to use a local MKL instead of downloading, please set the environment variable "TF_MKL_ROOT" every time before build.

Configuration finished

开始编译

bazel build --config opt //tensorflow:libtensorflow.so

耗时比较长，用了90多分钟。

./tensorflow/core/framework/function.h::: note: in expansion of macro 'REGISTER_OP_GRADIENT_UNIQ'

   REGISTER_OP_GRADIENT_UNIQ(ctr, name, fn)

   ^

./tensorflow/core/framework/function.h::: note: in expansion of macro 'REGISTER_OP_GRADIENT_UNIQ_HELPER'

   REGISTER_OP_GRADIENT_UNIQ_HELPER(__COUNTER__, name, fn)

   ^

tensorflow/core/ops/nn_grad.cc::: note: in expansion of macro 'REGISTER_OP_GRADIENT'

 REGISTER_OP_GRADIENT("MaxPool", MaxPoolGrad);

 ^

./tensorflow/core/framework/function.h::: warning: 'tensorflow::unused_grad_6' defined but not used [-Wunused-variable]

   static bool unused_grad_##ctr = SHOULD_REGISTER_OP_GRADIENT && \

               ^

./tensorflow/core/framework/function.h::: note: in expansion of macro 'REGISTER_OP_GRADIENT_UNIQ'

   REGISTER_OP_GRADIENT_UNIQ(ctr, name, fn)

   ^

./tensorflow/core/framework/function.h::: note: in expansion of macro 'REGISTER_OP_GRADIENT_UNIQ_HELPER'

   REGISTER_OP_GRADIENT_UNIQ_HELPER(__COUNTER__, name, fn)

   ^

tensorflow/core/ops/nn_grad.cc::: note: in expansion of macro 'REGISTER_OP_GRADIENT'

 REGISTER_OP_GRADIENT("AvgPool", AvgPoolGrad);

 ^

./tensorflow/core/framework/function.h::: warning: 'tensorflow::unused_grad_7' defined but not used [-Wunused-variable]

   static bool unused_grad_##ctr = SHOULD_REGISTER_OP_GRADIENT && \

               ^

./tensorflow/core/framework/function.h::: note: in expansion of macro 'REGISTER_OP_GRADIENT_UNIQ'

   REGISTER_OP_GRADIENT_UNIQ(ctr, name, fn)

   ^

./tensorflow/core/framework/function.h::: note: in expansion of macro 'REGISTER_OP_GRADIENT_UNIQ_HELPER'

   REGISTER_OP_GRADIENT_UNIQ_HELPER(__COUNTER__, name, fn)

   ^

tensorflow/core/ops/nn_grad.cc::: note: in expansion of macro 'REGISTER_OP_GRADIENT'

 REGISTER_OP_GRADIENT("MaxPoolGrad", MaxPoolGradGrad);

 ^

./tensorflow/core/framework/function.h::: warning: 'tensorflow::unused_grad_8' defined but not used [-Wunused-variable]

   static bool unused_grad_##ctr = SHOULD_REGISTER_OP_GRADIENT && \

               ^

./tensorflow/core/framework/function.h::: note: in expansion of macro 'REGISTER_OP_GRADIENT_UNIQ'

   REGISTER_OP_GRADIENT_UNIQ(ctr, name, fn)

   ^

./tensorflow/core/framework/function.h::: note: in expansion of macro 'REGISTER_OP_GRADIENT_UNIQ_HELPER'

   REGISTER_OP_GRADIENT_UNIQ_HELPER(__COUNTER__, name, fn)

   ^

tensorflow/core/ops/nn_grad.cc::: note: in expansion of macro 'REGISTER_OP_GRADIENT'

 REGISTER_OP_GRADIENT("BiasAdd", BiasAddGrad);

 ^

Target //tensorflow:libtensorflow.so up-to-date:

  bazel-bin/tensorflow/libtensorflow.so

INFO: Elapsed time: .039s, Critical Path: .77s

INFO: Build completed successfully,  total actions

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