背景
按照官网预编译的最新版 TensorFlow for macOS，运行测试程序：
(venv) $ python -c "import tensorflow as tf; hello = tf.constant('Hello, TensorFlow!'); sess = tf.Session(); print(sess.run(hello))" # output: b'Hello, TensorFlow!'
输出结果有个警告信息：
(venv) $ 2019-04-19 14:45:50.202157: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
(venv) $ b'Hello, TensorFlow!'
意思是警告本机 CPU 支持 AVX2 和 FMA 指令集，但安装的预编译 TensorFlow 版本不支持。
于是从源码编译安装 TensorFlow，进行优化。
环境
| Require | TF | HW | OS | GCC | Python | Supports |
|---|---|---|---|---|---|---|
| Version | 1.13.1 | CPU | MacOS Mojave 10.14.4 (18E226) | clang-1001.0.46.4 | 3.6.5 | FMA, AVX, AVX2, SSE4.1, SSE4.2 |
构建产物：tensorflow-1.13.1-cp36-cp36m-macosx_10_13_x86_64.whl
步骤
安装 Python 和 TensorFlow 软件包依赖项
# install Homebrew if not installed
$ /usr/bin/ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"
$ export PATH="/usr/local/bin:/usr/local/sbin:$PATH"
$ brew update
# install Python 3.6.5 if not installed
$ brew install --ignore-dependencies https://raw.githubusercontent.com/Homebrew/homebrew-core/f2a764ef944b1080be64bd88dca9a1d80130c558/Formula/python.rb
$ brew link --overwrite python
$ python3 --version
# 使用特定于 shell 的命令激活该虚拟环境：
$ source ./venv/bin/activate
# 安装 TensorFlow pip 软件包依赖项
(venv) $ pip install -U pip six numpy wheel mock
(venv) $ pip install -U keras_applications==1.0.6 --no-deps
(venv) $ pip install -U keras_preprocessing==1.0.5 --no-deps
安装 Bazel
官网：https://docs.bazel.build/versions/master/install-os-x.html#install-on-mac-os-x-homebrew
# Please note that if your system has the Bazel package from homebrew core installed you first need to uninstall it by typing: `brew uninstall bazel`
# Bazel 0.20.0 because TensorFlow require version 0.21.0 or lower to build
$ brew install --ignore-dependencies https://raw.githubusercontent.com/Homebrew/homebrew-core/da863ab7d8122b8ad406eb5e8bb2253953e6bcc9/Formula/bazel.rb
# You can confirm Bazel is installed successfully by running the following command:
$ bazel version
# Once installed, you can upgrade to a newer version of Bazel using the following command:
$ brew upgrade bazelbuild/tap/bazel
下载 TensorFlow 源代码
$ source ./venv/bin/activate
(venv) $ git clone https://github.com/tensorflow/tensorflow.git
(venv) $ cd tensorflow
# 代码库默认为 master 开发分支。您也可以检出要编译的版本分支：
(venv) $ git checkout r1.13 # version 1.13.1 on 2019/04/19
配置编译系统
(venv) $ ./configure
WARNING: --batch mode is deprecated. Please instead explicitly shut down your Bazel server using the command "bazel shutdown".
INFO: Invocation ID: 824b97ef-4279-4576-8e4c-b9c405cb7a28
You have bazel 0.20.0-homebrew installed.
Please specify the location of python. [Default is /Users/xiaobailong24/venv/bin/python]:
Traceback (most recent call last):
File "<string>", line 1, in <module>
AttributeError: module 'site' has no attribute 'getsitepackages'
Found possible Python library paths:
/Users/xiaobailong24/venv/lib/python3.6/site-packages
Please input the desired Python library path to use. Default is [/Users/xiaobailong24/venv/lib/python3.6/site-packages]
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]: N
No CUDA support will be enabled for TensorFlow.
Do you wish to download a fresh release of clang? (Experimental) [y/N]: N
Clang will not be downloaded.
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 -Wno-sign-compare]:
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.
--config=dynamic_kernels # (Experimental) Build kernels into separate shared objects.
Preconfigured Bazel build configs to DISABLE default on features:
--config=noaws # Disable AWS S3 filesystem support.
--config=nogcp # Disable GCP support.
--config=nohdfs # Disable HDFS support.
--config=noignite # Disable Apacha Ignite support.
--config=nokafka # Disable Apache Kafka support.
--config=nonccl # Disable NVIDIA NCCL support.
Configuration finished
编译 pip 软件包
Bazel 构建
从源代码编译 TensorFlow 可能会消耗大量内存。如果系统内存有限，请使用以下命令限制 Bazel 的内存消耗量：–local_resources 2048,.5,1.0。我这里使用了 3072。
(venv) $ bazel build -c opt --copt=-mavx --copt=-mavx2 --copt=-mfma --copt=-msse4.1 --copt=-msse4.2 -k //tensorflow/tools/pip_package:build_pip_package --local_resources 3072,.5,1.0
编译软件包
bazel build 命令会创建一个名为 build_pip_package 的可执行文件，此文件是用于编译 pip 软件包的程序。请如下所示地运行该可执行文件，以在 /tmp/tensorflow_pkg 目录中编译 .whl 软件包。
(venv) $ ./bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/tensorflow_pkg
安装软件包
生成的 .whl 文件的文件名取决于 TensorFlow 版本和您的平台，这里生成的为：tensorflow-1.13.1-cp36-cp36m-macosx_10_13_x86_64.whl
# Please note that if your system has the tensorflow installed you first need to uninstall it by typing: `pip uninstall tensorflow`
(venv) $ pip install /tmp/tensorflow_pkg/tensorflow-1.13.1-cp36-cp36m-macosx_10_13_x86_64.whl
成功：TensorFlow 现已安装完毕。
验证安装结果
# 验证安装效果，输出结果不再有不支持 AVX2 的警告
(venv) $ python -c "import tensorflow as tf; hello = tf.constant('Hello, TensorFlow!'); sess = tf.Session(); print(sess.run(hello))" # output: b'Hello, TensorFlow!'
参考
- 【维基百科】AVX指令集
- 【lakshayg】https://github.com/lakshayg/tensorflow-build
- 【TensorFlow】从源代码编译
- 【幻悠尘的小窝】通过源码编译安装TensorFlow-CPU版本支持AVX等指令集
- 【Aleksandr Sokolovskii】[Update 2] How to build and install TensorFlow GPU/CPU for Windows from source code using bazel and Python 3.6
联系
我是 xiaobailong24，您可以通过以下平台找到我：
