Mac OSX 上安装 TensorFlow [CPU supp

Mac OSX 上安装 TensorFlow [CPU support only]

本文介绍在 Mac OSX 系统上如何安装 Tensorflow ，但除了操作系统包管理有差异，其它内容使用于其它操作系统。

TensorFlow 可以在 Python 2 中运行，但，Python 3 才是未来。所以，建议大家直接使用 Python 3！

注：本文安装的是 TensorFlow with CPU support only ；电脑上没有NVIDIA 显卡，所以我理解应该没法安装 TensorFlow with GPU support。

安装 Python 3

$ brew install python3

安装 virtualenv

安装 virtualenv

$ sudo pip install -U virtualenv virtualenvwrapper

将下面命令加入 ~/.bashrc 或 ~/.zshrc，比如我使用zsh，所以加到 ~/.zshrc 文件末尾:

$ echo 'test -f /usr/local/bin/virtualenvwrapper.sh && source /usr/local/bin/virtualenvwrapper.sh' >> ~/.zshrc

安装 TensorFlow

$ mkvirtualenv -p python3 tensorflow
$ pip install -U tensorflow

安装 IPython

IPython 是一个体验特别好的 Python 交互式终端，安装：

$ workon tensorflow
$ pip install ipython

测试是否安装成功

$ ipython
In [1]: import tensorflow as tf
In [2]: hello = tf.constant('Hello, TensorFlow!')
In [3]: sess = tf.Session()
In [4]: print(sess.run(hello))
b'Hello, TensorFlow!'

看到成功输出 b'Hello, TensorFlow!' 说明已经成功安装 TensorFlow ！

这行之后：

In [3]: sess = tf.Session()

可能会看到类似下面的输出：

2017-06-14 13:50:49.512831: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
2017-06-14 13:50:49.512872: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
2017-06-14 13:50:49.512881: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
2017-06-14 13:50:49.512894: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
2017-06-14 13:50:49.512903: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.

上面输出中的 W 表示 警告 (Warning)，提示从源码编译并开启一些编译选项后可以加快CPU计算速度。

三种办法避免这类错误

上面的 Warning 信息并不影响学习 TensorFlow ，只是会导致 TensorFlow 运行的不够快。但，如果你还是不希望看到这些 Warning ，可以用下面的三种方法之一。

第一种仅仅是让你不再看到 Warning，而最后两种能让 TensorFlow 运行的更快！

设置 tensorflow log level，避免 warning 输出

TF_CPP_MIN_LOG_LEVEL

• It defaults to 0, showing all logs
• To filter out INFO set to 1
• WARNINGS, additionally 2
• and to additionally filter out ERROR logs set to 3

$ ipython
In [1]: import os
In [2]: os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
In [3]: import tensorflow as tf
In [4]: hello = tf.constant('Hello, TensorFlow!')
In [5]: sess = tf.Session()
In [6]: print(sess.run(hello))
b'Hello, TensorFlow!'

安装别人编译好的 TensorFlow

移步lakshayg/tensorflow-build

更多，请参考：https://github.com/yaroslavvb/tensorflow-community-wheels

自己编译 TensorFlow

请参考官方文档：Installing TensorFlow from Sources