CentOS7上默認(rèn)的python版本還是2.7，所以需要執(zhí)行tensorflow安裝指南中python2.7相關(guān)的命令。

yum install python-pip python-devel python-virtualenv

virtualenv --system-site-packages /data/tensorflow/

source bin/activate

pip install --upgrade setuptools

pip install --upgrade?https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.2.0-cp27-none-linux_x86_64.whl

安裝成功后，來個(gè)hello world測(cè)試下

(tensorflow)[root@10.15.241.19 data]# python

Python 2.7.5 (default, Sep 15 2016, 22:37:39)

[GCC 4.8.5 20150623 (Red Hat 4.8.5-4)] on linux2

Type "help", "copyright", "credits" or "license" for more information.

>>> import tensorflow as tf

>>> hello = tf.constant('Hello, TensorFlow!')

>>> sess = tf.Session()

2017-06-26 19:40:45.027481: 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.

2017-06-26 19:40:45.027521: 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.

2017-06-26 19:40:45.027535: 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.

2017-06-26 19:40:45.027544: 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.

2017-06-26 19:40:45.027566: 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.

>>> print(sess.run(hello))

Hello, TensorFlow!

>>>