TensorFlow学习笔记：2、TensorFlow超简单入门程序

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TensorFlow学习笔记：2、TensorFlow超简单入门程序

2.1 HelloWorld代码说明

import tensorflow as tf
加载TensorFlow模块
hello=tf.constant(“Hello,TensorFlow!”)
定义计算图（此处定义一个常量）
session=tf.Session()
获取TensorFlow的session
print(session.run(hello))
通过session，执行计算图

2.2 演示程序

[root@node1 ~]# pythonPython 2.7.5 (default, Aug  4 2017, 00:39:18) [GCC 4.8.5 20150623 (Red Hat 4.8.5-16)] on linux2Type "help", "copyright", "credits" or "license" for more information.>>> import tensorflow as tf>>> hello=tf.constant("Hello,TensorFlow!")>>> session=tf.Session()2017-10-14 23:26:49.914154: 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.2017-10-14 23:26:49.914260: 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.2017-10-14 23:26:49.914274: 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.2017-10-14 23:26:49.914284: 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(session.run(hello))Hello,TensorFlow!>>>

2.3 a+b计算

>>> import tensorflow as tf>>> session=tf.Session()2017-10-14 11:23:01.914540: 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.2017-10-14 11:23:01.914572: 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.2017-10-14 11:23:01.914582: 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.2017-10-14 11:23:01.914592: 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.>>> x=tf.constant(5)>>> y=tf.constant(7)>>> print(session.run(x+y))12>>>

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