02_Tensorflow基础操作 -- 常量，矩阵相乘

# python2.7
# Basic Operations example using TensorFlow library.
# Author: Aymeric Damien
# Project: https://github.com/aymericdamien/TensorFlow-Examples/ 
import tensorflow as tf
a = tf.constant(2)
b = tf.constant(3)

# Launch the default graph.
with tf.Session() as sess:
print "a: %i" % sess.run(a), "b: %i" % sess.run(b)
print "Addition with constants: %i" % sess.run(a+b)
print "Multiplication with constants: %i" % sess.run(a*b)

# 占位符
a = tf.placeholder(tf.int16)
b = tf.placeholder(tf.int16)

# Define some operations
add = tf.add(a, b)
mul = tf.multiply(a, b)

# Launch the default graph.
with tf.Session() as sess:
# Run every operation with variable input
print "Addition with variables: %i" % sess.run(add, feed_dict={a: 2, b: 3})
print "Multiplication with variables: %i" % sess.run(mul, feed_dict={a: 2, b: 3})

# More in details:
# Matrix Multiplication from TensorFlow official tutorial

matrix1 = tf.constant([[3., 3.]])

# Create another Constant that produces a 2x1 matrix.
matrix2 = tf.constant([[2.],[2.]])

product = tf.matmul(matrix1, matrix2)

# The output of the op is returned in 'result' as a numpy `ndarray` object.
with tf.Session() as sess:
result = sess.run(product)
print result

以上代码同样可以用python3进行操作，只要将print 改成print()即可。