【python入门】tensorflow 小记

计算公式

需要计算：平方 矩阵内部和, 开方

# -*- coding: utf-8 -*-
import tensorflow as tf
import numpy as np

#两种定义初始数组的方法,但是注意一定用float,因为最后一步是开平方,整型会报错

# x1 = tf.constant([[1,2,3,4],[5,6,7,8],[9,10,11,12]],tf.float32)
# x2 = tf.constant([[5,6,7,8],[9,10,11,12],[1,2,3,4]],tf.float32)

x1 = np.array([[1,2,3,4],[5,6,7,8],[9,10,11,12]],float)
x2 = np.array([[5,6,7,8],[9,10,11,12],[1,2,3,4]],float)


with tf.Session() as sess:
    di = x2 - x1;
    di1 = sess.run(tf.square(di))
    print(di1)
    di2 = sess.run(tf.reduce_sum(di1,1))
    print(di2)
    di3 = sess.run(tf.sqrt(di2))
    print(di3)

输出:
dis:
[[16. 16. 16. 16.]
[16. 16. 16. 16.]
[64. 64. 64. 64.]]
dis1
[ 64. 64. 256.]
euclidean
[ 8. 8. 16.]

练手:余弦距离

# -*- coding: utf-8 -*-
import tensorflow as tf
x1 = tf.constant([[[[1], [2], [3], [4]],
                   [[5], [6], [7], [8]],
                   [[9], [10], [11], [12]]],

                  [[[1], [2], [3], [4]],
                   [[5], [6], [7], [8]],
                   [[9], [10], [11], [12]]]], tf.float32)

x2 = tf.constant([[[[3], [4], [1], [2]],
                   [[5], [7], [8], [6]],
                   [[9], [12], [11], [10]]],

                  [[[1], [2], [3], [4]],
                   [[5], [6], [7], [8]],
                   [[9], [10], [11], [12]]]], tf.float32)

with tf.Session() as sess:
    di = tf.reduce_sum(tf.mul(x1, x2))

    di1 = tf.reduce_sum(tf.mul(x1,x2),2)

    di2 = tf.sqrt(tf.reduce_sum(tf.square(x1),2))#---------------

    di3 = tf.sqrt(tf.reduce_sum(tf.square(x2), 2))  # ---------------

    di4 = tf.div(tf.div(di1,di2),di3) # 除数的维度一定要一致,否则出错

    a,b,c,d,e = sess.run([di1,di2,di3,di4,di])#----sess.run([])
    print('a:', a)  #可以看一下有个参数2是啥意思
    print('e:', e)  # 可以和上面比较一下(没有参数)
    print('b:', b)
    print('c:', c)
    print('d:', d)

答案:

(‘a:’, array([[[ 22.],
[171.],
[442.]],

   [[ 30.],
    [174.],
    [446.]]], dtype=float32))

(‘e:’, 1285.0)
(‘b:’, array([[[ 5.477225],
[13.190904],
[21.118713]],

   [[ 5.477225],
    [13.190906],
    [21.118711]]], dtype=float32))

(‘c:’, array([[[ 5.477225],
[13.190904],
[21.118713]],

   [[ 5.477225],
    [13.190906],
    [21.118711]]], dtype=float32))

(‘d:’, array([[[0.7333335],
[0.982759 ],
[0.9910313]],

   [[1.0000002],
    [1.0000001],
    [1.0000001]]], dtype=float32))