常見簡單函數(shù)用法

- tf.clip_by_value()

tf.clip_by_value(V, min, max) 功能：截取在V，使V里面的各個元素在min和max之間

具體代碼用法

import tensorflow as tf v = tf.constant([[1.0, 2.0, 4.0],[4.0, 5.0, 6.0]]) result = tf.clip_by_value(v,2.5,4.5) with tf.Session() as sess: print(sess.run(result))# 輸出結(jié)果如下 ''' [[ 2.5 2.5 4. ] [ 4. 4.5 4.5]] '''

- numpy.random.RandomState()

numpy.random.RandomState(None|int) 功能：產(chǎn)生隨機數(shù)種子

具體代碼用法

import numpy for i in [1,2,3,4]:a = numpy.random.RandomState(None)b = a.rand(1,2)print(i)print(b)for i in [1,2,3,4]:a = numpy.random.RandomState(1)b = a.rand(1,2)print(i)print(b)# 結(jié)果輸出如下 ''' 1 [[ 0.63678388 0.53997544]] 2 [[ 0.88420701 0.11569489]] 3 [[ 0.55099434 0.9790908 ]] 4 [[ 0.6769419 0.42401973]]1 [[ 0.417022 0.72032449]] 2 [[ 0.417022 0.72032449]] 3 [[ 0.417022 0.72032449]] 4 [[ 0.417022 0.72032449]] '''

- tf.argmax()

tf.argmax(input,dimension=None,name=None) 功能：返回沿dimension最大值的索引

具體代碼用法

import tensorflow as tf val = tf.constant([[1,2,3],[4,5,6]]) valShape = tf.shape(val) t = tf.argmax(val,1) with tf.Session() as sess: result, shape = sess.run([t,valShape]) print(result) print("shape = %s" % shape)#輸出結(jié)果如下 ''' [2 2] shape = [2 3] '''

參考

https://blog.csdn.net/qq_41694195/article/details/79573494
https://blog.csdn.net/william_hehe/article/details/78635815
https://blog.csdn.net/m0_37041325/article/details/77159660

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記錄日期

2018/9/11 19:50 第一次

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