莫烦theano学习自修第二天激励函数
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1. 代码如下:
#!/usr/bin/env python #! _*_ coding:UTF-8 _*_ import numpy as np import theano.tensor as T import theano x = T.dmatrix(‘x‘) # 定义一个激励函数 s = 1 / (1 + T.exp(-x)) logistic = theano.function([x], s) print logistic([[0, 1], [-2, -3]]) # 一个函数输出多个变量的结果 a, b = T.dmatrices(‘a‘, ‘b‘) diff = a - b abs_diff = abs(diff) diff_squared = diff ** 2 f = theano.function([a, b], [diff, abs_diff, diff_squared]) print f(np.ones((2, 2)), np.arange(4).reshape((2, 2)) ) # 也可以写为 x1, x2, x3 = f(np.ones((2, 2)), np.arange(4).reshape((2, 2)) ) print x1, x2, x3 # 变量的名称及默认值 x, y, w = T.dscalars(‘x‘, ‘y‘, ‘w‘) z = (x + y) * w f = theano.function([ x, theano.In(y, value=1), theano.In(w, value=2, name=‘weights‘) ], z) print f(23, )
结果:
/Users/liudaoqiang/PycharmProjects/numpy/venv/bin/python /Users/liudaoqiang/Project/python_project/theano_day2/theano_test.py [[ 0.5 0.73105858] [ 0.11920292 0.04742587]] [array([[ 1., 0.], [-1., -2.]]), array([[ 1., 0.], [ 1., 2.]]), array([[ 1., 0.], [ 1., 4.]])] [[ 1. 0.] [-1. -2.]] [[ 1. 0.] [ 1. 2.]] [[ 1. 0.] [ 1. 4.]] 48.0 Process finished with exit code 0
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