我的第一个双隐层神经代码

import numpy as np

def nonlin(x,deriv = False):
    if deriv == True:
        return x*(1-x)
    return 1/(1+np.exp(-x))

X = np.array([[0, 0, 1], [0, 1, 1], [1, 0, 1], [1, 1, 1]])
y = np.array([[0, 1, 1, 1]]).T



w0 = 2*np.random.random((3, 4))-1

w1 = 2*np.random.random((4, 1))-1





for iter in xrange(100000):
    l0 = X
    l1 = nonlin(np.dot(l0, w0))
    l2 = nonlin(np.dot(l1, w1))
    l2_error = y - l2
    l2_grad = l2_error*nonlin(l2, deriv=True)
    l1_error = l2_grad.dot(w1.T)
    l1_grad = l1_error*nonlin(l1, deriv=True)
    w1 += l1.T.dot(l2_grad)
    w0 += l0.T.dot(l1_grad)

print 'result'
print l2