#encoding:UTF-8
__author__ = 'auroua'
import theano_test
from theano_test import pp
from theano_test import function
import theano_test.tensor as T
x = T.dscalar('x')
y = x**2
gy = T.grad(y,x)
f = function([x],y)
print f(4)
x2 = T.dmatrix('x2')
s = T.sum(1/(1+T.exp(-x2)))
gs = T.grad(s,x2)
dlogistic = function([x2],gs)
print dlogistic([[0,1],[-1,-2]])
x3 = T.dvector('x3')
y3 = x3**2
J,updates = theano_test.scan(lambda i,y,x:T.grad(y[i],x),sequences=T.arange(y3.shape[0]),non_sequences=[y3,x3])
f = function([x3],J,updates=updates)
print f([4,4])
x4 = T.dvector('x4')
y4 = x4**2
cost = y4.sum()
gy4 = T.grad(cost,x4)
H,updates2 = theano_test.scan(lambda i,gy,x4:T.grad(gy[i],x4),sequences=T.arange(gy4.shape[0]),non_sequences=[gy4,x4])
#encoding:UTF-8
__author__ = 'auroua'
from theano_test import pp
import theano_test.tensor as T
from theano_test import function
#简单标量函数的求导
x = T.dscalar('x')
y = x ** 2
gy = T.grad(y,x)
print pp(gy)
f = function([x],gy)
print f(4)
print f(94.2)
print pp(f.maker.fgraph.outputs[0])
#sigmodi的求导
xs = T.dmatrix('x')
y = T.sum(1/(1+T.exp(-xs)))
gs = T.grad(y,xs)
dlogistic = function([xs],gs)
print dlogistic([[0, 1], [-1, -2]])
