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Code Issues Projects Releases Wiki Activity

2020-10-19 21:08:55

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2020-10-19 21:08:55 +08:00
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@@ -2,7 +2,7 @@
In [1]:
```
```py
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
@@ -11,7 +11,7 @@ import theano.tensor as T
```
```
```py
Using gpu device 0: GeForce GTX 850M
```
@@ -24,7 +24,7 @@ Using gpu device 0: GeForce GTX 850M
In [2]:
```
```py
x = T.matrix('x')
s = 1 / (1 + T.exp(-x))
sigmoid = theano.function([x], s, allow_input_downcast=True)
@@ -35,7 +35,7 @@ sigmoid = theano.function([x], s, allow_input_downcast=True)
In [3]:
```
```py
sigmoid([[ 0, 1],
[-1,-2]])
@@ -43,7 +43,7 @@ sigmoid([[ 0, 1],
Out[3]:
```
```py
array([[ 0.5 , 0.7310586 ],
[ 0.26894143, 0.11920293]], dtype=float32)
```
@@ -52,7 +52,7 @@ array([[ 0.5 , 0.7310586 ],
In [4]:
```
```py
X = np.linspace(-6, 6, 100)
X = X[np.newaxis,:]
@@ -325,7 +325,7 @@ tZIkSUo9i1pJkiSl3v8H7tR/QglpVT0AAAAASUVORK5CYII=
In [5]:
```
```py
s2 = (1 + T.tanh(x / 2)) / 2
sigmoid2 = theano.function([x], s2)
@@ -337,7 +337,7 @@ sigmoid2([[ 0, 1],
Out[5]:
```
```py
array([[ 0.5 , 0.7310586 ],
[ 0.26894143, 0.11920291]], dtype=float32)
```
@@ -366,7 +366,7 @@ $$- y \log(h_{w,b}(x)) - (1-y) \log(1-h_{w,b}(x))$$
In [6]:
```
```py
rng = np.random
# 数据大小和规模
@@ -382,7 +382,7 @@ D = (rng.randn(N, feats), rng.randint(size=N, low=0, high=2))
In [7]:
```
```py
x = T.matrix('x')
y = T.vector('y')
@@ -396,7 +396,7 @@ b = theano.shared(0., name='b')
In [8]:
```
```py
h = 1 / (1 + T.exp(-T.dot(x, w) - b))
```
@@ -405,7 +405,7 @@ h = 1 / (1 + T.exp(-T.dot(x, w) - b))
In [9]:
```
```py
prediction = h > 0.5
```
@@ -414,7 +414,7 @@ prediction = h > 0.5
In [10]:
```
```py
cost = - T.mean(y * T.log(h) + (1 - y) * T.log(1 - h)) + 0.01 * T.sum(w ** 2) # 正则项，防止过拟合
gw, gb = T.grad(cost, [w, b])
@@ -424,7 +424,7 @@ gw, gb = T.grad(cost, [w, b])
In [11]:
```
```py
train = theano.function(inputs=[x, y],
outputs=cost,
updates=[[w, w - 0.1 * gw], [b, b - 0.1 * gb]],
@@ -438,7 +438,7 @@ predict = theano.function(inputs=[x],
In [12]:
```
```py
for i in xrange(10001):
err = train(D[0], D[1])
if i % 1000 == 0:
@@ -446,7 +446,7 @@ for i in xrange(10001):
```
```
```py
iter 0, error 19.295896
iter 1000, error 0.210341
iter 2000, error 0.126124
@@ -465,12 +465,12 @@ iter 10000, error 0.124845
In [13]:
```
```py
print D[1]
```
```
```py
[0 0 0 1 1 0 1 1 1 0 0 1 1 1 1 1 0 1 1 1 0 1 1 0 1 0 1 0 0 1 1 0 0 0 0 1 0
1 1 0 0 0 0 1 0 0 1 1 0 1 1 1 0 0 0 1 0 0 1 1 0 1 0 1 1 1 0 0 0 0 0 1 0 0
0 1 0 1 0 0 1 1 0 1 0 0 0 1 0 1 1 1 0 1 1 0 1 0 0 1 0 0 1 0 1 1 1 1 0 1 0
@@ -487,12 +487,12 @@ print D[1]
In [14]:
```
```py
print predict(D[0])
```
```
```py
[0 0 0 1 1 0 1 1 1 0 0 1 1 1 1 1 0 1 1 1 0 1 1 0 1 0 1 0 0 1 1 0 0 0 0 1 0
1 1 0 0 0 0 1 0 0 1 1 0 1 1 1 0 0 0 1 0 0 1 1 0 1 0 1 1 1 0 0 0 0 0 1 0 0
0 1 0 1 0 0 1 1 0 1 0 0 0 1 0 1 1 1 0 1 1 0 1 0 0 1 0 0 1 0 1 1 1 1 0 1 0