自己符号化器による等価変換

等価変換がうまくいきません．原因が分かる方がいらっしゃれば教えていただきたいです.

python
1#coding:utf-8
2
3import sys
4import numpy
5import csv
6
7class Sandglass:
8
9    def __init__(self, n_input, n_hidden):
10        self.hidden_weight = numpy.random.randn(n_hidden, n_input + 1)
11        self.output_weight = numpy.random.randn(n_input, n_hidden + 1)
12
13    def fit(self, X, epsilon, epoch):
14        self.error = numpy.zeros(epoch)
15        N = X.shape[0]
16        for epo in range(epoch):
17            print (u'epoch: %d' % epo)
18            count = 0
19            for x in X:
20                count += 1
21                self.__update_weight(x, epsilon, count)
22
23            self.error[epo] = self.__calc_error(X)
24        with open('error15.csv','a',newline='') as f:
25            writer = csv.writer(f)
26            writer.writerow(self.error)
27        f.close()
28
29    def encode(self, X):
30        Z = numpy.zeros((X.shape[0], self.hidden_weight.shape[0]))
31        Y = numpy.zeros(X.shape)
32        for (i, x) in enumerate(X):
33            z, y = self.__forward(x)
34            Z[i, :] = z
35            Y[i, :] = y
36
37        return (Z, Y)
38
39    def __forward(self, x):
40        z = self.hidden_weight.dot(numpy.hstack((1, x)))
41        y = self.output_weight.dot(numpy.hstack((1, z)))
42
43        return (z, y)
44
45    def __update_weight(self, x, epsilon, c):
46        z, y = self.__forward(x)
47
48        # update output_weight
49        output_delta = y - x
50        self.output_weight -= epsilon * output_delta.reshape(-1, 1) * numpy.hstack((1, z))
51
52        # update hidden_weight
53        hidden_delta = self.output_weight[:, 1:].T.dot(output_delta)
54        self.hidden_weight -= epsilon * hidden_delta.reshape(-1, 1) * numpy.hstack((1, x))
55
56        if (c == 1):
57            with open('inout21.csv','a',newline='') as f:
58                writer = csv.writer(f)
59                writer.writerow(x)
60                writer.writerow(y)
61            f.close()
62
63    def __calc_error(self, X):
64        N = X.shape[0]
65        err = 0.0
66        for x in X:
67            _, y = self.__forward(x)
68            err += (y - x).dot(y - x) / 2.0
69
70        return err
71
72def ReadDatafile(args):
73    return numpy.loadtxt(args, delimiter=',', dtype='float')
74
75def min_max(x, axis=None):
76    # 正規化（0,1）
77    min = x.min(axis=axis, keepdims=True)
78    max = x.max(axis=axis, keepdims=True)
79    result = (x-min)/(max-min)
80    return result
81
82if __name__ == '__main__':
83
84    args = sys.argv
85
86    print ('read data...')
87    train = ReadDatafile(args[1])
88    x = min_max(train)
89#    x = train
90    input_size = x.shape[1]
91    hidden_size = 2
92    epsilon = 0.01
93    epoch = 10000
94    stride = 2
95
96    print ('Sandglass init...')
97    sand = Sandglass(input_size, hidden_size)
98
99    print ('train...')
100    sand.fit(x[::stride], epsilon, epoch)
101
102    test = ReadDatafile(args[2])
103    y = min_max(test)
104#    y = test
105
106    print ('encode...')
107    Z, Y = sand.encode(y[::stride])
108    with open('out21.csv','a',newline='') as f:
109        writer = csv.writer(f)
110        writer.writerow(Y)
111    f.close()