GV

GeezerVison

The World Wide Web, restored to 800 pixels of glory.

Home|About|Gaming cabinet|Archives|How it works|Starter sites

On this site

  • Sign in
  • ActionsCI/CD and automation
  • CodespacesCloud development environments
  • All Features
  • Documentation
  • Training
  • Certifications
  • Build with Copilot
  • Customize Copilot
  • Integrations
  • Trending repos
  • GitHub Sponsors
  • Developer articles
  • Enterprises

This view

  • Original page
  • New address

GeezerVison is showing github.com — DeepLearning/java/src/DeepLearning/HiddenLayer.java at master · cdingding/DeepLearning

Expand file tree

/

HiddenLayer.java

Copy path
More file actions
More file actions

Latest commit

 

History

History
History
106 lines (84 loc) · 2.98 KB
/

HiddenLayer.java

Copy path

File metadata and controls

106 lines (84 loc) · 2.98 KB
Raw
Copy raw file
Download raw file
Open symbols panel
Edit and raw actions
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
package DeepLearning;
import java.util.Random;
import java.util.function.DoubleFunction;
import static DeepLearning.utils.*;
public class HiddenLayer {
public int N;
public int n_in;
public int n_out;
public double[][] W;
public double[] b;
public Random rng;
public DoubleFunction<Double> activation;
public DoubleFunction<Double> dactivation;
public HiddenLayer(int N, int n_in, int n_out, double[][] W, double[] b, Random rng, String activation) {
this.N = N;
this.n_in = n_in;
this.n_out = n_out;
if (rng == null) this.rng = new Random(1234);
else this.rng = rng;
if (W == null) {
this.W = new double[n_out][n_in];
double a = 1.0 / this.n_in;
for(int i=0; i<n_out; i++) {
for(int j=0; j<n_in; j++) {
this.W[i][j] = uniform(-a, a, rng);
}
}
} else {
this.W = W;
}
if (b == null) this.b = new double[n_out];
else this.b = b;
if (activation == "sigmoid" || activation == null) {
this.activation = (double x) -> sigmoid(x);
this.dactivation = (double x) -> dsigmoid(x);
} else if (activation == "tanh") {
this.activation = (double x) -> tanh(x);
this.dactivation = (double x) -> dtanh(x);
} else if (activation == "ReLU") {
this.activation = (double x) -> ReLU(x);
this.dactivation = (double x) -> dReLU(x);
} else {
throw new IllegalArgumentException("activation function not supported");
}
}
public double output(double[] input, double[] w, double b) {
double linear_output = 0.0;
for(int j=0; j<n_in; j++) {
linear_output += w[j] * input[j];
}
linear_output += b;
return activation.apply(linear_output);
}
public void forward(double[] input, double[] output) {
for(int i=0; i<n_out; i++) {
output[i] = this.output(input, W[i], b[i]);
}
}
public void backward(double[] input, double[] dy, double[] prev_layer_input, double[] prev_layer_dy, double[][] prev_layer_W, double lr) {
if(dy == null) dy = new double[n_out];
int prev_n_in = n_out;
int prev_n_out = prev_layer_dy.length;
for(int i=0; i<prev_n_in; i++) {
dy[i] = 0;
for(int j=0; j<prev_n_out; j++) {
dy[i] += prev_layer_dy[j] * prev_layer_W[j][i];
}
dy[i] *= dactivation.apply(prev_layer_input[i]);
}
for(int i=0; i<n_out; i++) {
for(int j=0; j<n_in; j++) {
W[i][j] += lr * dy[i] * input[j] / N;
}
b[i] += lr * dy[i] / N;
}
}
public int[] dropout(int size, double p, Random rng) {
int[] mask = new int[size];
for(int i=0; i<size; i++) {
mask[i] = binomial(1, p, rng);
}
return mask;
}
}
You are visitor 01402520 — GeezerVison does not store the pages you look up.
Best viewed with Netscape Navigator 4.7 or Internet Explorer 6 at 800×600. No cookies required.