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1 /* Copyright (c) 2008-2011 Octasic Inc.
2    Written by Jean-Marc Valin */
3 /*
4    Redistribution and use in source and binary forms, with or without
5    modification, are permitted provided that the following conditions
6    are met:
7 
8    - Redistributions of source code must retain the above copyright
9    notice, this list of conditions and the following disclaimer.
10 
11    - Redistributions in binary form must reproduce the above copyright
12    notice, this list of conditions and the following disclaimer in the
13    documentation and/or other materials provided with the distribution.
14 
15    THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
16    ``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
17    LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
18    A PARTICULAR PURPOSE ARE DISCLAIMED.  IN NO EVENT SHALL THE FOUNDATION OR
19    CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
20    EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
21    PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
22    PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
23    LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
24    NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
25    SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
26 */
27 
28 #ifdef HAVE_CONFIG_H
29 #include "config.h"
30 #endif
31 
32 #include "opus_types.h"
33 #include "opus_defines.h"
34 
35 #include <math.h>
36 #include "mlp.h"
37 #include "arch.h"
38 #include "tansig_table.h"
39 #define MAX_NEURONS 100
40 
41 #if 0
42 static OPUS_INLINE opus_val16 tansig_approx(opus_val32 _x) /* Q19 */
43 {
44     int i;
45     opus_val16 xx; /* Q11 */
46     /*double x, y;*/
47     opus_val16 dy, yy; /* Q14 */
48     /*x = 1.9073e-06*_x;*/
49     if (_x>=QCONST32(8,19))
50         return QCONST32(1.,14);
51     if (_x<=-QCONST32(8,19))
52         return -QCONST32(1.,14);
53     xx = EXTRACT16(SHR32(_x, 8));
54     /*i = lrint(25*x);*/
55     i = SHR32(ADD32(1024,MULT16_16(25, xx)),11);
56     /*x -= .04*i;*/
57     xx -= EXTRACT16(SHR32(MULT16_16(20972,i),8));
58     /*x = xx*(1./2048);*/
59     /*y = tansig_table[250+i];*/
60     yy = tansig_table[250+i];
61     /*y = yy*(1./16384);*/
62     dy = 16384-MULT16_16_Q14(yy,yy);
63     yy = yy + MULT16_16_Q14(MULT16_16_Q11(xx,dy),(16384 - MULT16_16_Q11(yy,xx)));
64     return yy;
65 }
66 #else
67 /*extern const float tansig_table[501];*/
tansig_approx(float x)68 static OPUS_INLINE float tansig_approx(float x)
69 {
70     int i;
71     float y, dy;
72     float sign=1;
73     /* Tests are reversed to catch NaNs */
74     if (!(x<8))
75         return 1;
76     if (!(x>-8))
77         return -1;
78 #ifndef FIXED_POINT
79     /* Another check in case of -ffast-math */
80     if (celt_isnan(x))
81        return 0;
82 #endif
83     if (x<0)
84     {
85        x=-x;
86        sign=-1;
87     }
88     i = (int)floor(.5f+25*x);
89     x -= .04f*i;
90     y = tansig_table[i];
91     dy = 1-y*y;
92     y = y + x*dy*(1 - y*x);
93     return sign*y;
94 }
95 #endif
96 
97 #if 0
98 void mlp_process(const MLP *m, const opus_val16 *in, opus_val16 *out)
99 {
100     int j;
101     opus_val16 hidden[MAX_NEURONS];
102     const opus_val16 *W = m->weights;
103     /* Copy to tmp_in */
104     for (j=0;j<m->topo[1];j++)
105     {
106         int k;
107         opus_val32 sum = SHL32(EXTEND32(*W++),8);
108         for (k=0;k<m->topo[0];k++)
109             sum = MAC16_16(sum, in[k],*W++);
110         hidden[j] = tansig_approx(sum);
111     }
112     for (j=0;j<m->topo[2];j++)
113     {
114         int k;
115         opus_val32 sum = SHL32(EXTEND32(*W++),14);
116         for (k=0;k<m->topo[1];k++)
117             sum = MAC16_16(sum, hidden[k], *W++);
118         out[j] = tansig_approx(EXTRACT16(PSHR32(sum,17)));
119     }
120 }
121 #else
mlp_process(const MLP * m,const float * in,float * out)122 void mlp_process(const MLP *m, const float *in, float *out)
123 {
124     int j;
125     float hidden[MAX_NEURONS];
126     const float *W = m->weights;
127     /* Copy to tmp_in */
128     for (j=0;j<m->topo[1];j++)
129     {
130         int k;
131         float sum = *W++;
132         for (k=0;k<m->topo[0];k++)
133             sum = sum + in[k]**W++;
134         hidden[j] = tansig_approx(sum);
135     }
136     for (j=0;j<m->topo[2];j++)
137     {
138         int k;
139         float sum = *W++;
140         for (k=0;k<m->topo[1];k++)
141             sum = sum + hidden[k]**W++;
142         out[j] = tansig_approx(sum);
143     }
144 }
145 #endif
146