1.1 --- /dev/null Thu Jan 01 00:00:00 1970 +0000
1.2 +++ b/media/libopus/src/mlp.c Wed Dec 31 06:09:35 2014 +0100
1.3 @@ -0,0 +1,140 @@
1.4 +/* Copyright (c) 2008-2011 Octasic Inc.
1.5 + Written by Jean-Marc Valin */
1.6 +/*
1.7 + Redistribution and use in source and binary forms, with or without
1.8 + modification, are permitted provided that the following conditions
1.9 + are met:
1.10 +
1.11 + - Redistributions of source code must retain the above copyright
1.12 + notice, this list of conditions and the following disclaimer.
1.13 +
1.14 + - Redistributions in binary form must reproduce the above copyright
1.15 + notice, this list of conditions and the following disclaimer in the
1.16 + documentation and/or other materials provided with the distribution.
1.17 +
1.18 + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
1.19 + ``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
1.20 + LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
1.21 + A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE FOUNDATION OR
1.22 + CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
1.23 + EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
1.24 + PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
1.25 + PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
1.26 + LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
1.27 + NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
1.28 + SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
1.29 +*/
1.30 +
1.31 +#ifdef HAVE_CONFIG_H
1.32 +#include "config.h"
1.33 +#endif
1.34 +
1.35 +#include "opus_types.h"
1.36 +#include "opus_defines.h"
1.37 +
1.38 +#include <math.h>
1.39 +#include "mlp.h"
1.40 +#include "arch.h"
1.41 +#include "tansig_table.h"
1.42 +#define MAX_NEURONS 100
1.43 +
1.44 +#if 0
1.45 +static OPUS_INLINE opus_val16 tansig_approx(opus_val32 _x) /* Q19 */
1.46 +{
1.47 + int i;
1.48 + opus_val16 xx; /* Q11 */
1.49 + /*double x, y;*/
1.50 + opus_val16 dy, yy; /* Q14 */
1.51 + /*x = 1.9073e-06*_x;*/
1.52 + if (_x>=QCONST32(8,19))
1.53 + return QCONST32(1.,14);
1.54 + if (_x<=-QCONST32(8,19))
1.55 + return -QCONST32(1.,14);
1.56 + xx = EXTRACT16(SHR32(_x, 8));
1.57 + /*i = lrint(25*x);*/
1.58 + i = SHR32(ADD32(1024,MULT16_16(25, xx)),11);
1.59 + /*x -= .04*i;*/
1.60 + xx -= EXTRACT16(SHR32(MULT16_16(20972,i),8));
1.61 + /*x = xx*(1./2048);*/
1.62 + /*y = tansig_table[250+i];*/
1.63 + yy = tansig_table[250+i];
1.64 + /*y = yy*(1./16384);*/
1.65 + dy = 16384-MULT16_16_Q14(yy,yy);
1.66 + yy = yy + MULT16_16_Q14(MULT16_16_Q11(xx,dy),(16384 - MULT16_16_Q11(yy,xx)));
1.67 + return yy;
1.68 +}
1.69 +#else
1.70 +/*extern const float tansig_table[501];*/
1.71 +static OPUS_INLINE float tansig_approx(float x)
1.72 +{
1.73 + int i;
1.74 + float y, dy;
1.75 + float sign=1;
1.76 + /* Tests are reversed to catch NaNs */
1.77 + if (!(x<8))
1.78 + return 1;
1.79 + if (!(x>-8))
1.80 + return -1;
1.81 + if (x<0)
1.82 + {
1.83 + x=-x;
1.84 + sign=-1;
1.85 + }
1.86 + i = (int)floor(.5f+25*x);
1.87 + x -= .04f*i;
1.88 + y = tansig_table[i];
1.89 + dy = 1-y*y;
1.90 + y = y + x*dy*(1 - y*x);
1.91 + return sign*y;
1.92 +}
1.93 +#endif
1.94 +
1.95 +#if 0
1.96 +void mlp_process(const MLP *m, const opus_val16 *in, opus_val16 *out)
1.97 +{
1.98 + int j;
1.99 + opus_val16 hidden[MAX_NEURONS];
1.100 + const opus_val16 *W = m->weights;
1.101 + /* Copy to tmp_in */
1.102 + for (j=0;j<m->topo[1];j++)
1.103 + {
1.104 + int k;
1.105 + opus_val32 sum = SHL32(EXTEND32(*W++),8);
1.106 + for (k=0;k<m->topo[0];k++)
1.107 + sum = MAC16_16(sum, in[k],*W++);
1.108 + hidden[j] = tansig_approx(sum);
1.109 + }
1.110 + for (j=0;j<m->topo[2];j++)
1.111 + {
1.112 + int k;
1.113 + opus_val32 sum = SHL32(EXTEND32(*W++),14);
1.114 + for (k=0;k<m->topo[1];k++)
1.115 + sum = MAC16_16(sum, hidden[k], *W++);
1.116 + out[j] = tansig_approx(EXTRACT16(PSHR32(sum,17)));
1.117 + }
1.118 +}
1.119 +#else
1.120 +void mlp_process(const MLP *m, const float *in, float *out)
1.121 +{
1.122 + int j;
1.123 + float hidden[MAX_NEURONS];
1.124 + const float *W = m->weights;
1.125 + /* Copy to tmp_in */
1.126 + for (j=0;j<m->topo[1];j++)
1.127 + {
1.128 + int k;
1.129 + float sum = *W++;
1.130 + for (k=0;k<m->topo[0];k++)
1.131 + sum = sum + in[k]**W++;
1.132 + hidden[j] = tansig_approx(sum);
1.133 + }
1.134 + for (j=0;j<m->topo[2];j++)
1.135 + {
1.136 + int k;
1.137 + float sum = *W++;
1.138 + for (k=0;k<m->topo[1];k++)
1.139 + sum = sum + hidden[k]**W++;
1.140 + out[j] = tansig_approx(sum);
1.141 + }
1.142 +}
1.143 +#endif
