140 lines
3.8 KiB
C
140 lines
3.8 KiB
C
/* Copyright (c) 2008-2011 Octasic Inc.
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Written by Jean-Marc Valin */
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/*
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Redistribution and use in source and binary forms, with or without
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modification, are permitted provided that the following conditions
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are met:
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- Redistributions of source code must retain the above copyright
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notice, this list of conditions and the following disclaimer.
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- Redistributions in binary form must reproduce the above copyright
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notice, this list of conditions and the following disclaimer in the
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documentation and/or other materials provided with the distribution.
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THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
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LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
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A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE FOUNDATION OR
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CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
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EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
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PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
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PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
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LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
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NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
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SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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*/
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#ifdef HAVE_CONFIG_H
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#include "config.h"
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#endif
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#include "opus_types.h"
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#include "opus_defines.h"
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#include <math.h>
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#include "mlp.h"
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#include "arch.h"
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#include "tansig_table.h"
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#define MAX_NEURONS 100
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#if 0
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static OPUS_INLINE opus_val16 tansig_approx(opus_val32 _x) /* Q19 */
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{
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int i;
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opus_val16 xx; /* Q11 */
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/*double x, y;*/
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opus_val16 dy, yy; /* Q14 */
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/*x = 1.9073e-06*_x;*/
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if (_x>=QCONST32(8,19))
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return QCONST32(1.,14);
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if (_x<=-QCONST32(8,19))
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return -QCONST32(1.,14);
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xx = EXTRACT16(SHR32(_x, 8));
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/*i = lrint(25*x);*/
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i = SHR32(ADD32(1024,MULT16_16(25, xx)),11);
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/*x -= .04*i;*/
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xx -= EXTRACT16(SHR32(MULT16_16(20972,i),8));
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/*x = xx*(1./2048);*/
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/*y = tansig_table[250+i];*/
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yy = tansig_table[250+i];
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/*y = yy*(1./16384);*/
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dy = 16384-MULT16_16_Q14(yy,yy);
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yy = yy + MULT16_16_Q14(MULT16_16_Q11(xx,dy),(16384 - MULT16_16_Q11(yy,xx)));
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return yy;
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}
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#else
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/*extern const float tansig_table[501];*/
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static OPUS_INLINE float tansig_approx(float x)
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{
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int i;
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float y, dy;
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float sign=1;
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/* Tests are reversed to catch NaNs */
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if (!(x<8))
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return 1;
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if (!(x>-8))
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return -1;
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if (x<0)
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{
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x=-x;
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sign=-1;
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}
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i = (int)floor(.5f+25*x);
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x -= .04f*i;
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y = tansig_table[i];
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dy = 1-y*y;
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y = y + x*dy*(1 - y*x);
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return sign*y;
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}
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#endif
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#if 0
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void mlp_process(const MLP *m, const opus_val16 *in, opus_val16 *out)
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{
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int j;
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opus_val16 hidden[MAX_NEURONS];
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const opus_val16 *W = m->weights;
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/* Copy to tmp_in */
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for (j=0;j<m->topo[1];j++)
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{
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int k;
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opus_val32 sum = SHL32(EXTEND32(*W++),8);
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for (k=0;k<m->topo[0];k++)
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sum = MAC16_16(sum, in[k],*W++);
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hidden[j] = tansig_approx(sum);
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}
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for (j=0;j<m->topo[2];j++)
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{
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int k;
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opus_val32 sum = SHL32(EXTEND32(*W++),14);
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for (k=0;k<m->topo[1];k++)
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sum = MAC16_16(sum, hidden[k], *W++);
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out[j] = tansig_approx(EXTRACT16(PSHR32(sum,17)));
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}
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}
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#else
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void mlp_process(const MLP *m, const float *in, float *out)
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{
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int j;
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float hidden[MAX_NEURONS];
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const float *W = m->weights;
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/* Copy to tmp_in */
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for (j=0;j<m->topo[1];j++)
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{
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int k;
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float sum = *W++;
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for (k=0;k<m->topo[0];k++)
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sum = sum + in[k]**W++;
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hidden[j] = tansig_approx(sum);
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}
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for (j=0;j<m->topo[2];j++)
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{
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int k;
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float sum = *W++;
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for (k=0;k<m->topo[1];k++)
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sum = sum + hidden[k]**W++;
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out[j] = tansig_approx(sum);
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}
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}
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#endif
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