Newer
Older
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
/* Copyright (c) 2023 Amazon */
/*
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions
are met:
- Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
- Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER
OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
#ifdef HAVE_CONFIG_H
#include "config.h"
#endif
#include "fargan.h"
#include "os_support.h"
#include "freq.h"
#include "fargan_data.h"
#include "lpcnet.h"
#include "pitch.h"
#include "nnet.h"
#include "lpcnet_private.h"
#define FARGAN_FEATURES (NB_FEATURES)
static void compute_fargan_cond(FARGANState *st, float *cond, const float *features, int period)
{
FARGAN *model;
float dense_in[NB_FEATURES+COND_NET_PEMBED_OUT_SIZE];
float conv1_in[COND_NET_FCONV1_IN_SIZE];
model = &st->model;
celt_assert(FARGAN_FEATURES+COND_NET_PEMBED_OUT_SIZE == model->cond_net_fdense1.nb_inputs);
celt_assert(COND_NET_FCONV1_IN_SIZE == model->cond_net_fdense1.nb_outputs);
celt_assert(COND_NET_FCONV1_OUT_SIZE == model->cond_net_fconv1.nb_outputs);
OPUS_COPY(&dense_in[NB_FEATURES], &model->cond_net_pembed.float_weights[IMAX(0,IMIN(period-32, 223))*COND_NET_PEMBED_OUT_SIZE], COND_NET_PEMBED_OUT_SIZE);
OPUS_COPY(dense_in, features, NB_FEATURES);
compute_generic_dense(&model->cond_net_fdense1, conv1_in, dense_in, ACTIVATION_TANH, st->arch);
compute_generic_conv1d(&model->cond_net_fconv1, fdense2_in, st->cond_conv1_state, conv1_in, COND_NET_FCONV1_IN_SIZE, ACTIVATION_TANH, st->arch);
compute_generic_dense(&model->cond_net_fdense2, cond, fdense2_in, ACTIVATION_TANH, st->arch);
}
static void fargan_deemphasis(float *pcm, float *deemph_mem) {
int i;
for (i=0;i<FARGAN_SUBFRAME_SIZE;i++) {
pcm[i] += FARGAN_DEEMPHASIS * *deemph_mem;
*deemph_mem = pcm[i];
}
}
static void run_fargan_subframe(FARGANState *st, float *pcm, const float *cond, int period)
{
int i, pos;
float fwc0_in[SIG_NET_INPUT_SIZE];
float gru1_in[SIG_NET_FWC0_CONV_OUT_SIZE+2*FARGAN_SUBFRAME_SIZE];
float gru2_in[SIG_NET_GRU1_OUT_SIZE+2*FARGAN_SUBFRAME_SIZE];
float gru3_in[SIG_NET_GRU2_OUT_SIZE+2*FARGAN_SUBFRAME_SIZE];
float pred[FARGAN_SUBFRAME_SIZE+4];
float prev[FARGAN_SUBFRAME_SIZE];
float pitch_gate[4];
float gain;
float gain_1;
float skip_cat[10000];
float skip_out[SIG_NET_SKIP_DENSE_OUT_SIZE];
FARGAN *model;
celt_assert(st->cont_initialized);
model = &st->model;
compute_generic_dense(&model->sig_net_cond_gain_dense, &gain, cond, ACTIVATION_LINEAR, st->arch);
pos = PITCH_MAX_PERIOD-period-2;
for (i=0;i<FARGAN_SUBFRAME_SIZE+4;i++) {
pred[i] = MIN32(1.f, MAX32(-1.f, gain_1*st->pitch_buf[IMAX(0, pos)]));
pos++;
if (pos == PITCH_MAX_PERIOD) pos -= period;
}
for (i=0;i<FARGAN_SUBFRAME_SIZE;i++) prev[i] = MAX32(-1.f, MIN16(1.f, gain_1*st->pitch_buf[PITCH_MAX_PERIOD-FARGAN_SUBFRAME_SIZE+i]));
OPUS_COPY(&fwc0_in[0], &cond[0], FARGAN_COND_SIZE);
OPUS_COPY(&fwc0_in[FARGAN_COND_SIZE], pred, FARGAN_SUBFRAME_SIZE+4);
OPUS_COPY(&fwc0_in[FARGAN_COND_SIZE+FARGAN_SUBFRAME_SIZE+4], prev, FARGAN_SUBFRAME_SIZE);
compute_generic_conv1d(&model->sig_net_fwc0_conv, gru1_in, st->fwc0_mem, fwc0_in, SIG_NET_INPUT_SIZE, ACTIVATION_TANH, st->arch);
celt_assert(SIG_NET_FWC0_GLU_GATE_OUT_SIZE == model->sig_net_fwc0_glu_gate.nb_outputs);
compute_glu(&model->sig_net_fwc0_glu_gate, gru1_in, gru1_in, st->arch);
compute_generic_dense(&model->sig_net_gain_dense_out, pitch_gate, gru1_in, ACTIVATION_SIGMOID, st->arch);
for (i=0;i<FARGAN_SUBFRAME_SIZE;i++) gru1_in[SIG_NET_FWC0_GLU_GATE_OUT_SIZE+i] = pitch_gate[0]*pred[i+2];
OPUS_COPY(&gru1_in[SIG_NET_FWC0_GLU_GATE_OUT_SIZE+FARGAN_SUBFRAME_SIZE], prev, FARGAN_SUBFRAME_SIZE);
compute_generic_gru(&model->sig_net_gru1_input, &model->sig_net_gru1_recurrent, st->gru1_state, gru1_in, st->arch);
compute_glu(&model->sig_net_gru1_glu_gate, gru2_in, st->gru1_state, st->arch);
for (i=0;i<FARGAN_SUBFRAME_SIZE;i++) gru2_in[SIG_NET_GRU1_OUT_SIZE+i] = pitch_gate[1]*pred[i+2];
OPUS_COPY(&gru2_in[SIG_NET_GRU1_OUT_SIZE+FARGAN_SUBFRAME_SIZE], prev, FARGAN_SUBFRAME_SIZE);
compute_generic_gru(&model->sig_net_gru2_input, &model->sig_net_gru2_recurrent, st->gru2_state, gru2_in, st->arch);
compute_glu(&model->sig_net_gru2_glu_gate, gru3_in, st->gru2_state, st->arch);
for (i=0;i<FARGAN_SUBFRAME_SIZE;i++) gru3_in[SIG_NET_GRU2_OUT_SIZE+i] = pitch_gate[2]*pred[i+2];
OPUS_COPY(&gru3_in[SIG_NET_GRU2_OUT_SIZE+FARGAN_SUBFRAME_SIZE], prev, FARGAN_SUBFRAME_SIZE);
compute_generic_gru(&model->sig_net_gru3_input, &model->sig_net_gru3_recurrent, st->gru3_state, gru3_in, st->arch);
compute_glu(&model->sig_net_gru3_glu_gate, &skip_cat[SIG_NET_GRU1_OUT_SIZE+SIG_NET_GRU2_OUT_SIZE], st->gru3_state, st->arch);
OPUS_COPY(skip_cat, gru2_in, SIG_NET_GRU1_OUT_SIZE);
OPUS_COPY(&skip_cat[SIG_NET_GRU1_OUT_SIZE], gru3_in, SIG_NET_GRU2_OUT_SIZE);
OPUS_COPY(&skip_cat[SIG_NET_GRU1_OUT_SIZE+SIG_NET_GRU2_OUT_SIZE+SIG_NET_GRU3_OUT_SIZE], gru1_in, SIG_NET_FWC0_CONV_OUT_SIZE);
for (i=0;i<FARGAN_SUBFRAME_SIZE;i++) skip_cat[SIG_NET_GRU1_OUT_SIZE+SIG_NET_GRU2_OUT_SIZE+SIG_NET_GRU3_OUT_SIZE+SIG_NET_FWC0_CONV_OUT_SIZE+i] = pitch_gate[3]*pred[i+2];
OPUS_COPY(&skip_cat[SIG_NET_GRU1_OUT_SIZE+SIG_NET_GRU2_OUT_SIZE+SIG_NET_GRU3_OUT_SIZE+SIG_NET_FWC0_CONV_OUT_SIZE+FARGAN_SUBFRAME_SIZE], prev, FARGAN_SUBFRAME_SIZE);
compute_generic_dense(&model->sig_net_skip_dense, skip_out, skip_cat, ACTIVATION_TANH, st->arch);
compute_glu(&model->sig_net_skip_glu_gate, skip_out, skip_out, st->arch);
compute_generic_dense(&model->sig_net_sig_dense_out, pcm, skip_out, ACTIVATION_TANH, st->arch);
for (i=0;i<FARGAN_SUBFRAME_SIZE;i++) pcm[i] *= gain;
OPUS_MOVE(st->pitch_buf, &st->pitch_buf[FARGAN_SUBFRAME_SIZE], PITCH_MAX_PERIOD-FARGAN_SUBFRAME_SIZE);
OPUS_COPY(&st->pitch_buf[PITCH_MAX_PERIOD-FARGAN_SUBFRAME_SIZE], pcm, FARGAN_SUBFRAME_SIZE);
fargan_deemphasis(pcm, &st->deemph_mem);
}
void fargan_cont(FARGANState *st, const float *pcm0, const float *features0)
{
int i;
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
float x0[FARGAN_CONT_SAMPLES];
float dummy[FARGAN_SUBFRAME_SIZE];
int period=0;
/* Pre-load features. */
for (i=0;i<5;i++) {
const float *features = &features0[i*NB_FEATURES];
st->last_period = period;
period = (int)floor(.5+256./pow(2.f,((1./60.)*((features[NB_BANDS]+1.5)*60))));
compute_fargan_cond(st, cond, features, period);
}
x0[0] = 0;
for (i=1;i<FARGAN_CONT_SAMPLES;i++) {
x0[i] = pcm0[i] - FARGAN_DEEMPHASIS*pcm0[i-1];
}
OPUS_COPY(&st->pitch_buf[PITCH_MAX_PERIOD-FARGAN_FRAME_SIZE], x0, FARGAN_FRAME_SIZE);
st->cont_initialized = 1;
for (i=0;i<FARGAN_NB_SUBFRAMES;i++) {
run_fargan_subframe(st, dummy, &cond[i*FARGAN_COND_SIZE], st->last_period);
OPUS_COPY(&st->pitch_buf[PITCH_MAX_PERIOD-FARGAN_SUBFRAME_SIZE], &x0[FARGAN_FRAME_SIZE+i*FARGAN_SUBFRAME_SIZE], FARGAN_SUBFRAME_SIZE);
}
st->deemph_mem = pcm0[FARGAN_CONT_SAMPLES-1];
}
void fargan_init(FARGANState *st)
{
int ret;
OPUS_CLEAR(st, 1);
ret = init_fargan(&st->model, fargan_arrays);
int fargan_load_model(FARGANState *st, const void *data, int len) {
WeightArray *list;
int ret;
parse_weights(&list, data, len);
ret = init_fargan(&st->model, list);
opus_free(list);
if (ret == 0) return 0;
else return -1;
}
static void fargan_synthesize_impl(FARGANState *st, float *pcm, const float *features)
{
int subframe;
int period;
celt_assert(st->cont_initialized);
period = (int)floor(.5+256./pow(2.f,((1./60.)*((features[NB_BANDS]+1.5)*60))));
compute_fargan_cond(st, cond, features, period);
for (subframe=0;subframe<FARGAN_NB_SUBFRAMES;subframe++) {
float *sub_cond;
sub_cond = &cond[subframe*FARGAN_COND_SIZE];
run_fargan_subframe(st, &pcm[subframe*FARGAN_SUBFRAME_SIZE], sub_cond, st->last_period);
}
st->last_period = period;
}
void fargan_synthesize(FARGANState *st, float *pcm, const float *features)
{
fargan_synthesize_impl(st, pcm, features);
}
void fargan_synthesize_int(FARGANState *st, opus_int16 *pcm, const float *features)
{
int i;
float fpcm[FARGAN_FRAME_SIZE];
fargan_synthesize(st, fpcm, features);
for (i=0;i<LPCNET_FRAME_SIZE;i++) pcm[i] = (int)floor(.5 + MIN32(32767, MAX32(-32767, 32768.f*fpcm[i])));
}