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Convert PLC weights to blob format

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This commit is contained in:
Jean-Marc Valin 2023-05-22 03:32:53 -04:00
parent c7b6935bf2
commit 98da335009
4 changed files with 64 additions and 28 deletions
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30
dnn/lpcnet_plc.c
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@ -44,6 +44,7 @@ LPCNET_EXPORT int lpcnet_plc_get_size() {
}
LPCNET_EXPORT int lpcnet_plc_init(LPCNetPLCState *st, int options) {
int ret;
RNN_CLEAR(st, 1);
lpcnet_init(&st->lpcnet);
lpcnet_encoder_init(&st->enc);
@ -67,7 +68,9 @@ LPCNET_EXPORT int lpcnet_plc_init(LPCNetPLCState *st, int options) {
return -1;
}
st->remove_dc = !!(options&LPCNET_PLC_DC_FILTER);
return 0;
ret = init_plc_model(&st->model, lpcnet_plc_arrays);
celt_assert(ret == 0);
return ret;
}
LPCNET_EXPORT LPCNetPLCState *lpcnet_plc_create(int options) {
@ -105,13 +108,14 @@ void lpcnet_plc_fec_clear(LPCNetPLCState *st) {
}
static void compute_plc_pred(PLCNetState *net, float *out, const float *in) {
static void compute_plc_pred(LPCNetPLCState *st, float *out, const float *in) {
float zeros[3*PLC_MAX_RNN_NEURONS] = {0};
float dense_out[PLC_DENSE1_OUT_SIZE];
_lpcnet_compute_dense(&plc_dense1, dense_out, in);
compute_gruB(&plc_gru1, zeros, net->plc_gru1_state, dense_out);
compute_gruB(&plc_gru2, zeros, net->plc_gru2_state, net->plc_gru1_state);
_lpcnet_compute_dense(&plc_out, out, net->plc_gru2_state);
PLCNetState *net = &st->plc_net;
_lpcnet_compute_dense(&st->model.plc_dense1, dense_out, in);
compute_gruB(&st->model.plc_gru1, zeros, net->plc_gru1_state, dense_out);
compute_gruB(&st->model.plc_gru2, zeros, net->plc_gru2_state, net->plc_gru1_state);
_lpcnet_compute_dense(&st->model.plc_out, out, net->plc_gru2_state);
/* Artificially boost the correlation to make harmonics cleaner. */
out[19] = MIN16(.5f, out[19]+.1f);
}
@ -127,11 +131,11 @@ static int get_fec_or_pred(LPCNetPLCState *st, float *out) {
/* Update PLC state using FEC, so without Burg features. */
RNN_COPY(&plc_features[2*NB_BANDS], out, NB_FEATURES);
plc_features[2*NB_BANDS+NB_FEATURES] = -1;
compute_plc_pred(&st->plc_net, discard, plc_features);
compute_plc_pred(st, discard, plc_features);
return 1;
} else {
float zeros[2*NB_BANDS+NB_FEATURES+1] = {0};
compute_plc_pred(&st->plc_net, out, zeros);
compute_plc_pred(st, out, zeros);
if (st->fec_skip > 0) st->fec_skip--;
return 0;
}
@ -187,7 +191,7 @@ static int lpcnet_plc_update_causal(LPCNetPLCState *st, short *pcm) {
if (st->enable_blending) {
LPCNetState copy;
st->plc_net = st->plc_copy[FEATURES_DELAY];
compute_plc_pred(&st->plc_net, st->features, zeros);
compute_plc_pred(st, st->features, zeros);
for (i=0;i<FEATURES_DELAY;i++) {
/* FIXME: backtrack state, replace features. */
run_frame_network_deferred(&st->lpcnet, st->features);
@ -227,7 +231,7 @@ static int lpcnet_plc_update_causal(LPCNetPLCState *st, short *pcm) {
if (!st->blend) {
RNN_COPY(&plc_features[2*NB_BANDS], st->enc.features[0], NB_FEATURES);
plc_features[2*NB_BANDS+NB_FEATURES] = 1;
compute_plc_pred(&st->plc_net, st->features, plc_features);
compute_plc_pred(st, st->features, plc_features);
/* Discard an FEC frame that we know we will no longer need. */
if (st->fec_skip) st->fec_skip--;
else if (st->fec_read_pos < st->fec_fill_pos) st->fec_read_pos++;
@ -352,7 +356,7 @@ static int lpcnet_plc_update_non_causal(LPCNetPLCState *st, short *pcm) {
float zeros[2*NB_BANDS+NB_FEATURES+1] = {0};
RNN_COPY(zeros, plc_features, 2*NB_BANDS);
zeros[2*NB_BANDS+NB_FEATURES] = 1;
compute_plc_pred(&st->plc_net, st->features, zeros);
compute_plc_pred(st, st->features, zeros);
copy = st->lpcnet;
lpcnet_synthesize_impl(&st->lpcnet, st->features, &st->pcm[FRAME_SIZE-TRAINING_OFFSET], TRAINING_OFFSET, 0);
/* Undo initial DC offset removal so that we can take into account the last 5ms of synthesis. */
@ -405,7 +409,7 @@ static int lpcnet_plc_update_non_causal(LPCNetPLCState *st, short *pcm) {
if (st->loss_count == 0) {
RNN_COPY(&plc_features[2*NB_BANDS], st->enc.features[0], NB_FEATURES);
plc_features[2*NB_BANDS+NB_FEATURES] = 1;
compute_plc_pred(&st->plc_net, st->features, plc_features);
compute_plc_pred(st, st->features, plc_features);
lpcnet_synthesize_impl(&st->lpcnet, st->enc.features[0], &st->pcm[FRAME_SIZE-TRAINING_OFFSET], TRAINING_OFFSET, TRAINING_OFFSET);
lpcnet_synthesize_tail_impl(&st->lpcnet, pcm, FRAME_SIZE-TRAINING_OFFSET, FRAME_SIZE-TRAINING_OFFSET);
}
@ -428,7 +432,7 @@ static int lpcnet_plc_conceal_non_causal(LPCNetPLCState *st, short *pcm) {
process_queued_update(st);
st->enc.pcount = 0;
compute_plc_pred(&st->plc_net, st->features, zeros);
compute_plc_pred(st, st->features, zeros);
if (st->loss_count >= 10) st->features[0] = MAX16(-10, st->features[0]+att_table[9] - 2*(st->loss_count-9));
else st->features[0] = MAX16(-10, st->features[0]+att_table[st->loss_count]);