ref: 33adba02c7ac5fe1d1f3bd4027f42b87cddc933c
dir: /dnn/pitchdnn.c/
#ifdef HAVE_CONFIG_H #include "config.h" #endif #include <math.h> #include "pitchdnn.h" #include "os_support.h" #include "nnet.h" #include "lpcnet_private.h" int compute_pitchdnn( PitchDNNState *st, const float *if_features, const float *xcorr_features ) { float if1_out[DENSE_IF_UPSAMPLER_1_OUT_SIZE]; float downsampler_in[NB_XCORR_FEATURES + DENSE_IF_UPSAMPLER_2_OUT_SIZE]; float downsampler_out[DENSE_DOWNSAMPLER_OUT_SIZE]; float conv1_tmp1[NB_XCORR_FEATURES + 2] = {0}; float conv1_tmp2[NB_XCORR_FEATURES + 2] = {0}; float output[DENSE_FINAL_UPSAMPLER_OUT_SIZE]; int i; int pos=0; float maxval=-1; PitchDNN *model = &st->model; /* IF */ compute_generic_dense(&model->dense_if_upsampler_1, if1_out, if_features, ACTIVATION_TANH); compute_generic_dense(&model->dense_if_upsampler_2, &downsampler_in[NB_XCORR_FEATURES], if1_out, ACTIVATION_TANH); /* xcorr*/ OPUS_COPY(&conv1_tmp1[1], xcorr_features, NB_XCORR_FEATURES); compute_conv2d(&model->conv2d_1, &conv1_tmp2[1], st->xcorr_mem1, conv1_tmp1, NB_XCORR_FEATURES, ACTIVATION_TANH); compute_conv2d(&model->conv2d_1, &conv1_tmp1[1], st->xcorr_mem2, conv1_tmp2, NB_XCORR_FEATURES, ACTIVATION_TANH); compute_conv2d(&model->conv2d_1, downsampler_in, st->xcorr_mem3, conv1_tmp1, NB_XCORR_FEATURES, ACTIVATION_TANH); compute_generic_dense(&model->dense_downsampler, downsampler_out, downsampler_in, ACTIVATION_TANH); compute_generic_gru(&model->gru_1_input, &model->gru_1_recurrent, st->gru_state, downsampler_out); compute_generic_dense(&model->dense_final_upsampler, output, st->gru_state, ACTIVATION_LINEAR); for (i=0;i<DENSE_FINAL_UPSAMPLER_OUT_SIZE;i++) { if (output[i] > maxval) { pos = i; maxval = output[i]; } } return (1.f/60.f)*pos - 1.5; /*return 256.f/pow(2.f, (1.f/60.f)*i);*/ } void pitchdnn_init(PitchDNNState *st) { int ret; OPUS_CLEAR(st, 1); ret = init_pitchdnn(&st->model, pitchdnn_arrays); celt_assert(ret == 0); /* FIXME: perform arch detection. */ }