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third_party/opus/dnn/dred_rdovae_enc.c

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+/* Copyright (c) 2022 Amazon
+   Written by Jan Buethe */
+/*
+   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.
+*/
+
+#include <math.h>
+
+#ifdef HAVE_CONFIG_H
+#include "config.h"
+#endif
+
+
+#include "dred_rdovae_enc.h"
+#include "os_support.h"
+#include "dred_rdovae_constants.h"
+
+static void conv1_cond_init(float *mem, int len, int dilation, int *init)
+{
+    if (!*init) {
+        int i;
+        for (i=0;i<dilation;i++) OPUS_CLEAR(&mem[i*len], len);
+    }
+    *init = 1;
+}
+
+void dred_rdovae_encode_dframe(
+    RDOVAEEncState *enc_state,           /* io: encoder state */
+    const RDOVAEEnc *model,
+    float *latents,                 /* o: latent vector */
+    float *initial_state,           /* o: initial state */
+    const float *input,              /* i: double feature frame (concatenated) */
+    int arch
+    )
+{
+    float padded_latents[DRED_PADDED_LATENT_DIM];
+    float padded_state[DRED_PADDED_STATE_DIM];
+    float buffer[ENC_DENSE1_OUT_SIZE + ENC_GRU1_OUT_SIZE + ENC_GRU2_OUT_SIZE + ENC_GRU3_OUT_SIZE + ENC_GRU4_OUT_SIZE + ENC_GRU5_OUT_SIZE
+               + ENC_CONV1_OUT_SIZE + ENC_CONV2_OUT_SIZE + ENC_CONV3_OUT_SIZE + ENC_CONV4_OUT_SIZE + ENC_CONV5_OUT_SIZE];
+    float state_hidden[GDENSE1_OUT_SIZE];
+    int output_index = 0;
+
+    /* run encoder stack and concatenate output in buffer*/
+    compute_generic_dense(&model->enc_dense1, &buffer[output_index], input, ACTIVATION_TANH, arch);
+    output_index += ENC_DENSE1_OUT_SIZE;
+
+    compute_generic_gru(&model->enc_gru1_input, &model->enc_gru1_recurrent, enc_state->gru1_state, buffer, arch);
+    OPUS_COPY(&buffer[output_index], enc_state->gru1_state, ENC_GRU1_OUT_SIZE);
+    output_index += ENC_GRU1_OUT_SIZE;
+    conv1_cond_init(enc_state->conv1_state, output_index, 1, &enc_state->initialized);
+    compute_generic_conv1d(&model->enc_conv1, &buffer[output_index], enc_state->conv1_state, buffer, output_index, ACTIVATION_TANH, arch);
+    output_index += ENC_CONV1_OUT_SIZE;
+
+    compute_generic_gru(&model->enc_gru2_input, &model->enc_gru2_recurrent, enc_state->gru2_state, buffer, arch);
+    OPUS_COPY(&buffer[output_index], enc_state->gru2_state, ENC_GRU2_OUT_SIZE);
+    output_index += ENC_GRU2_OUT_SIZE;
+    conv1_cond_init(enc_state->conv2_state, output_index, 2, &enc_state->initialized);
+    compute_generic_conv1d_dilation(&model->enc_conv2, &buffer[output_index], enc_state->conv2_state, buffer, output_index, 2, ACTIVATION_TANH, arch);
+    output_index += ENC_CONV2_OUT_SIZE;
+
+    compute_generic_gru(&model->enc_gru3_input, &model->enc_gru3_recurrent, enc_state->gru3_state, buffer, arch);
+    OPUS_COPY(&buffer[output_index], enc_state->gru3_state, ENC_GRU3_OUT_SIZE);
+    output_index += ENC_GRU3_OUT_SIZE;
+    conv1_cond_init(enc_state->conv3_state, output_index, 2, &enc_state->initialized);
+    compute_generic_conv1d_dilation(&model->enc_conv3, &buffer[output_index], enc_state->conv3_state, buffer, output_index, 2, ACTIVATION_TANH, arch);
+    output_index += ENC_CONV3_OUT_SIZE;
+
+    compute_generic_gru(&model->enc_gru4_input, &model->enc_gru4_recurrent, enc_state->gru4_state, buffer, arch);
+    OPUS_COPY(&buffer[output_index], enc_state->gru4_state, ENC_GRU4_OUT_SIZE);
+    output_index += ENC_GRU4_OUT_SIZE;
+    conv1_cond_init(enc_state->conv4_state, output_index, 2, &enc_state->initialized);
+    compute_generic_conv1d_dilation(&model->enc_conv4, &buffer[output_index], enc_state->conv4_state, buffer, output_index, 2, ACTIVATION_TANH, arch);
+    output_index += ENC_CONV4_OUT_SIZE;
+
+    compute_generic_gru(&model->enc_gru5_input, &model->enc_gru5_recurrent, enc_state->gru5_state, buffer, arch);
+    OPUS_COPY(&buffer[output_index], enc_state->gru5_state, ENC_GRU5_OUT_SIZE);
+    output_index += ENC_GRU5_OUT_SIZE;
+    conv1_cond_init(enc_state->conv5_state, output_index, 2, &enc_state->initialized);
+    compute_generic_conv1d_dilation(&model->enc_conv5, &buffer[output_index], enc_state->conv5_state, buffer, output_index, 2, ACTIVATION_TANH, arch);
+    output_index += ENC_CONV5_OUT_SIZE;
+
+    compute_generic_dense(&model->enc_zdense, padded_latents, buffer, ACTIVATION_LINEAR, arch);
+    OPUS_COPY(latents, padded_latents, DRED_LATENT_DIM);
+
+    /* next, calculate initial state */
+    compute_generic_dense(&model->gdense1, state_hidden, buffer, ACTIVATION_TANH, arch);
+    compute_generic_dense(&model->gdense2, padded_state, state_hidden, ACTIVATION_LINEAR, arch);
+    OPUS_COPY(initial_state, padded_state, DRED_STATE_DIM);
+}