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70 lines
2.2 KiB
C
70 lines
2.2 KiB
C
/* Copyright (c) 2017 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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#ifndef RNN_H_
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#define RNN_H_
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#include "rnnoise.h"
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#include "opus_types.h"
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#define WEIGHTS_SCALE (1.f/256)
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#define MAX_NEURONS 128
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#define ACTIVATION_TANH 0
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#define ACTIVATION_SIGMOID 1
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#define ACTIVATION_RELU 2
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typedef signed char rnn_weight;
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typedef struct {
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const rnn_weight *bias;
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const rnn_weight *input_weights;
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int nb_inputs;
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int nb_neurons;
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int activation;
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} DenseLayer;
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typedef struct {
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const rnn_weight *bias;
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const rnn_weight *input_weights;
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const rnn_weight *recurrent_weights;
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int nb_inputs;
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int nb_neurons;
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int activation;
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} GRULayer;
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typedef struct RNNState RNNState;
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void compute_dense(const DenseLayer *layer, float *output, const float *input);
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void compute_gru(const GRULayer *gru, float *state, const float *input);
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void compute_rnn(RNNState *rnn, float *gains, float *vad, const float *input);
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#endif /* _MLP_H_ */
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