1 files changed, 69 insertions, 0 deletions
diff --git a/src/rnn.h b/src/rnn.h
new file mode 100644
index 0000000..10329f5
--- /dev/null
+++ b/src/rnn.h
@@ -0,0 +1,69 @@
+/* Copyright (c) 2017 Jean-Marc Valin */
+/*
+   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 FOUNDATION 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.
+*/
+
+#ifndef RNN_H_
+#define RNN_H_
+
+#include "rnnoise.h"
+
+#include "opus_types.h"
+
+#define WEIGHTS_SCALE (1.f/256)
+
+#define MAX_NEURONS 128
+
+#define ACTIVATION_TANH    0
+#define ACTIVATION_SIGMOID 1
+#define ACTIVATION_RELU    2
+
+typedef signed char rnn_weight;
+
+typedef struct {
+  const rnn_weight *bias;
+  const rnn_weight *input_weights;
+  int nb_inputs;
+  int nb_neurons;
+  int activation;
+} DenseLayer;
+
+typedef struct {
+  const rnn_weight *bias;
+  const rnn_weight *input_weights;
+  const rnn_weight *recurrent_weights;
+  int nb_inputs;
+  int nb_neurons;
+  int activation;
+} GRULayer;
+
+typedef struct RNNState RNNState;
+
+void compute_dense(const DenseLayer *layer, float *output, const float *input);
+
+void compute_gru(const GRULayer *gru, float *state, const float *input);
+
+void compute_rnn(RNNState *rnn, float *gains, float *vad, const float *input);
+
+#endif /* _MLP_H_ */