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third_party/opus/dnn/nnet.h

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+/* Copyright (c) 2018 Mozilla
+   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 NNET_H_
+#define NNET_H_
+
+#include <stddef.h>
+#include "opus_types.h"
+
+#define ACTIVATION_LINEAR  0
+#define ACTIVATION_SIGMOID 1
+#define ACTIVATION_TANH    2
+#define ACTIVATION_RELU    3
+#define ACTIVATION_SOFTMAX 4
+#define ACTIVATION_SWISH   5
+
+#define WEIGHT_BLOB_VERSION 0
+#define WEIGHT_BLOCK_SIZE 64
+typedef struct {
+  const char *name;
+  int type;
+  int size;
+  const void *data;
+} WeightArray;
+
+#define WEIGHT_TYPE_float 0
+#define WEIGHT_TYPE_int 1
+#define WEIGHT_TYPE_qweight 2
+#define WEIGHT_TYPE_int8 3
+
+typedef struct {
+  char head[4];
+  int version;
+  int type;
+  int size;
+  int block_size;
+  char name[44];
+} WeightHead;
+
+/* Generic sparse affine transformation. */
+typedef struct {
+  const float *bias;
+  const float *subias;
+  const opus_int8 *weights;
+  const float *float_weights;
+  const int *weights_idx;
+  const float *diag;
+  const float *scale;
+  int nb_inputs;
+  int nb_outputs;
+} LinearLayer;
+
+/* Generic sparse affine transformation. */
+typedef struct {
+  const float *bias;
+  const float *float_weights;
+  int in_channels;
+  int out_channels;
+  int ktime;
+  int kheight;
+} Conv2dLayer;
+
+
+void compute_generic_dense(const LinearLayer *layer, float *output, const float *input, int activation, int arch);
+void compute_generic_gru(const LinearLayer *input_weights, const LinearLayer *recurrent_weights, float *state, const float *in, int arch);
+void compute_generic_conv1d(const LinearLayer *layer, float *output, float *mem, const float *input, int input_size, int activation, int arch);
+void compute_generic_conv1d_dilation(const LinearLayer *layer, float *output, float *mem, const float *input, int input_size, int dilation, int activation, int arch);
+void compute_glu(const LinearLayer *layer, float *output, const float *input, int arch);
+void compute_gated_activation(const LinearLayer *layer, float *output, const float *input, int activation, int arch);
+
+
+int parse_weights(WeightArray **list, const void *data, int len);
+
+
+extern const WeightArray lpcnet_arrays[];
+extern const WeightArray plcmodel_arrays[];
+extern const WeightArray rdovaeenc_arrays[];
+extern const WeightArray rdovaedec_arrays[];
+extern const WeightArray fwgan_arrays[];
+extern const WeightArray fargan_arrays[];
+extern const WeightArray pitchdnn_arrays[];
+extern const WeightArray lossgen_arrays[];
+
+int linear_init(LinearLayer *layer, const WeightArray *arrays,
+  const char *bias,
+  const char *subias,
+  const char *weights,
+  const char *float_weights,
+  const char *weights_idx,
+  const char *diag,
+  const char *scale,
+  int nb_inputs,
+  int nb_outputs);
+
+int conv2d_init(Conv2dLayer *layer, const WeightArray *arrays,
+  const char *bias,
+  const char *float_weights,
+  int in_channels,
+  int out_channels,
+  int ktime,
+  int kheight);
+
+
+void compute_linear_c(const LinearLayer *linear, float *out, const float *in);
+void compute_activation_c(float *output, const float *input, int N, int activation);
+void compute_conv2d_c(const Conv2dLayer *conv, float *out, float *mem, const float *in, int height, int hstride, int activation);
+
+
+#if defined(OPUS_ARM_MAY_HAVE_DOTPROD) || defined(OPUS_ARM_MAY_HAVE_NEON_INTR)
+#include "arm/dnn_arm.h"
+#endif
+
+#if defined(OPUS_X86_MAY_HAVE_SSE2)
+#include "x86/dnn_x86.h"
+#endif
+
+#ifndef OVERRIDE_COMPUTE_LINEAR
+#define compute_linear(linear, out, in, arch) ((void)(arch),compute_linear_c(linear, out, in))
+#endif
+
+#ifndef OVERRIDE_COMPUTE_ACTIVATION
+#define compute_activation(output, input, N, activation, arch) ((void)(arch),compute_activation_c(output, input, N, activation))
+#endif
+
+#ifndef OVERRIDE_COMPUTE_CONV2D
+#define compute_conv2d(conv, out, mem, in, height, hstride, activation, arch) ((void)(arch),compute_conv2d_c(conv, out, mem, in, height, hstride, activation))
+#endif
+
+#if defined(__x86_64__) && !defined(OPUS_X86_MAY_HAVE_SSE4_1) && !defined(OPUS_X86_MAY_HAVE_AVX2)
+#if defined(_MSC_VER)
+#pragma message ("Only SSE and SSE2 are available. On newer machines, enable SSSE3/AVX/AVX2 to get better performance")
+#else
+#warning "Only SSE and SSE2 are available. On newer machines, enable SSSE3/AVX/AVX2 using -march= to get better performance"
+#endif
+#endif
+
+
+
+#endif /* NNET_H_ */