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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"
#ifdef DISABLE_DOT_PROD
typedef float qweight;
#else
typedef signed char qweight;
#define DOT_PROD
#endif
#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;
typedef struct {
const float *bias;
const float *input_weights;
int nb_inputs;
int nb_neurons;
int activation;
} DenseLayer;
typedef struct {
const float *bias;
const float *subias;
const qweight *input_weights;
const int *input_weights_idx;
const qweight *recurrent_weights;
int nb_inputs;
int nb_neurons;
int activation;
int reset_after;
} GRULayer;
typedef struct {
const float *bias;
const float *input_weights;
int nb_inputs;
int kernel_size;
int nb_neurons;
int activation;
} Conv1DLayer;
typedef struct {
const float *embedding_weights;
int nb_inputs;
int dim;
} EmbeddingLayer;
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);
void _lpcnet_compute_dense(const DenseLayer *layer, float *output, const float *input, int arch);
void compute_gruB(const GRULayer *gru, const float* gru_b_condition, float *state, const float *input, int arch);
int parse_weights(WeightArray **list, const unsigned char *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);
int dense_init(DenseLayer *layer, const WeightArray *arrays,
const char *bias,
const char *input_weights,
int nb_inputs,
int nb_neurons,
int activation);
int gru_init(GRULayer *layer, const WeightArray *arrays,
const char *bias,
const char *subias,
const char *input_weights,
const char *input_weights_idx,
const char *recurrent_weights,
int nb_inputs,
int nb_neurons,
int activation,
int reset_after);
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_ */
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