#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;
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;
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