darknet/src/network.h
2016-08-11 11:54:24 -07:00

119 lines
3.1 KiB
C

// Oh boy, why am I about to do this....
#ifndef NETWORK_H
#define NETWORK_H
#include "image.h"
#include "layer.h"
#include "data.h"
typedef enum {
CONSTANT, STEP, EXP, POLY, STEPS, SIG, RANDOM
} learning_rate_policy;
typedef struct network{
float *workspace;
int n;
int batch;
int *seen;
float epoch;
int subdivisions;
float momentum;
float decay;
layer *layers;
int outputs;
float *output;
learning_rate_policy policy;
float learning_rate;
float gamma;
float scale;
float power;
int time_steps;
int step;
int max_batches;
float *scales;
int *steps;
int num_steps;
int burn_in;
int inputs;
int h, w, c;
int max_crop;
int min_crop;
float angle;
float exposure;
float saturation;
int gpu_index;
#ifdef GPU
float **input_gpu;
float **truth_gpu;
#endif
} network;
typedef struct network_state {
float *truth;
float *input;
float *delta;
float *workspace;
int train;
int index;
network net;
} network_state;
#ifdef GPU
float train_network_datum_gpu(network net, float *x, float *y);
float *network_predict_gpu(network net, float *input);
float * get_network_output_gpu_layer(network net, int i);
float * get_network_delta_gpu_layer(network net, int i);
float *get_network_output_gpu(network net);
void forward_network_gpu(network net, network_state state);
void backward_network_gpu(network net, network_state state);
void update_network_gpu(network net);
#endif
float get_current_rate(network net);
int get_current_batch(network net);
void free_network(network net);
void compare_networks(network n1, network n2, data d);
char *get_layer_string(LAYER_TYPE a);
network make_network(int n);
void forward_network(network net, network_state state);
void backward_network(network net, network_state state);
void update_network(network net);
float train_network(network net, data d);
float train_network_batch(network net, data d, int n);
float train_network_sgd(network net, data d, int n);
float train_network_datum(network net, float *x, float *y);
matrix network_predict_data(network net, data test);
float *network_predict(network net, float *input);
float network_accuracy(network net, data d);
float *network_accuracies(network net, data d, int n);
float network_accuracy_multi(network net, data d, int n);
void top_predictions(network net, int n, int *index);
float *get_network_output(network net);
float *get_network_output_layer(network net, int i);
float *get_network_delta_layer(network net, int i);
float *get_network_delta(network net);
int get_network_output_size_layer(network net, int i);
int get_network_output_size(network net);
image get_network_image(network net);
image get_network_image_layer(network net, int i);
int get_predicted_class_network(network net);
void print_network(network net);
void visualize_network(network net);
int resize_network(network *net, int w, int h);
void set_batch_network(network *net, int b);
int get_network_input_size(network net);
float get_network_cost(network net);
int get_network_nuisance(network net);
int get_network_background(network net);
#endif