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130 lines
3.4 KiB
C
130 lines
3.4 KiB
C
// Oh boy, why am I about to do this....
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#ifndef NETWORK_H
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#define NETWORK_H
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#include "image.h"
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#include "layer.h"
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#include "data.h"
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#include "tree.h"
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typedef enum {
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CONSTANT, STEP, EXP, POLY, STEPS, SIG, RANDOM
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} learning_rate_policy;
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typedef struct network{
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float *workspace;
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int n;
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int batch;
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int *seen;
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float epoch;
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int subdivisions;
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float momentum;
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float decay;
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layer *layers;
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int outputs;
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float *output;
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learning_rate_policy policy;
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float learning_rate;
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float gamma;
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float scale;
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float power;
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int time_steps;
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int step;
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int max_batches;
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float *scales;
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int *steps;
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int num_steps;
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int burn_in;
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int adam;
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float B1;
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float B2;
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float eps;
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int inputs;
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int h, w, c;
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int max_crop;
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int min_crop;
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float angle;
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float aspect;
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float exposure;
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float saturation;
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float hue;
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int gpu_index;
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tree *hierarchy;
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#ifdef GPU
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float **input_gpu;
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float **truth_gpu;
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#endif
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} network;
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typedef struct network_state {
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float *truth;
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float *input;
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float *delta;
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float *workspace;
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int train;
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int index;
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network net;
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} network_state;
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#ifdef GPU
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float train_networks(network *nets, int n, data d, int interval);
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void sync_nets(network *nets, int n, int interval);
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float train_network_datum_gpu(network net, float *x, float *y);
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float *network_predict_gpu(network net, float *input);
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float * get_network_output_gpu_layer(network net, int i);
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float * get_network_delta_gpu_layer(network net, int i);
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float *get_network_output_gpu(network net);
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void forward_network_gpu(network net, network_state state);
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void backward_network_gpu(network net, network_state state);
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void update_network_gpu(network net);
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#endif
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float get_current_rate(network net);
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int get_current_batch(network net);
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void free_network(network net);
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void compare_networks(network n1, network n2, data d);
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char *get_layer_string(LAYER_TYPE a);
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network make_network(int n);
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void forward_network(network net, network_state state);
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void backward_network(network net, network_state state);
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void update_network(network net);
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float train_network(network net, data d);
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float train_network_batch(network net, data d, int n);
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float train_network_sgd(network net, data d, int n);
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float train_network_datum(network net, float *x, float *y);
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matrix network_predict_data(network net, data test);
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float *network_predict(network net, float *input);
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float network_accuracy(network net, data d);
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float *network_accuracies(network net, data d, int n);
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float network_accuracy_multi(network net, data d, int n);
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void top_predictions(network net, int n, int *index);
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float *get_network_output(network net);
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float *get_network_output_layer(network net, int i);
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float *get_network_delta_layer(network net, int i);
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float *get_network_delta(network net);
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int get_network_output_size_layer(network net, int i);
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int get_network_output_size(network net);
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image get_network_image(network net);
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image get_network_image_layer(network net, int i);
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int get_predicted_class_network(network net);
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void print_network(network net);
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void visualize_network(network net);
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int resize_network(network *net, int w, int h);
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void set_batch_network(network *net, int b);
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int get_network_input_size(network net);
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float get_network_cost(network net);
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int get_network_nuisance(network net);
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int get_network_background(network net);
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#endif
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