| | |
| | | #define NETWORK_H |
| | | |
| | | #include "image.h" |
| | | #include "params.h" |
| | | #include "data.h" |
| | | |
| | | typedef enum { |
| | | CONVOLUTIONAL, |
| | | DECONVOLUTIONAL, |
| | | CONNECTED, |
| | | MAXPOOL, |
| | | SOFTMAX, |
| | | DETECTION, |
| | | NORMALIZATION, |
| | | DROPOUT, |
| | | FREEWEIGHT, |
| | | CROP, |
| | | COST |
| | | } LAYER_TYPE; |
| | |
| | | int n; |
| | | int batch; |
| | | int seen; |
| | | int subdivisions; |
| | | float learning_rate; |
| | | float momentum; |
| | | float decay; |
| | |
| | | int outputs; |
| | | float *output; |
| | | |
| | | int inputs; |
| | | int h, w, c; |
| | | |
| | | #ifdef GPU |
| | | float **input_gpu; |
| | | float **truth_gpu; |
| | |
| | | void compare_networks(network n1, network n2, data d); |
| | | char *get_layer_string(LAYER_TYPE a); |
| | | |
| | | network make_network(int n, int batch); |
| | | void forward_network(network net, float *input, float *truth, int train); |
| | | void backward_network(network net, float *input); |
| | | 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); |
| | |
| | | void visualize_network(network net); |
| | | int resize_network(network net, int h, int w, int c); |
| | | void set_batch_network(network *net, int b); |
| | | void set_learning_network(network *net, float rate, float momentum, float decay); |
| | | int get_network_input_size(network net); |
| | | float get_network_cost(network net); |
| | | |