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| | | typedef enum { |
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| | | CONVOLUTIONAL, |
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| | | CONNECTED, |
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| | | MAXPOOL |
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| | | MAXPOOL, |
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| | | SOFTMAX |
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| | | } LAYER_TYPE; |
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| | | |
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| | | typedef struct { |
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| | | int n; |
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| | | void **layers; |
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| | | LAYER_TYPE *types; |
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| | | int outputs; |
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| | | double *output; |
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| | | } network; |
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| | | |
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| | | network make_network(int n); |
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| | | void forward_network(network net, double *input); |
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| | | void learn_network(network net, double *input); |
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| | | void update_network(network net, double step); |
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| | | void train_network_batch(network net, batch b); |
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| | | double backward_network(network net, double *input, double *truth); |
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| | | void update_network(network net, double step, double momentum, double decay); |
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| | | double train_network_sgd(network net, data d, int n, double step, double momentum,double decay); |
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| | | double train_network_batch(network net, data d, int n, double step, double momentum,double decay); |
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| | | void train_network(network net, data d, double step, double momentum, double decay); |
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| | | matrix network_predict_data(network net, data test); |
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| | | double network_accuracy(network net, data d); |
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| | | double *get_network_output(network net); |
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| | | double *get_network_output_layer(network net, int i); |
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| | | double *get_network_delta_layer(network net, int i); |
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| | |
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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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| | | |
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| | | #endif |
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| | | |
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