neural_utils.h

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#include <aio.h>
#include <math.h>
#ifndef NEURAL_UTILS_H
#define NEURAL_UTILS_H
 
typedef struct
{
    double activation;
    double activation_input;
    double local_gradient;
    double bias;
    double* weights;
}neuron;
 
typedef struct
{
    size_t nb_input;
    size_t hidden_height;
    size_t hidden_depth;
    size_t nb_output;
 
    double learning_rate;
 
    neuron* inputs;
    neuron** hidden;
    neuron* outputs;
}neural_network;
 
typedef struct
{
    double* inputs;
    double* outputs;
}training_data;
 
double sigmoid(double x);
 
double double_rand(double size);
 
void init_neuron(neuron* n, size_t nb_connection);
 
void init_neural_network(neural_network* network);
 
void save_neural_network(neural_network* network, const char* file_path);
 
char** string_split(const char* string, char separator, size_t* res_len);
 
void load_neural_network(neural_network* network, const char* content);
 
char* read_file(const char* file);
 
void process_network(neural_network* network);
 
double get_network_cost(neural_network* network, training_data expected_data);
 
void network_process_epoche(neural_network* network, neural_network* memory_network, training_data* data, size_t data_len, size_t batch_size, size_t nb_shuffle, double learning_rate, double* total_cost);
 
double get_network_total_cost(neural_network* network, training_data* datas, size_t data_len);
 
void train_network(neural_network* network, training_data* datas, size_t data_len, float learning_rate, size_t batch_size, size_t warmup, size_t warmup_iterations, size_t iterations);
 
size_t get_network_success_rate(neural_network* network, training_data* datas, size_t data_len, size_t AdaFactor);
 
training_data* load_dataset(const char* directory, size_t AdaFactor, size_t* nb_data);
 
char get_data_char_prediction(training_data data, size_t nb_output);
 
char get_network_char_prediction(neural_network* network, size_t AdaFactor);
 
void print_network_activations(neural_network* network);
 
void network_set_input_data(neural_network* network, training_data data);
 
void print_network_state(neural_network *network);
 
void print_training_debug(neural_network* network, training_data* data, size_t data_len);
 
#endif