setup neurons library and some script to test this lib

neuron_t/include_neurons/include/neuron_t/neuron_t.h

@@ -0,0 +1,127 @@
+#ifndef __NEURON_T_C__H
+#define __NEURON_T_C__H
+
+#include <stdlib.h>
+#include <pthread.h>
+#include <semaphore.h>
+
+//#include "tools_t/tools_t.h"
+#include "tensor_t/tensor_t.h"
+
+extern bool randomizeInitWeight;
+
+struct config_layers{
+   size_t nb_layers;
+   size_t *sz_layers;
+   size_t **array_dim_in_layers;
+};
+typedef struct config_layers config_layers; 
+config_layers *create_config_layers(size_t nb_layers, size_t *sz_layers, size_t **array_dim_in_layers);
+config_layers *create_config_layers_from_OneD(size_t nb_layers, size_t *array_dim_in_layers);
+void free_config_layers(config_layers *pconf);
+
+
+#define GEN_NEURON_(type)\
+\
+struct neurons_##type {/* layer */\
+  size_t id_layer;\
+  size_t iteration_step;\
+  size_t nb_prod_thread;\
+  size_t nb_calc_thread;\
+  type initial_learning_rate;\
+  type learning_rate;\
+  type decay_rate;\
+  size_t drop_rate;\
+  void (*update_learning_rate)(struct neurons_##type *N); \
+  tensor_##type *input; \
+  tensor_##type *net; /* output tensor_prodContract */\
+  tensor_##type *output; \
+  tensor_##type *target; \
+  tensor_##type *weight_in; /* weight link in */\
+  tensor_##type *bias; /* bias */\
+  tensor_##type *weight_out; /* weight link out */\
+  tensor_##type *delta_out; /* delta */\
+  struct neurons_##type *prev_layer;\
+  struct neurons_##type *next_layer;\
+  void (*TensorContraction)(tensor_##type **MM, tensor_##type *M0, tensor_##type *M1, size_t contractionNumber, size_t nbthread);/* nbthread is ignored if not required ! */\
+  void (*TensorProduct)(tensor_##type **MM, tensor_##type *M0, tensor_##type *M1, size_t nbthread);/* nbthread is ignored if not required ! */\
+  type (*dL)(type t, type o);\
+  type (*L)(type t, type o);\
+  type (*f_act)(type x);\
+  type (*d_f_act)(type x);\
+};\
+typedef struct neurons_##type neurons_##type;\
+\
+struct func_act_##type {\
+  type (*func_act)(type x); /* function activation */\
+  type (*deriv_func_act)(type x); /* derivate func act */\
+};\
+\
+void do_not_update_learnig_rate_##type(neurons_##type *N);\
+void time_based_update_learning_rate_##type(neurons_##type *nr);\
+void step_based_update_learning_rate_##type(neurons_##type *nr);\
+void setup_learning_rate_params_neurons_##type(neurons_##type *base,type initial_learning_rate, type decay_rate, size_t drop_rate, void (*update_learning_rate)(neurons_##type *));\
+/*void calc_net_neurons_##type(neurons_##type *nr);*/\
+void calc_out_neurons_##type(neurons_##type *nr);\
+void calc_delta_neurons_##type(neurons_##type *nr);\
+void update_weight_neurons_##type(neurons_##type *nr);\
+/*void setup_networks_##type(neurons_##type **base_nr, size_t **array_dim_in_layers, size_t *tab_sz_layers, size_t nb_layers);*/\
+void init_copy_in_out_networks_from_tensors_##type(neurons_##type *nr, tensor_##type *input, tensor_##type *target);\
+void init_in_out_networks_from_tensors_##type(neurons_##type *nr, tensor_##type *input, tensor_##type *target, neurons_##type *base);\
+void init_in_out_all_networks_##type(neurons_##type *nr, tensor_##type *in, tensor_##type *out);\
+void setup_networks_alloutputs_GLOBAL_rdm01_##type(neurons_##type **base_nr, size_t **array_dim_in_layers, size_t *sz_layers, size_t nb_layers);\
+void setup_networks_alloutputs_##type(neurons_##type **base_nr, size_t **array_dim_in_layers, size_t *sz_layers, size_t nb_layers, bool randomize, type minR, type maxR,  int randomRange);\
+void setup_networks_alloutputs_config_##type(neurons_##type **base_nr, config_layers *lconf, bool randomize, type minR, type maxR,  int randomRange);\
+void setup_networks_layers_without_weights_##type(neurons_##type **base_nr, size_t **array_dim_in_layers, size_t *sz_layers, size_t nb_layers);\
+void setup_networks_layers_without_weights_from_config_##type(neurons_##type **base, config_layers *pconf);\
+void setup_networks_OneD_##type(neurons_##type **base_nr, size_t *array_dim_in_layers, size_t nb_layers, bool randomize, type minR, type maxR,  int randomRange);\
+void init_in_out_all_networks_OneD_##type(neurons_##type *nr, type *in, size_t sz_in, type *out, size_t sz_out);\
+void print_neurons_msg_##type(neurons_##type *nr, char * msg);\
+\
+void free_neurons_##type(neurons_##type *base);\
+\
+void setup_all_layers_functions_##type(neurons_##type *base, \
+  void (*TensorContraction)(tensor_##type **MM, tensor_##type *M0, tensor_##type *M1, size_t contractionNumber, size_t nbthread),/* nbthread is ignored if not required ! */\
+  void (*TensorProduct)(tensor_##type **MM, tensor_##type *M0, tensor_##type *M1, size_t nbthread),/* nbthread is ignored if not required ! */\
+  type (*dL)(type t, type o),\
+  type (*L)(type t, type o),\
+  type (*f_act)(type x),\
+  type (*d_f_act)(type x)\
+);\
+void setup_all_layers_params_##type(neurons_##type *base,\
+  size_t nb_prod_thread,\
+  size_t nb_calc_thread,\
+  type learning_rate);\
+type error_out_##type(neurons_##type *base);\
+struct data_set_##type{\
+  size_t size;\
+  tensor_##type **input;\
+  tensor_##type **target;\
+};\
+typedef struct data_set_##type data_set_##type;\
+void free_data_set_##type(data_set_##type *ds);\
+data_set_##type*  fill_data_set_from_file_##type(char * file_input, size_t pivotSplit);\
+void print_data_set_msg_##type(data_set_##type *ds, char *msg);\
+\
+size_t learning_online_neurons_##type(neurons_##type *base, data_set_##type *dataset, bool (*condition)(type, size_t));\
+size_t learning_online2_neurons_##type(neurons_##type *base, data_set_##type *dataset, bool (*condition)(type, size_t));\
+\
+void print_predict_by_network_neurons_##type(neurons_##type *base, tensor_##type *input);\
+void print_predict_by_network_with_error_neurons_##type(neurons_##type *base, tensor_##type *input, tensor_##type *target);\
+\
+struct cloneuronset_##type{\
+  size_t nb_clone;\
+  config_layers *conf;\
+  neurons_##type *base;\
+  neurons_##type **cloneurons;\
+};\
+typedef struct cloneuronset_##type cloneuronset_##type;\
+void free_cloneuronset_##type(cloneuronset_##type *clnrnst);\
+cloneuronset_##type * create_cloneuronset_from_base_conf_##type(neurons_##type *base, config_layers *conf, size_t nb_clone);\
+size_t learning_cloneuronset_##type(cloneuronset_##type *clnrnst, data_set_##type *dataset, bool (*condition)(type, size_t));\
+
+GEN_NEURON_(TYPE_FLOAT)
+GEN_NEURON_(TYPE_DOUBLE)
+
+
+#endif /*__NEURON_T_C__H*/