setup neurons library and some script to test this lib
This commit is contained in:
+3
-4
@@ -70,10 +70,9 @@ $(DEPS):
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$(MAKE) -C $@ $(MAKECMDGOALS)
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update_headers: $(PROJECT_LIB)
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for file_h in $(DEPS); do
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cd ${file_h}/src
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#cp --parents "$$file_h/include/" include_neurons/; done
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cp --parents "*/*.h" "$(INCLUDE_HEADERS_NEURONS)/" ;
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for file_h in $(DEPS); do \
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cd "$$file_h/src" ; \
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cp --parents */*.h $(INCLUDE_HEADERS_NEURONS)/ ; \
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done
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@@ -0,0 +1,70 @@
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#ifndef __DIMENSION_T__H__
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#define __DIMENSION_T__H__
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#include "permutation_t/permutation_t.h"
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extern bool endian;
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bool isLessEqThan(long int a, long int b) ;
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bool isLessThan(long int a, long int b) ;
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bool isGreatEqThan(long int a, long int b) ;
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bool isGreatThan(long int a, long int b) ;
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long int incr(long int i) ;
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long int decr(long int i) ;
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typedef struct PERMUTATION_TYPE_SIZE_T dimension ;
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dimension * create_dim(size_t size);
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dimension * create_reverse_dim(size_t size);
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dimension* init_dim(size_t *t, size_t sz);
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dimension* init_copy_dim(size_t *t, size_t sz);
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dimension* clone_dim(dimension *dim);
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void free_dimension(dimension *d);
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bool is_equal_dim(dimension *d0, dimension *d1);
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dimension* sub_minus_dim_head(dimension *t, size_t minusSubdim);
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dimension* sub_minus_dim_tail(dimension *t, size_t minusSubdim);
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dimension* sub_dim_head(dimension *t, size_t subdim);
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dimension* sub_dim_tail(dimension *t, size_t subdim);
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dimension* sub_copy_minus_dim_head(dimension *t, size_t minusSubdim);
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dimension* sub_copy_minus_dim_tail(dimension *t, size_t minusSubdim);
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dimension* sub_copy_dim_head(dimension *t, size_t sub_copydim);
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dimension* sub_copy_dim_tail(dimension *t, size_t sub_copydim);
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void split_dim_part(dimension *root, dimension **part_1, dimension **part_2, size_t pivotSplit, size_t rangeInPivot );
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void add_copy_dimension(dimension **d, dimension *d0, dimension *d1);
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void min_copy_dimension(dimension **d, dimension *d0, dimension *d1);
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void add_dimension(dimension **d, dimension *d0, dimension *d1);
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void min_dimension(dimension **d, dimension *d0, dimension *d1);
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void printDebug_dimension(dimension *d, char *msg);
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size_t sprint_dimension(char **dimContent, dimension *d);
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void updateRankDim(dimension *dim);
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size_t LineFromCoord(size_t *coo, dimension *dim);
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size_t* CoordFromLin(size_t line, dimension *dim);
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void vCoordFromLin(size_t *ret, size_t line, dimension *dim );
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void increment_dim_var(dimension *d);
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void decrement_dim_var(dimension *d);
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struct list_perm_in_dim{
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size_t index;
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size_t perm;
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struct list_perm_in_dim *next;
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};
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typedef struct list_perm_in_dim list_perm_in_dim;
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void append_in_list_perm(list_perm_in_dim **list_p, size_t perm);
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dimension * create_dim_from_list_perm( list_perm_in_dim *l_p);
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void free_list_perm_in_dim(list_perm_in_dim *l_p);
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#endif /* __DIMENSION_T__H__ */
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//int compare_dimension(dimension *d1, dimension *d2);
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@@ -0,0 +1,127 @@
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#ifndef __NEURON_T_C__H
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#define __NEURON_T_C__H
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#include <stdlib.h>
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#include <pthread.h>
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#include <semaphore.h>
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//#include "tools_t/tools_t.h"
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#include "tensor_t/tensor_t.h"
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extern bool randomizeInitWeight;
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struct config_layers{
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size_t nb_layers;
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size_t *sz_layers;
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size_t **array_dim_in_layers;
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};
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typedef struct config_layers config_layers;
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config_layers *create_config_layers(size_t nb_layers, size_t *sz_layers, size_t **array_dim_in_layers);
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config_layers *create_config_layers_from_OneD(size_t nb_layers, size_t *array_dim_in_layers);
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void free_config_layers(config_layers *pconf);
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#define GEN_NEURON_(type)\
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\
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struct neurons_##type {/* layer */\
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size_t id_layer;\
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size_t iteration_step;\
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size_t nb_prod_thread;\
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size_t nb_calc_thread;\
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type initial_learning_rate;\
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type learning_rate;\
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type decay_rate;\
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size_t drop_rate;\
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void (*update_learning_rate)(struct neurons_##type *N); \
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tensor_##type *input; \
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tensor_##type *net; /* output tensor_prodContract */\
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tensor_##type *output; \
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tensor_##type *target; \
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tensor_##type *weight_in; /* weight link in */\
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tensor_##type *bias; /* bias */\
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tensor_##type *weight_out; /* weight link out */\
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tensor_##type *delta_out; /* delta */\
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struct neurons_##type *prev_layer;\
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struct neurons_##type *next_layer;\
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void (*TensorContraction)(tensor_##type **MM, tensor_##type *M0, tensor_##type *M1, size_t contractionNumber, size_t nbthread);/* nbthread is ignored if not required ! */\
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void (*TensorProduct)(tensor_##type **MM, tensor_##type *M0, tensor_##type *M1, size_t nbthread);/* nbthread is ignored if not required ! */\
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type (*dL)(type t, type o);\
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type (*L)(type t, type o);\
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type (*f_act)(type x);\
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type (*d_f_act)(type x);\
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};\
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typedef struct neurons_##type neurons_##type;\
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\
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struct func_act_##type {\
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type (*func_act)(type x); /* function activation */\
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type (*deriv_func_act)(type x); /* derivate func act */\
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};\
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\
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void do_not_update_learnig_rate_##type(neurons_##type *N);\
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void time_based_update_learning_rate_##type(neurons_##type *nr);\
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void step_based_update_learning_rate_##type(neurons_##type *nr);\
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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 *));\
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/*void calc_net_neurons_##type(neurons_##type *nr);*/\
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void calc_out_neurons_##type(neurons_##type *nr);\
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void calc_delta_neurons_##type(neurons_##type *nr);\
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void update_weight_neurons_##type(neurons_##type *nr);\
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/*void setup_networks_##type(neurons_##type **base_nr, size_t **array_dim_in_layers, size_t *tab_sz_layers, size_t nb_layers);*/\
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void init_copy_in_out_networks_from_tensors_##type(neurons_##type *nr, tensor_##type *input, tensor_##type *target);\
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void init_in_out_networks_from_tensors_##type(neurons_##type *nr, tensor_##type *input, tensor_##type *target, neurons_##type *base);\
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void init_in_out_all_networks_##type(neurons_##type *nr, tensor_##type *in, tensor_##type *out);\
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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);\
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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);\
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void setup_networks_alloutputs_config_##type(neurons_##type **base_nr, config_layers *lconf, bool randomize, type minR, type maxR, int randomRange);\
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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);\
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void setup_networks_layers_without_weights_from_config_##type(neurons_##type **base, config_layers *pconf);\
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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);\
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void init_in_out_all_networks_OneD_##type(neurons_##type *nr, type *in, size_t sz_in, type *out, size_t sz_out);\
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void print_neurons_msg_##type(neurons_##type *nr, char * msg);\
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\
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void free_neurons_##type(neurons_##type *base);\
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\
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void setup_all_layers_functions_##type(neurons_##type *base, \
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void (*TensorContraction)(tensor_##type **MM, tensor_##type *M0, tensor_##type *M1, size_t contractionNumber, size_t nbthread),/* nbthread is ignored if not required ! */\
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void (*TensorProduct)(tensor_##type **MM, tensor_##type *M0, tensor_##type *M1, size_t nbthread),/* nbthread is ignored if not required ! */\
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type (*dL)(type t, type o),\
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type (*L)(type t, type o),\
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type (*f_act)(type x),\
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type (*d_f_act)(type x)\
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);\
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void setup_all_layers_params_##type(neurons_##type *base,\
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size_t nb_prod_thread,\
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size_t nb_calc_thread,\
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type learning_rate);\
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type error_out_##type(neurons_##type *base);\
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struct data_set_##type{\
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size_t size;\
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tensor_##type **input;\
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tensor_##type **target;\
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};\
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typedef struct data_set_##type data_set_##type;\
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void free_data_set_##type(data_set_##type *ds);\
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data_set_##type* fill_data_set_from_file_##type(char * file_input, size_t pivotSplit);\
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void print_data_set_msg_##type(data_set_##type *ds, char *msg);\
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\
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size_t learning_online_neurons_##type(neurons_##type *base, data_set_##type *dataset, bool (*condition)(type, size_t));\
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size_t learning_online2_neurons_##type(neurons_##type *base, data_set_##type *dataset, bool (*condition)(type, size_t));\
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\
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void print_predict_by_network_neurons_##type(neurons_##type *base, tensor_##type *input);\
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void print_predict_by_network_with_error_neurons_##type(neurons_##type *base, tensor_##type *input, tensor_##type *target);\
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\
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struct cloneuronset_##type{\
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size_t nb_clone;\
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config_layers *conf;\
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neurons_##type *base;\
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neurons_##type **cloneurons;\
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};\
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typedef struct cloneuronset_##type cloneuronset_##type;\
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void free_cloneuronset_##type(cloneuronset_##type *clnrnst);\
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cloneuronset_##type * create_cloneuronset_from_base_conf_##type(neurons_##type *base, config_layers *conf, size_t nb_clone);\
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size_t learning_cloneuronset_##type(cloneuronset_##type *clnrnst, data_set_##type *dataset, bool (*condition)(type, size_t));\
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GEN_NEURON_(TYPE_FLOAT)
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GEN_NEURON_(TYPE_DOUBLE)
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#endif /*__NEURON_T_C__H*/
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@@ -0,0 +1,54 @@
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#ifndef __PERMUTATION_T_C_H__
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#define __PERMUTATION_T_C_H__
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#include "tools_t/tools_t.h"
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#include "set_theoric_t/set_theoric_t.h"
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/* struct of permutation, not necessarly set_theoric
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*
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* */
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#define GENERATE_PERMUTATION(type)\
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struct PERMUTATION_##type{\
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size_t size;\
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size_t rank;\
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type * perm; \
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};\
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\
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typedef struct PERMUTATION_##type PERMUTATION_##type;\
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PERMUTATION_##type * CREATE_PERMUTATION_##type(size_t size);\
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PERMUTATION_##type * INIT_PERMUTATION_##type(type *perm, size_t size);\
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PERMUTATION_##type * INIT_COPY_PERMUTATION_##type(type *perm, size_t size);\
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void free_permut_##type(PERMUTATION_##type * permut);\
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PERMUTATION_TYPE_SIZE_T * TRANSLATE_TO_SET_THEORIC_SIZE_T_##type(const PERMUTATION_##type *p );\
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bool IS_PERMUTATION_##type(const PERMUTATION_##type *p );\
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size_t TabToPlaceAlgo_##type(const PERMUTATION_##type *p);\
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size_t TabToPlaceOpt1_##type(const PERMUTATION_##type *p);\
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size_t TabToPlaceNotab_##type(const PERMUTATION_##type *p);\
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PERMUTATION_TYPE_SIZE_T * PlaceToTab_##type(PERMUTATION_##type *p, size_t pl);\
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GENERATE_PERMUTATION(TYPE_SIZE_T)
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GENERATE_PERMUTATION(TYPE_CHAR)
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GENERATE_PERMUTATION(TYPE_U_CHAR)
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GENERATE_PERMUTATION(TYPE_INT)
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GENERATE_PERMUTATION(TYPE_U_INT)
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GENERATE_PERMUTATION(TYPE_L_INT)
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GENERATE_PERMUTATION(TYPE_U_L_INT)
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GENERATE_PERMUTATION(TYPE_FLOAT)
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GENERATE_PERMUTATION(TYPE_DOUBLE)
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GENERATE_PERMUTATION(TYPE_L_DOUBLE)
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GENERATE_PERMUTATION(TYPE_STRING)
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#define GENERATE_FUNCTIONS_UNSIGNED(type)\
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bool IS_PERMUTATION_SET_THEORIC_##type(const PERMUTATION_##type *p);\
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GENERATE_FUNCTIONS_UNSIGNED(TYPE_U_CHAR)
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GENERATE_FUNCTIONS_UNSIGNED(TYPE_U_INT)
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GENERATE_FUNCTIONS_UNSIGNED(TYPE_U_L_INT)
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GENERATE_FUNCTIONS_UNSIGNED(TYPE_SIZE_T)
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#endif /*__PERMUTATION_T_C_H__*/
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@@ -0,0 +1,24 @@
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#ifndef __SET_THEORIC_T_C__H
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#define __SET_THEORIC_T_C__H
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#include <stdlib.h>
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#include "tools_t/tools_t.h"
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#define GENERATE_UNSIGNED_SET_THEORIC(type) \
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struct SET_THEORIC_##type{ \
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type id; \
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type *set; \
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}; \
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typedef struct SET_THEORIC_##type SET_THEORIC_##type; \
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SET_THEORIC_##type * CREATE_SET_THEORIC_##type(size_t id/*TYPE_##type*/); \
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bool IS_SET_THEORIC_##type(SET_THEORIC_##type *st); \
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GENERATE_UNSIGNED_SET_THEORIC(TYPE_U_CHAR)
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GENERATE_UNSIGNED_SET_THEORIC(TYPE_U_INT)
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GENERATE_UNSIGNED_SET_THEORIC(TYPE_U_L_INT)
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GENERATE_UNSIGNED_SET_THEORIC(TYPE_SIZE_T)
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#endif /*__SET_THEORIC_T_C__H*/
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@@ -0,0 +1,28 @@
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#ifndef __CL_TENSOR_T__H__
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#define __CL_TENSOR_T__H__
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#include <stdio.h>
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#include <stdlib.h>
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#define CL_TARGET_OPENCL_VERSION 300
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#ifdef __APPLE__
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#include <OpenCL/opencl.h>
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#else
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#include <CL/cl.h>
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#endif
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#include "tensor_t/tensor_t.h"
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#define CL_GENERATE_TENSOR_TYPE(type) \
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void cl_tensorProd_##type(tensor_##type **MM, tensor_##type *M0, tensor_##type *M1); \
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void cl_tensorContractnProd_##type(tensor_##type **MM, tensor_##type *M0, tensor_##type *M1, size_t contractionNumber); \
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void cl2d_tensorProd_##type(tensor_##type **MM, tensor_##type *M0, tensor_##type *M1, size_t div0Wsz, size_t div1Wsz); \
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void cl2d_tensorContractnProd_##type(tensor_##type **MM, tensor_##type *M0, tensor_##type *M1, size_t contractionNumber, size_t div0Wsz, size_t div1Wsz); \
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CL_GENERATE_TENSOR_TYPE(TYPE_FLOAT);
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CL_GENERATE_TENSOR_TYPE(TYPE_DOUBLE);
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#endif /* __CL_TENSOR_T__H__ */
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@@ -0,0 +1,85 @@
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#ifndef __TENSOR_T__H__
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#define __TENSOR_T__H__
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#include <stdlib.h>
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#include <time.h>
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#include <pthread.h>
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#include "dimension_t/dimension_t.h"
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void subArray(size_t* dst, size_t* src, size_t debDst, size_t finDst, size_t debSrc);
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#define GENERATE_TENSOR_TYPE(type) \
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struct tensor_##type{\
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dimension *dim;\
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type *x;\
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};\
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typedef struct tensor_##type tensor_##type;\
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tensor_##type * CREATE_TENSOR_##type(dimension *dim); \
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tensor_##type* CREATE_TENSOR_FROM_CPY_DIM_##type(dimension *dim);\
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void _RECREATE_TENSOR_IF_NOT_THE_SAME_DIM_OR_NULL_##type(tensor_##type **M, dimension *dd);\
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tensor_##type* CLONE_TENSOR_##type(tensor_##type *tens);\
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void free_tensor_##type(tensor_##type * tens); \
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tensor_##type * sub_minus_tensor_head_##type(tensor_##type *rootens, size_t minuSubdim, size_t rankInDim); \
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tensor_##type * sub_minus_tensor_tail_##type(tensor_##type *rootens, size_t minuSubdim, size_t rankInDim); \
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tensor_##type * sub_tensor_head_##type(tensor_##type *rootens, size_t subdim, size_t rankInDim); \
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tensor_##type * sub_tensor_tail_##type(tensor_##type *rootens, size_t subdim, size_t rankInDim); \
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tensor_##type * sub_copy_minus_tensor_head_##type(tensor_##type *rootens, size_t minuSubdim, size_t rankInDim); \
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tensor_##type * sub_copy_minus_tensor_tail_##type(tensor_##type *rootens, size_t minuSubdim, size_t rankInDim); \
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tensor_##type * sub_copy_tensor_head_##type(tensor_##type *rootens, size_t sub_copydim, size_t rankInDim); \
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||||
tensor_##type * sub_copy_tensor_tail_##type(tensor_##type *rootens, size_t sub_copydim, size_t rankInDim); \
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||||
void print_tensor_msg_##type(tensor_##type *T, char *msg);\
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||||
void fprint_tensor_##type(char *file_name, tensor_##type *T);\
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||||
size_t sprint_tensor_##type(char **tensorContent,tensor_##type *T, bool withIndex);\
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||||
void split_tensor_##type(tensor_##type *Troot, tensor_##type **Tpart1, tensor_##type **Tpart2, size_t pivotSplit, size_t rangeInPivot);\
|
||||
void split_copy_tensor_##type(tensor_##type *Troot, tensor_##type **Tpart1, tensor_##type **Tpart2, size_t pivotSplit, size_t rangeInPivot);\
|
||||
void tensorProdNotOpt_##type(tensor_##type **MM, tensor_##type *M0, tensor_##type *M1); \
|
||||
void tensorProd_##type(tensor_##type **MM, tensor_##type *M0, tensor_##type *M1); \
|
||||
void tensorContractnProd_##type(tensor_##type **MM, tensor_##type *M0, tensor_##type *M1, size_t contractionNumber); \
|
||||
void tensorProdThread_##type(tensor_##type **MM, tensor_##type *M0, tensor_##type *M1,size_t nbthread); \
|
||||
void tensorProdThrea2d_##type(tensor_##type **MM, tensor_##type *M0, tensor_##type *M1,size_t nbthread); \
|
||||
void tensorContractnProdThread_##type(tensor_##type **MM, tensor_##type *M0, tensor_##type *M1, size_t contractionNumber, size_t nbthread); \
|
||||
void tensorContractnPro2dThread_##type(tensor_##type **MM, tensor_##type *M0, tensor_##type *M1, size_t contractionNumber, size_t nbthread); \
|
||||
void tensorContractnProdNotOpt_##type(tensor_##type **MM, tensor_##type *M0, tensor_##type *M1, size_t contractionNumber); \
|
||||
void init_random_x_##type(tensor_##type *M, type minR, type maxR, int randomRange);\
|
||||
tensor_##type * parseInput_withDim_to_tensor_##type(char *input);\
|
||||
void parseInputOutput_withDim_to_tensors_##type(tensor_##type **Tpart1, tensor_##type **Tpart2, char *input, size_t pivotSplit);\
|
||||
void parse_file_InputOutput_withDim_to_tensors_##type(tensor_##type **Tpart1, tensor_##type **Tpart2, char *file_name_input, size_t pivotSplit);\
|
||||
tensor_##type ** fromInput_to_array_tensor_##type(tensor_##type *tens);\
|
||||
struct array_chainlist_##type{\
|
||||
size_t index;\
|
||||
type x;\
|
||||
struct array_chainlist_##type *next;\
|
||||
};\
|
||||
typedef struct array_chainlist_##type array_chainlist_##type;\
|
||||
void append_array_chainlist_##type(array_chainlist_##type **list_a, type x);\
|
||||
tensor_##type * create_tensor_from_list_array_##type( array_chainlist_##type *l_a, dimension *part_dim);\
|
||||
void free_array_chainlist_##type(array_chainlist_##type *l_a);\
|
||||
tensor_##type * transpose_notOpt_tensor_##type(tensor_##type *org);\
|
||||
tensor_##type * permute_notOpt_tensor_##type(tensor_##type *org, dimension *dperm);\
|
||||
void update_1tensor_func_##type(tensor_##type *M0, \
|
||||
type (*func)(type), size_t nbthread);\
|
||||
void update_2tensor_func_##type(tensor_##type *M0, tensor_##type *M1, \
|
||||
type (*func)(type), size_t nbthread);\
|
||||
void update_3tensor_func_##type(tensor_##type *M0, tensor_##type *M1, tensor_##type *M2, \
|
||||
type (*func)(type, type), size_t nbthread);\
|
||||
void update_4tensor_func_##type(tensor_##type *M0, tensor_##type *M1, tensor_##type *M2, \
|
||||
type (*func)(type, type, type(*f1)(type)),\
|
||||
type(*f1)(type),\
|
||||
size_t nbthread);\
|
||||
void update_5tensor_func_##type(tensor_##type *M0, tensor_##type *M1, tensor_##type *M2, tensor_##type *M3 , \
|
||||
type (*func) (type, type, type, type(*f1)(type), type (*f2)(type,type)), \
|
||||
type(*f1)(type), \
|
||||
type (*f2)(type,type), \
|
||||
size_t nbthread);\
|
||||
void update_6tensor_func_##type(tensor_##type *M0, tensor_##type *M1, \
|
||||
type (*func)(type, type, type),\
|
||||
type scalar,\
|
||||
size_t nbthread);\
|
||||
|
||||
|
||||
GENERATE_TENSOR_TYPE(TYPE_FLOAT);
|
||||
GENERATE_TENSOR_TYPE(TYPE_DOUBLE);
|
||||
|
||||
|
||||
#endif /* __TENSOR_T__H__ */
|
||||
Binary file not shown.
@@ -0,0 +1,3 @@
|
||||
#!/bin/sh
|
||||
|
||||
gcc -o c_launch is_good.c -I../include_neurons/include/ -L.. -L../../ytest_t/ -lneurons -lytest -lpthread -lm
|
||||
@@ -0,0 +1,3 @@
|
||||
#!/bin/bash
|
||||
|
||||
LD_LIBRARY_PATH=..:../../ytest_t/ ./c_launch
|
||||
Reference in New Issue
Block a user