723 lines
22 KiB
C
723 lines
22 KiB
C
#include <stdio.h>
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#include <stdlib.h>
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#include <stdbool.h>
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#include <math.h>
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// for sleep !
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#ifdef __linux__
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#include <unistd.h>
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#elif _WIN32
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#include <windows.h>
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#endif
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#include "ftest/ftest.h"
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#include "ftest/ftest_array.h"
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#include "fmock/fmock.h"
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//#include "permutation_t/permutation_t.h"
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#include "neuron_t/neuron_t.h"
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#include "neuron_t/nneuron_t_file.h"
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#define VALGRIND_ 1
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float L(float t, float o){
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return (o - t) * (o - t)/2;
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}
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float DL(float t, float o){
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return (o - t);
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}
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float f(float x){
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return 1/(1+exp((double)(-x)));
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}
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float df(float x){
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return exp(-x)/ ((1+exp(-x)) * (1+exp(-x)));
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}
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float __id_(float x){
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return x;
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}
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float d__id_(float x){
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return 1;
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}
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TEST(init_One){
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//endian=false;
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neurons_TYPE_FLOAT *bn=NULL, *tmp=NULL, *ttmp=NULL;
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setup_networks_OneD_TYPE_FLOAT(&bn, (size_t[]){3,5,2},3,false,0,1,5000);
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init_in_out_all_networks_OneD_TYPE_FLOAT(bn,(float[]){1.2,0.5,1.3},3,(float[]){0.1,0.8},2);
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setup_all_layers_functions_TYPE_FLOAT(bn,
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tensorContractnProdThread_TYPE_FLOAT,
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tensorProdThread_TYPE_FLOAT,
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DL,
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L,
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f,
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df);
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setup_all_layers_params_TYPE_FLOAT(bn, 2, 3, 0.7);
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print_neurons_msg_TYPE_FLOAT(bn,"bn init");
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tmp=bn->next_layer;
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while(tmp){
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calc_out_neurons_TYPE_FLOAT(tmp);
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ttmp = tmp;
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tmp = tmp->next_layer;
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}
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while(ttmp != bn){
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calc_delta_neurons_TYPE_FLOAT(ttmp);
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update_weight_neurons_TYPE_FLOAT(ttmp);
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ttmp = ttmp->prev_layer;
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}
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print_neurons_msg_TYPE_FLOAT(bn,"bn after ");
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LOG(" error : %f\n", error_out_TYPE_FLOAT(bn));
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free_neurons_TYPE_FLOAT(bn);
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}
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#if 0
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TEST(data_set_from_file){
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data_set_TYPE_FLOAT *ds= fill_data_set_from_file_TYPE_FLOAT("data.txt",1);
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print_data_set_msg_TYPE_FLOAT(ds,"data");
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free_data_set_TYPE_FLOAT(ds);
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}
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#endif
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#define epsilon 0.0001
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bool cond(float e, size_t nbreps){
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if (nbreps > 2000) return true;
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if ((e<epsilon) && (e>-epsilon)) return true;
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return false;
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}
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TEST(learning_first){
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bool rec_randomizeInitWeight = randomizeInitWeight;
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randomizeInitWeight =false;
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data_set_TYPE_FLOAT *ds= fill_data_set_from_file_TYPE_FLOAT("xor.txt",1);
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print_data_set_msg_TYPE_FLOAT(ds,"data");
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neurons_TYPE_FLOAT *bn=NULL, *tmp ;
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setup_networks_OneD_TYPE_FLOAT(&bn, (size_t[]){2,4,1},3,false,0,1,5000); /* 2 input , 1 target; 1 hidden layer with 5 neurons */
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//setup_networks_OneD_TYPE_FLOAT(&bn, (size_t[]){2,4,1},3,true,0,1,5000); /* 2 input , 1 target; 1 hidden layer with 5 neurons */
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setup_all_layers_functions_TYPE_FLOAT(bn,
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tensorContractnProdThread_TYPE_FLOAT,
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tensorProdThread_TYPE_FLOAT,
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DL,
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L,
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f,
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df);
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setup_all_layers_params_TYPE_FLOAT(bn, 5/*5*/, 3/*1*/ , 0.5);
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neurons_TYPE_FLOAT *ttmp=bn;
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while(ttmp){
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if(ttmp->next_layer == NULL){
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ttmp->f_act=__id_;
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ttmp->d_f_act=d__id_;
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}
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ttmp=ttmp->next_layer;
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}
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LOG("%s","setup done\n");
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print_neurons_msg_TYPE_FLOAT(bn,"bn before ");
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size_t reps = learning_online_neurons_TYPE_FLOAT(bn,ds,cond);
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print_neurons_msg_TYPE_FLOAT(bn,"bn after ");
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//char msg[256];
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for(size_t i=0; i<ds->size; ++i){
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print_predict_by_network_with_error_neurons_TYPE_FLOAT(bn,ds->input[i],ds->target[i]);
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//print_predict_by_network_neurons_TYPE_FLOAT(bn,ds->input[i]);
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/*sprintf(msg, "data set [%ld]",i);
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init_copy_in_out_networks_from_tensors_TYPE_FLOAT(bn, ds->input[i],ds->target[i]);\
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tmp=bn->next_layer;\
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while(tmp){\
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calc_out_neurons_TYPE_FLOAT(tmp);\
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tmp = tmp->next_layer;\
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}
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print_neurons_msg_TYPE_FLOAT(bn, msg);
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*/
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}
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LOG("reps = %ld error=%f\n",reps, error_out_TYPE_FLOAT(bn));
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free_data_set_TYPE_FLOAT(ds);
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free_neurons_TYPE_FLOAT(bn);
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randomizeInitWeight = rec_randomizeInitWeight;
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}
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TEST(learning_second_PRINT){ endian=false;
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bool rec_randomizeInitWeight = randomizeInitWeight;
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randomizeInitWeight =false;
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data_set_TYPE_FLOAT *ds= fill_data_set_from_file_TYPE_FLOAT("xor.txt",1);
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// print_data_set_msg_TYPE_FLOAT(ds,"data");
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neurons_TYPE_FLOAT *bn=NULL, *tmp ;
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setup_networks_OneD_TYPE_FLOAT(&bn, (size_t[]){2,4,1},3,false,0,1,5000); /* 2 input , 1 target; 1 hidden layer with 5 neurons */
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setup_all_layers_functions_TYPE_FLOAT(bn,
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tensorContractnProdThread_TYPE_FLOAT,
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tensorProdThread_TYPE_FLOAT,
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DL,
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L,
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f,
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df);
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setup_all_layers_params_TYPE_FLOAT(bn, 5, 1 , 0.4);
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neurons_TYPE_FLOAT *ttmp=bn;
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while(ttmp){
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if(ttmp->next_layer == NULL){
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ttmp->f_act=__id_;
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ttmp->d_f_act=d__id_;
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}
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ttmp=ttmp->next_layer;
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}
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size_t reps = learning_online2_neurons_TYPE_FLOAT(bn,ds,cond);
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char msg[256];
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for(size_t i=0; i<ds->size; ++i){
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print_predict_by_network_with_error_neurons_TYPE_FLOAT(bn,ds->input[i],ds->target[i]);
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//print_predict_by_network_neurons_TYPE_FLOAT(bn,ds->input[i]);
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/*sprintf(msg, "data set [%ld]",i);
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init_copy_in_out_networks_from_tensors_TYPE_FLOAT(bn, ds->input[i],ds->target[i]);\
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tmp=bn->next_layer;\
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while(tmp){\
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calc_out_neurons_TYPE_FLOAT(tmp);\
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tmp = tmp->next_layer;\
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}
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print_neurons_msg_TYPE_FLOAT(bn, msg);
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*/
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}
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PRINT_ATTRIBUTE_TENS_IN_ALL_LAYERS(TYPE_FLOAT, bn, input, " bn input");
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PRINT_ATTRIBUTE_TENS_IN_ALL_LAYERS(TYPE_FLOAT, bn, output, " bn output");
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PRINT_ATTRIBUTE_TENS_IN_ALL_LAYERS(TYPE_FLOAT, bn, bias, " bn bias");
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free_data_set_TYPE_FLOAT(ds);
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free_neurons_TYPE_FLOAT(bn);
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LOG("reps = %ld\n",reps);
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randomizeInitWeight = rec_randomizeInitWeight;
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}
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TEST(learning_withconfig2){
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bool rec_randomizeInitWeight = randomizeInitWeight;
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randomizeInitWeight =false;
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data_set_TYPE_FLOAT *ds= fill_data_set_from_file_TYPE_FLOAT("xor.txt",1);
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// print_data_set_msg_TYPE_FLOAT(ds,"data");
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config_layers *pconf = create_config_layers_from_OneD(3,(size_t[]){2,4,1}); /* 2 input , 1 target; 1 hidden layer with 5 neurons */
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neurons_TYPE_FLOAT *bn=NULL, *tmp ;
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//setup_networks_alloutputs_config_GLOBAL_rdm01_TYPE_FLOAT(setup_networks_alloutputs_config_TYPE_FLOAT(&bn,pconf);bn,pconf);
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setup_networks_alloutputs_config_TYPE_FLOAT(&bn,pconf,false,0,1,5000);
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setup_all_layers_functions_TYPE_FLOAT(bn,
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tensorContractnProdThread_TYPE_FLOAT,
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tensorProdThread_TYPE_FLOAT,
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DL,
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L,
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f,
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df);
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setup_all_layers_params_TYPE_FLOAT(bn, 1, 1 , 0.5);
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neurons_TYPE_FLOAT *ttmp=bn;
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while(ttmp){
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if(ttmp->next_layer == NULL){
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ttmp->f_act=__id_;
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ttmp->d_f_act=d__id_;
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}
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ttmp=ttmp->next_layer;
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}
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size_t reps = learning_online2_neurons_TYPE_FLOAT(bn,ds,cond);
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char msg[256];
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for(size_t i=0; i<ds->size; ++i){
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print_predict_by_network_with_error_neurons_TYPE_FLOAT(bn,ds->input[i],ds->target[i]);
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}
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free_data_set_TYPE_FLOAT(ds);
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free_neurons_TYPE_FLOAT(bn);
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free_config_layers(pconf);
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LOG("reps = %ld\n",reps);
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randomizeInitWeight = rec_randomizeInitWeight;
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}
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TEST(learning_cloneuroneset){
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bool rec_randomizeInitWeight = randomizeInitWeight;
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randomizeInitWeight =false;
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data_set_TYPE_FLOAT *ds= fill_data_set_from_file_TYPE_FLOAT("xor.txt",1);
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// print_data_set_msg_TYPE_FLOAT(ds,"data");
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config_layers *pconf = create_config_layers_from_OneD(3,(size_t[]){2,4,1}); /* 2 input , 1 target; 1 hidden layer with 5 neurons */
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neurons_TYPE_FLOAT *bn=NULL, *tmp ;
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//setup_networks_alloutputs_config_GLOBAL_rdm01_TYPE_FLOAT(setup_networks_alloutputs_config_TYPE_FLOAT(&bn,pconf);bn,pconf);
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setup_networks_alloutputs_config_TYPE_FLOAT(&bn,pconf,false,0,1,5000);
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setup_all_layers_functions_TYPE_FLOAT(bn,
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tensorContractnProdThread_TYPE_FLOAT,
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tensorProdThread_TYPE_FLOAT,
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DL,
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L,
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f,
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df);
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setup_all_layers_params_TYPE_FLOAT(bn, 1, 1 , 0.5);
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neurons_TYPE_FLOAT *ttmp=bn;
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while(ttmp){
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if(ttmp->next_layer == NULL){
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ttmp->f_act=__id_;
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ttmp->d_f_act=d__id_;
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}
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ttmp=ttmp->next_layer;
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}
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//print_neurons_msg_TYPE_FLOAT(bn,"before create clones");
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cloneuronset_TYPE_FLOAT *clnrnst = create_cloneuronset_from_base_conf_TYPE_FLOAT(bn, pconf, 3);
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// size_t reps = learning_online2_neurons_TYPE_FLOAT(bn,ds,cond);
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size_t reps = learning_cloneuronset_TYPE_FLOAT(clnrnst, ds,cond);
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char msg[256];
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for(size_t i=0; i<ds->size; ++i){
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print_predict_by_network_with_error_neurons_TYPE_FLOAT(bn,ds->input[i],ds->target[i]);
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}
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free_cloneuronset_TYPE_FLOAT(clnrnst);
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free_data_set_TYPE_FLOAT(ds);
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free_neurons_TYPE_FLOAT(bn);
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LOG("reps = %ld\n",reps);
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randomizeInitWeight = rec_randomizeInitWeight;
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}
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TEST(learning_cloneuroneset_LEARN_RATE){
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bool rec_randomizeInitWeight = randomizeInitWeight;
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randomizeInitWeight =false;
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data_set_TYPE_FLOAT *ds= fill_data_set_from_file_TYPE_FLOAT("xor.txt",1);
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// print_data_set_msg_TYPE_FLOAT(ds,"data");
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config_layers *pconf = create_config_layers_from_OneD(3,(size_t[]){2,4,1}); /* 2 input , 1 target; 1 hidden layer with 5 neurons */
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neurons_TYPE_FLOAT *bn=NULL, *tmp ;
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//setup_networks_alloutputs_config_GLOBAL_rdm01_TYPE_FLOAT(setup_networks_alloutputs_config_TYPE_FLOAT(&bn,pconf);bn,pconf);
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setup_networks_alloutputs_config_TYPE_FLOAT(&bn,pconf,false,0,1,5000);
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setup_all_layers_functions_TYPE_FLOAT(bn,
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tensorContractnProdThread_TYPE_FLOAT,
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tensorProdThread_TYPE_FLOAT,
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DL,
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L,
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f,
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df);
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setup_all_layers_params_TYPE_FLOAT(bn, 5, 1 , 0.4);
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float initRate=0.6;
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float decayRate=0.85; /* halving*/
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size_t dropRate = 100;
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// setup_learning_rate_params_neurons_TYPE_FLOAT(bn, initRate, decayRate, dropRate, time_based_update_learning_rate_TYPE_FLOAT);
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setup_learning_rate_params_neurons_TYPE_FLOAT(bn, initRate, decayRate, dropRate, step_based_update_learning_rate_TYPE_FLOAT);
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neurons_TYPE_FLOAT *ttmp=bn;
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while(ttmp){
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if(ttmp->next_layer == NULL){
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ttmp->f_act=__id_;
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ttmp->d_f_act=d__id_;
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}
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ttmp=ttmp->next_layer;
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}
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//print_neurons_msg_TYPE_FLOAT(bn,"before create clones");
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cloneuronset_TYPE_FLOAT *clnrnst = create_cloneuronset_from_base_conf_TYPE_FLOAT(bn, pconf, 3);
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// size_t reps = learning_online2_neurons_TYPE_FLOAT(bn,ds,cond);
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size_t reps = learning_cloneuronset_TYPE_FLOAT(clnrnst, ds,cond);
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char msg[256];
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for(size_t i=0; i<ds->size; ++i){
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print_predict_by_network_with_error_neurons_TYPE_FLOAT(bn,ds->input[i],ds->target[i]);
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}
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free_cloneuronset_TYPE_FLOAT(clnrnst);
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free_data_set_TYPE_FLOAT(ds);
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free_neurons_TYPE_FLOAT(bn);
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LOG("reps = %ld\n",reps);
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randomizeInitWeight = rec_randomizeInitWeight;
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}
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TEST(copy_weight_in_neurons){
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bool rec_randomizeInitWeight = randomizeInitWeight;
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randomizeInitWeight =false;
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data_set_TYPE_FLOAT *ds= fill_data_set_from_file_TYPE_FLOAT("xor.txt",1);
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// print_data_set_msg_TYPE_FLOAT(ds,"data");
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config_layers *pconf = create_config_layers_from_OneD(3,(size_t[]){2,4,1}); /* 2 input , 1 target; 1 hidden layer with 5 neurons */
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neurons_TYPE_FLOAT *bn=NULL, *tmp ;
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neurons_TYPE_FLOAT *cpyn=NULL;
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//setup_networks_alloutputs_config_GLOBAL_rdm01_TYPE_FLOAT(setup_networks_alloutputs_config_TYPE_FLOAT(&bn,pconf);bn,pconf);
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setup_networks_alloutputs_config_TYPE_FLOAT(&bn,pconf,false,0,1,5000);
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setup_networks_alloutputs_config_TYPE_FLOAT(&cpyn, pconf,false,0,1,5000);
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setup_all_layers_functions_TYPE_FLOAT(bn,
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tensorContractnProdThread_TYPE_FLOAT,
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tensorProdThread_TYPE_FLOAT,
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DL,
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L,
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f,
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df);
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setup_all_layers_params_TYPE_FLOAT(bn, 5, 1 , 0.1);
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neurons_TYPE_FLOAT *ttmp=bn;
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while(ttmp){
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if(ttmp->next_layer == NULL){
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ttmp->f_act=__id_;
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ttmp->d_f_act=d__id_;
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}
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ttmp=ttmp->next_layer;
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}
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size_t reps = learning_online2_neurons_TYPE_FLOAT(bn,ds,cond);
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setup_all_layers_functions_TYPE_FLOAT(cpyn,
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tensorContractnProdThread_TYPE_FLOAT,
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tensorProdThread_TYPE_FLOAT,
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DL,
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L,
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f,
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df);
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setup_all_layers_params_TYPE_FLOAT(cpyn, 5, 1 , 0.1);
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copy_weight_in_neurons_TYPE_FLOAT(cpyn, bn);
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char msg[256];
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tensor_TYPE_FLOAT * linked_tens = NULL;
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for(size_t i=0; i<ds->size; ++i){
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// print_predict_by_network_with_error_neurons_TYPE_FLOAT(bn,ds->input[i],ds->target[i]);
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// print_predict_by_network_with_error_neurons_TYPE_FLOAT(cpyn,ds->input[i],ds->target[i]);
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calculate_output_by_network_neurons_TYPE_FLOAT(bn,ds->input[i],&linked_tens);
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sprintf(msg," output base %ld ",i);
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print_tensor_msg_TYPE_FLOAT(linked_tens,msg);
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calculate_output_by_network_neurons_TYPE_FLOAT(cpyn,ds->input[i],&linked_tens);
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sprintf(msg," output copy %ld ",i);
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print_tensor_msg_TYPE_FLOAT(linked_tens,msg);
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}
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EXPORT_TO_FILE_TENSOR_ATTRIBUTE_IN_NNEURONS(TYPE_FLOAT, bn, weight_in, ".ff_bn_weight_in.txt")
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free_data_set_TYPE_FLOAT(ds);
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free_neurons_TYPE_FLOAT(bn);
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free_neurons_TYPE_FLOAT(cpyn);
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LOG("reps = %ld\n",reps);
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randomizeInitWeight = rec_randomizeInitWeight;
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free_config_layers(pconf);
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}
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TEST(Extract_weight_in_neurons){
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bool rec_randomizeInitWeight = randomizeInitWeight;
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randomizeInitWeight =false;
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data_set_TYPE_FLOAT *ds= fill_data_set_from_file_TYPE_FLOAT("xor.txt",1);
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// print_data_set_msg_TYPE_FLOAT(ds,"data");
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config_layers *pconf = create_config_layers_from_OneD(3,(size_t[]){2,4,1}); /* 2 input , 1 target; 1 hidden layer with 5 neurons */
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neurons_TYPE_FLOAT *bn=NULL, *tmp ;
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neurons_TYPE_FLOAT *cpyn=NULL;
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//setup_networks_alloutputs_config_GLOBAL_rdm01_TYPE_FLOAT(setup_networks_alloutputs_config_TYPE_FLOAT(&bn,pconf);bn,pconf);
|
|
setup_networks_alloutputs_config_TYPE_FLOAT(&bn,pconf,false,0,1,5000);
|
|
setup_networks_alloutputs_config_TYPE_FLOAT(&cpyn, pconf,false,0,1,5000);
|
|
|
|
setup_all_layers_functions_TYPE_FLOAT(bn,
|
|
tensorContractnProdThread_TYPE_FLOAT,
|
|
tensorProdThread_TYPE_FLOAT,
|
|
DL,
|
|
L,
|
|
f,
|
|
df);
|
|
|
|
setup_all_layers_params_TYPE_FLOAT(bn, 5, 1 , 0.1);
|
|
|
|
|
|
size_t reps = 1;// learning_online2_neurons_TYPE_FLOAT(bn,ds,cond);
|
|
//EXPORT_TO_FILE_TENSOR_ATTRIBUTE_IN_NNEURONS(TYPE_FLOAT, bn, weight_in, ".ff_bn_weight_in__toExtract.txt")
|
|
|
|
setup_all_layers_functions_TYPE_FLOAT(cpyn,
|
|
tensorContractnProdThread_TYPE_FLOAT,
|
|
tensorProdThread_TYPE_FLOAT,
|
|
DL,
|
|
L,
|
|
f,
|
|
df);
|
|
|
|
setup_all_layers_params_TYPE_FLOAT(cpyn, 5, 1 , 0.1);
|
|
neurons_TYPE_FLOAT *ttmp=bn;
|
|
while(ttmp){
|
|
if(ttmp->next_layer == NULL){
|
|
ttmp->f_act=__id_;
|
|
ttmp->d_f_act=d__id_;
|
|
}
|
|
ttmp=ttmp->next_layer;
|
|
}
|
|
EXTRACT_FILE_TO_TENSOR_ATTRIBUTE_NNEURONS(TYPE_FLOAT, cpyn, weight_in, ".ff_bn_weight_in__toExtract.txt")
|
|
// copy_weight_in_neurons_TYPE_FLOAT(cpyn, bn);
|
|
EXPORT_TO_FILE_TENSOR_ATTRIBUTE_IN_NNEURONS(TYPE_FLOAT, bn, weight_in, ".ff_bn_weight_in__toExtract___exp.txt")
|
|
|
|
char msg[256];
|
|
tensor_TYPE_FLOAT * linked_tens = NULL;
|
|
for(size_t i=0; i<ds->size; ++i){
|
|
// print_predict_by_network_with_error_neurons_TYPE_FLOAT(bn,ds->input[i],ds->target[i]);
|
|
// print_predict_by_network_with_error_neurons_TYPE_FLOAT(cpyn,ds->input[i],ds->target[i]);
|
|
calculate_output_by_network_neurons_TYPE_FLOAT(bn,ds->input[i],&linked_tens);
|
|
sprintf(msg," output base %ld ",i);
|
|
print_tensor_msg_TYPE_FLOAT(linked_tens,msg);
|
|
calculate_output_by_network_neurons_TYPE_FLOAT(cpyn,ds->input[i],&linked_tens);
|
|
sprintf(msg," output copy %ld ",i);
|
|
print_tensor_msg_TYPE_FLOAT(linked_tens,msg);
|
|
}
|
|
|
|
|
|
EXPORT_TO_FILE_TENSOR_ATTRIBUTE_IN_NNEURONS(TYPE_FLOAT, cpyn, weight_in, ".ff_bn_weight_in__exportedCPYfromExtract.txt")
|
|
|
|
|
|
free_data_set_TYPE_FLOAT(ds);
|
|
free_neurons_TYPE_FLOAT(bn);
|
|
free_neurons_TYPE_FLOAT(cpyn);
|
|
|
|
LOG("reps = %ld\n",reps);
|
|
randomizeInitWeight = rec_randomizeInitWeight;
|
|
|
|
free_config_layers(pconf);
|
|
}
|
|
|
|
|
|
TEST(Extract_EXPORT_weight_in_neurons){
|
|
bool rec_randomizeInitWeight = randomizeInitWeight;
|
|
randomizeInitWeight =false;
|
|
|
|
data_set_TYPE_FLOAT *ds= fill_data_set_from_file_TYPE_FLOAT("xor.txt",1);
|
|
// print_data_set_msg_TYPE_FLOAT(ds,"data");
|
|
//config_layers *pconf = create_config_layers_from_OneD(3,(size_t[]){2,4,1}); /* 2 input , 1 target; 1 hidden layer with 5 neurons */
|
|
config_layers *pconf = create_config_layers_from_OneD(4,(size_t[]){3,24,24,3});
|
|
neurons_TYPE_FLOAT *bn=NULL, *tmp ;
|
|
neurons_TYPE_FLOAT *cpyn=NULL;
|
|
//setup_networks_alloutputs_config_GLOBAL_rdm01_TYPE_FLOAT(setup_networks_alloutputs_config_TYPE_FLOAT(&bn,pconf);bn,pconf);
|
|
setup_networks_alloutputs_config_TYPE_FLOAT(&bn,pconf,false,0,1,5000);
|
|
setup_networks_alloutputs_config_TYPE_FLOAT(&cpyn, pconf,false,0,1,5000);
|
|
|
|
//print_weight_in_neurons_TYPE_FLOAT(bn, "");
|
|
EXTRACT_FILE_TO_TENSOR_ATTRIBUTE_NNEURONS(TYPE_FLOAT, bn, weight_in, ".ff_target_20240717_01h43m41s_13300.txt")
|
|
|
|
setup_all_layers_functions_TYPE_FLOAT(bn,
|
|
tensorContractnProdThread_TYPE_FLOAT,
|
|
tensorProdThread_TYPE_FLOAT,
|
|
DL,
|
|
L,
|
|
f,
|
|
df);
|
|
|
|
setup_all_layers_params_TYPE_FLOAT(bn, 5, 1 , 0.1);
|
|
neurons_TYPE_FLOAT *ttmp=bn;
|
|
while(ttmp){
|
|
if(ttmp->next_layer == NULL){
|
|
ttmp->f_act=__id_;
|
|
ttmp->d_f_act=d__id_;
|
|
}
|
|
ttmp=ttmp->next_layer;
|
|
}
|
|
|
|
size_t reps = 1;// learning_online2_neurons_TYPE_FLOAT(bn,ds,cond);
|
|
EXPORT_TO_FILE_TENSOR_ATTRIBUTE_IN_NNEURONS(TYPE_FLOAT, bn, weight_in, ".ff_bn_weight_in__toCMP__.txt")
|
|
print_weight_in_neurons_TYPE_FLOAT(bn, "");
|
|
|
|
setup_all_layers_functions_TYPE_FLOAT(cpyn,
|
|
tensorContractnProdThread_TYPE_FLOAT,
|
|
tensorProdThread_TYPE_FLOAT,
|
|
DL,
|
|
L,
|
|
f,
|
|
df);
|
|
|
|
setup_all_layers_params_TYPE_FLOAT(cpyn, 5, 1 , 0.1);
|
|
|
|
// EXTRACT_FILE_TO_TENSOR_ATTRIBUTE_NNEURONS(TYPE_FLOAT, cpyn, weight_in, ".ff_bn_weight_in__toExtract.txt")
|
|
// copy_weight_in_neurons_TYPE_FLOAT(cpyn, bn);
|
|
|
|
char msg[256];
|
|
tensor_TYPE_FLOAT * linked_tens = NULL;
|
|
for(size_t i=0; i<ds->size; ++i){
|
|
// print_predict_by_network_with_error_neurons_TYPE_FLOAT(bn,ds->input[i],ds->target[i]);
|
|
// print_predict_by_network_with_error_neurons_TYPE_FLOAT(cpyn,ds->input[i],ds->target[i]);
|
|
calculate_output_by_network_neurons_TYPE_FLOAT(bn,ds->input[i],&linked_tens);
|
|
sprintf(msg," output base %ld ",i);
|
|
print_tensor_msg_TYPE_FLOAT(linked_tens,msg);
|
|
calculate_output_by_network_neurons_TYPE_FLOAT(cpyn,ds->input[i],&linked_tens);
|
|
sprintf(msg," output copy %ld ",i);
|
|
print_tensor_msg_TYPE_FLOAT(linked_tens,msg);
|
|
}
|
|
|
|
|
|
// EXPORT_TO_FILE_TENSOR_ATTRIBUTE_IN_NNEURONS(TYPE_FLOAT, cpyn, weight_in, ".ff_bn_weight_in__exportedCPYfromExtract.txt")
|
|
|
|
|
|
free_data_set_TYPE_FLOAT(ds);
|
|
free_neurons_TYPE_FLOAT(bn);
|
|
free_neurons_TYPE_FLOAT(cpyn);
|
|
|
|
LOG("reps = %ld\n",reps);
|
|
randomizeInitWeight = rec_randomizeInitWeight;
|
|
|
|
free_config_layers(pconf);
|
|
}
|
|
|
|
|
|
|
|
|
|
double doubleL(double t, double o){
|
|
return (o - t) * (o - t)/2;
|
|
}
|
|
double doubleDL(double t, double o){
|
|
return (o - t);
|
|
}
|
|
|
|
double doublef(double x){
|
|
return 1/(1+exp((double)(-x)));
|
|
}
|
|
|
|
double doubledf(double x){
|
|
return exp(-x)/ ((1+exp(-x)) * (1+exp(-x)));
|
|
}
|
|
|
|
|
|
TEST(Extract_EXPORT_weight_in_neurons_double){
|
|
bool rec_randomizeInitWeight = randomizeInitWeight;
|
|
randomizeInitWeight =false;
|
|
|
|
data_set_TYPE_DOUBLE *ds= fill_data_set_from_file_TYPE_DOUBLE("xor.txt",1);
|
|
// print_data_set_msg_TYPE_DOUBLE(ds,"data");
|
|
//config_layers *pconf = create_config_layers_from_OneD(3,(size_t[]){2,4,1}); /* 2 input , 1 target; 1 hidden layer with 5 neurons */
|
|
config_layers *pconf = create_config_layers_from_OneD(4,(size_t[]){3,24,24,3});
|
|
neurons_TYPE_DOUBLE *bn=NULL, *tmp ;
|
|
neurons_TYPE_DOUBLE *cpyn=NULL;
|
|
//setup_networks_alloutputs_config_GLOBAL_rdm01_TYPE_DOUBLE(setup_networks_alloutputs_config_TYPE_DOUBLE(&bn,pconf);bn,pconf);
|
|
setup_networks_alloutputs_config_TYPE_DOUBLE(&bn,pconf,false,0,1,5000);
|
|
setup_networks_alloutputs_config_TYPE_DOUBLE(&cpyn, pconf,false,0,1,5000);
|
|
|
|
EXTRACT_FILE_TO_TENSOR_ATTRIBUTE_NNEURONS(TYPE_DOUBLE, bn, weight_in, ".ff_target_20240717_01h43m41s_13300.txt")
|
|
|
|
setup_all_layers_functions_TYPE_DOUBLE(bn,
|
|
tensorContractnProdThread_TYPE_DOUBLE,
|
|
tensorProdThread_TYPE_DOUBLE,
|
|
doubleDL,
|
|
doubleL,
|
|
doublef,
|
|
doubledf);
|
|
|
|
setup_all_layers_params_TYPE_DOUBLE(bn, 5, 1 , 0.1);
|
|
|
|
|
|
size_t reps = 1;// learning_online2_neurons_TYPE_DOUBLE(bn,ds,cond);
|
|
// EXPORT_TO_FILE_TENSOR_ATTRIBUTE_IN_NNEURONS(TYPE_DOUBLE, bn, weight_in, ".ff_bn_weight_in__toCMP__.txt")
|
|
print_weight_in_neurons_TYPE_DOUBLE(bn, "");
|
|
|
|
|
|
setup_all_layers_functions_TYPE_DOUBLE(cpyn,
|
|
tensorContractnProdThread_TYPE_DOUBLE,
|
|
tensorProdThread_TYPE_DOUBLE,
|
|
doubleDL,
|
|
doubleL,
|
|
doublef,
|
|
doubledf);
|
|
|
|
setup_all_layers_params_TYPE_DOUBLE(cpyn, 5, 1 , 0.1);
|
|
neurons_TYPE_DOUBLE *ttmp=bn;
|
|
while(ttmp){
|
|
if(ttmp->next_layer == NULL){
|
|
ttmp->f_act=id_TYPE_DOUBLE;
|
|
ttmp->d_f_act=d_id_TYPE_DOUBLE;
|
|
}
|
|
ttmp=ttmp->next_layer;
|
|
}
|
|
// EXTRACT_FILE_TO_TENSOR_ATTRIBUTE_NNEURONS(TYPE_DOUBLE, cpyn, weight_in, ".ff_bn_weight_in__toExtract.txt")
|
|
// copy_weight_in_neurons_TYPE_DOUBLE(cpyn, bn);
|
|
|
|
char msg[256];
|
|
tensor_TYPE_DOUBLE * linked_tens = NULL;
|
|
for(size_t i=0; i<ds->size; ++i){
|
|
// print_predict_by_network_with_error_neurons_TYPE_DOUBLE(bn,ds->input[i],ds->target[i]);
|
|
// print_predict_by_network_with_error_neurons_TYPE_DOUBLE(cpyn,ds->input[i],ds->target[i]);
|
|
calculate_output_by_network_neurons_TYPE_DOUBLE(bn,ds->input[i],&linked_tens);
|
|
sprintf(msg," output base %ld ",i);
|
|
print_tensor_msg_TYPE_DOUBLE(linked_tens,msg);
|
|
calculate_output_by_network_neurons_TYPE_DOUBLE(cpyn,ds->input[i],&linked_tens);
|
|
sprintf(msg," output copy %ld ",i);
|
|
print_tensor_msg_TYPE_DOUBLE(linked_tens,msg);
|
|
}
|
|
|
|
|
|
// EXPORT_TO_FILE_TENSOR_ATTRIBUTE_IN_NNEURONS(TYPE_DOUBLE, cpyn, weight_in, ".ff_bn_weight_in__exportedCPYfromExtract.txt")
|
|
|
|
|
|
free_data_set_TYPE_DOUBLE(ds);
|
|
free_neurons_TYPE_DOUBLE(bn);
|
|
free_neurons_TYPE_DOUBLE(cpyn);
|
|
|
|
LOG("reps = %ld\n",reps);
|
|
randomizeInitWeight = rec_randomizeInitWeight;
|
|
free_config_layers(pconf);
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
|
|
int main(int argc, char **argv){
|
|
|
|
|
|
run_all_tests_args(argc, argv);
|
|
|
|
return 0;
|
|
}
|