add functions calculate parallel updates neurons, and debug some leak functions

neuron_t/test/Makefile

@@ -14,7 +14,7 @@ NEURODIR=$(PWD)/..
 DIMDIR=$(PWD)/../../dimension_t
 INCLUDE_DIR=$(PWD)/../src
 CFLAGS=-I$(INCLUDE_DIR) -I$(YPERMDIR)/src -I$(YTESTDIR)/include_ytest/include -I$(DIMDIR)/src -I$(TENSDIR)/src #"-D DEBUG=1"
-LDFLAGS=-L$(YTESTDIR) -lytest -lOpenCL -lm
+LDFLAGS=-L$(YTESTDIR) -lytest -lOpenCL -lm -lpthread
 
 #SRC_DIR=$(ROOT_DIR)/src
 #SRC=$(wildcard */*/*.c) 

neuron_t/test/is_good.c

@@ -52,9 +52,9 @@ TEST(init_One){
     f,
     df);
 
-  setup_all_layers_params_TYPE_FLOAT(bn, 2, 0.7);
+  setup_all_layers_params_TYPE_FLOAT(bn, 2, 3, 0.7);
 
-  //print_neurons_msg_TYPE_FLOAT(bn,"bn");
+  print_neurons_msg_TYPE_FLOAT(bn,"bn init");
 
   tmp=bn->next_layer;
   while(tmp){
@@ -71,13 +71,70 @@ TEST(init_One){
   }
 
 
-  print_neurons_msg_TYPE_FLOAT(bn,"bn");
+  print_neurons_msg_TYPE_FLOAT(bn,"bn after ");
 
   LOG(" error : %f\n", error_out_TYPE_FLOAT(bn));
 
   free_neurons_TYPE_FLOAT(bn);
 }
 
+TEST(data_set_from_file){
+  data_set_TYPE_FLOAT *ds= fill_data_set_from_file_TYPE_FLOAT("data.txt",1);
+
+  print_data_set_msg_TYPE_FLOAT(ds,"data");
+
+  free_data_set_TYPE_FLOAT(ds);
+
+}
+
+#define epsilon 0.0001
+
+bool cond(float e, size_t nbreps){
+  //if (nbreps > 5) return true;
+  if ((e<epsilon) && (e>-epsilon)) return true;
+  return false;
+}
+
+TEST(learning_first){
+  
+  data_set_TYPE_FLOAT *ds= fill_data_set_from_file_TYPE_FLOAT("xor.txt",1);
+//  print_data_set_msg_TYPE_FLOAT(ds,"data");
+  neurons_TYPE_FLOAT *bn=NULL, *tmp ;
+  setup_networks_OneD_TYPE_FLOAT(&bn, (size_t[]){2,4,1},3); /* 2 input , 1 target; 1 hidden layer with 5 neurons */
+
+  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 ,  0.5);
+
+
+  size_t reps = learning_online_neurons_TYPE_FLOAT(bn,ds,cond);
+  
+ 
+  char msg[256];
+  for(size_t i=0; i<ds->size; ++i){
+    sprintf(msg, "data set [%ld]",i);
+    init_copy_in_out_networks_from_tensors_TYPE_FLOAT(bn, ds->input[i],ds->target[i]);\
+      tmp=bn->next_layer;\
+      while(tmp){\
+        calc_out_neurons_TYPE_FLOAT(tmp);\
+        tmp = tmp->next_layer;\
+      }
+    print_neurons_msg_TYPE_FLOAT(bn, msg);
+  
+  }
+  
+
+  free_data_set_TYPE_FLOAT(ds);
+  free_neurons_TYPE_FLOAT(bn); 
+
+  LOG("reps = %ld\n",reps);
+}
 
 
 int main(int argc, char **argv){