modify COMPARE_N in tool, modify attribute of vehicle by using tensor

neuron_t/src/neuron_t/neuron_t.c

@@ -747,6 +747,19 @@ size_t learning_online2_neurons_##type(neurons_##type *base, data_set_##type *da
   return nbreps;\
 }\
 \
+void calculate_output_by_network_neurons_##type(neurons_##type *base, tensor_##type *input, tensor_##type **output_link){\
+  for(size_t i=0; i<(input->dim)->rank; ++i) (base->output)->x[i]=input->x[i];\
+  neurons_##type * tmp=base->next_layer;\
+  while(tmp){\
+    calc_out_neurons_##type(tmp);\
+    if(tmp->next_layer==NULL){\
+      /*print_tensor_msg_##type(tmp->output,"retult");*/\
+      *output_link = tmp->output;\
+    }\
+    tmp = tmp->next_layer;\
+  }\
+\
+}\
 void print_predict_by_network_neurons_##type(neurons_##type *base, tensor_##type *input){\
     for(size_t i=0; i<(input->dim)->rank; ++i) (base->output)->x[i]=input->x[i];\
       neurons_##type * tmp=base->next_layer;\

neuron_t/src/neuron_t/neuron_t.h

@@ -106,7 +106,7 @@ 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 calculate_output_by_network_neurons_##type(neurons_##type *base, tensor_##type *input, tensor_##type **output_link);\
 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);\
 \

neuron_t/test/is_good.c

@@ -21,6 +21,7 @@
 
 #define VALGRIND_ 1
 
+
 float L(float t, float o){
   return (o - t) * (o - t)/2;
 }
@@ -356,13 +357,30 @@ TEST(copy_weight_in_neurons){
 
   size_t reps = learning_online2_neurons_TYPE_FLOAT(bn,ds,cond);
   
+  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);
+
+
   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]);
-    
+//    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);
   }