Add some MACRO in neuron_t and debug deepQlearning

neuron_t/src/neuron_t/neuron_t.c

@@ -627,6 +627,19 @@ void print_neurons_msg_##type(neurons_##type *nr, char *msg){\
   }\
 }\
 \
+void print_weight_in_neurons_##type(neurons_##type *nn, char *msg){\
+  neurons_##type *tmp = nn;\
+  size_t i = 0;\
+  char vmsg[250];\
+  while(tmp){\
+    if(tmp->weight_in){\
+      sprintf(vmsg,"%s layer %ld",msg,i++);\
+      print_tensor_msg_##type(tmp->weight_in, vmsg);\
+    }\
+    tmp = tmp->next_layer;\
+  }\
+}\
+\
 void free_neurons_##type(neurons_##type *base){\
   neurons_##type *temp = base, *ttemp;\
   while(temp){\
@@ -747,7 +760,7 @@ 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){\
+neurons_##type * 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){\
@@ -755,6 +768,7 @@ void calculate_output_by_network_neurons_##type(neurons_##type *base, tensor_##t
     if(tmp->next_layer==NULL){\
       /*print_tensor_msg_##type(tmp->output,"retult");*/\
       *output_link = tmp->output;\
+      return tmp;\
     }\
     tmp = tmp->next_layer;\
   }\

neuron_t/src/neuron_t/neuron_t.h

@@ -77,7 +77,9 @@ void setup_networks_layers_without_weights_##type(neurons_##type **base_nr, size
 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 print_weight_in_neurons_##type(neurons_##type *nn, char *msg);\
 \
 void free_neurons_##type(neurons_##type *base);\
 \
@@ -106,7 +108,7 @@ 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);\
+neurons_##type * 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);\
 \
@@ -134,4 +136,33 @@ GEN_NEURON_(TYPE_DOUBLE)
     }\
   }while(0);\
 
+#define COPY_NN_ATTRIBUTE_IN_ALL_LAYERS(type,  attribute, dstNN ,sourceNN)\
+  do{\
+    neurons_##type *tmpn = dstNN;\
+    neurons_##type *srcNN = sourceNN;\
+    while(tmpn){\
+      if(tmpn->attribute)\
+        copy_tensor_##type(tmpn->attribute, srcNN->attribute);\
+      tmpn = tmpn->next_layer;\
+      srcNN = srcNN->next_layer;\
+    }\
+  }while(0);\
+
+
+
+#define PRINT_ATTRIBUTE_TENS_IN_ALL_LAYERS(type, neuronVar, attribute, msg)\
+  do{\
+    neurons_##type *tmpn = neuronVar;\
+    char *vmsg=malloc(strlen(msg)+70);\
+    size_t i=0;\
+    while(tmpn){\
+      sprintf(vmsg,"%s layer %ld",msg,i++);\
+      if(tmpn->attribute)\
+        print_tensor_msg_##type(tmpn->attribute, vmsg);\
+      tmpn = tmpn->next_layer;\
+    }\
+    free(vmsg);\
+  }while(0);\
+
+
 #endif /*__NEURON_T_C__H*/