deepQlearning: add libdeepqlearn.so, debug some issue with -Werror -fpic

deepQlearn_0/src/deepQlearning/learn_to_drive.c

@@ -45,7 +45,7 @@ struct networks_qlearning * create_nework_qlearning(
   struct networks_qlearning *qnets = malloc(sizeof(struct networks_qlearning));
   qnets->config = config;
 
-  setup_networks_alloutputs_config_TYPE_FLOAT(&(qnets->main_net), config, random, minR, maxR, randomRange);  
+  setup_networks_alloutputs_config_TYPE_FLOAT(&(qnets->main_net), config, randomize, minR, maxR, randomRange);  
   setup_networks_alloutputs_config_TYPE_FLOAT(&(qnets->target_net), config, false, minR, maxR, randomRange);  
   copy_weight_in_networks_from_main_to_target(qnets);
   
@@ -283,7 +283,7 @@ int select_action(struct RL_agent * rlAgent){
     //init =false;
   //}
   //int random = xrand() % randRange;
-  float proba_explor =  (float) (xrand() % (1<<17 -1))/ (1<<17 -1); //frand(); //(float)(random ) / randRange;
+  float proba_explor =  (float) (xrand() % ((1<<17) -1))/ ((1<<17) -1); //frand(); //(float)(random ) / randRange;
   if(proba_explor > rlAgent->qlearnParams->exploration_factor ){
     action = ARG_MAX_ARRAY_TYPE_FLOAT( action_value->x, action_value->dim->rank  );
     //if(action == ARG_MIN_ARRAY_TYPE_FLOAT( action_value->x, action_value->dim->rank  )) 
@@ -385,7 +385,7 @@ void learn_to_drive(struct RL_agent * rlAgent){
   struct game_status * car_status = car->status;
   struct qlearning_params * qlParams = rlAgent->qlearnParams;
   struct status_qlearning * qlStatus = rlAgent->status;
-  struct print_params * pprint = rlAgent->pprint;
+  //struct print_params * pprint = rlAgent->pprint;
   char msg[100];
   
   pthread_t threadPrint;

deepQlearn_0/src/deepQlearning/vehicle.c

@@ -20,6 +20,7 @@ struct game_status * create_game_status(){
   status->reward = 0;
   status->cumulative_reward = 0;
   status->done = false;
+  return status;
 }
 
 coordinate * create_coordinate(size_t dim_size){
@@ -423,13 +424,12 @@ float distance2_coordinate(coordinate *c0, coordinate *c1){
   v->sensor->x[position] = (float)(MIN((SUBDIVISION-1),dist))/SUBDIVISION ;\
   
   
-  
-  //v->sensor->x[position] = (float)(MIN((SUBDIVISION-1),(int)dist))/SUBDIVISION ;\
-  
-  
-  //v->sensor->x[position] = (MIN(49,(distance2_coordinate(diStep_sensor, v->coord)/5))) ;\
-  //v->sensor->x[position] = (MIN(49,(distance2_coordinate(diStep_sensor, v->coord)))) / 50;\
-  //v->sensor->x[position] = (MIN(49,(int)(distance2_coordinate(diStep_sensor, v->coord)/10))) / 50;\
+ #if 0 
+  //v->sensor->x[position] = (float)(MIN((SUBDIVISION-1),(int)dist))/SUBDIVISION ; 
+  //v->sensor->x[position] = (MIN(49,(distance2_coordinate(diStep_sensor, v->coord)/5))) ;
+  //v->sensor->x[position] = (MIN(49,(distance2_coordinate(diStep_sensor, v->coord)))) / 50;
+  //v->sensor->x[position] = (MIN(49,(int)(distance2_coordinate(diStep_sensor, v->coord)/10))) / 50;
+#endif
 
 void read_sensor(struct vehicle *v){
   copy_tensor_TYPE_FLOAT(v->old_sensor, v->sensor);

dimension_t/src/dimension_t/dimension_t.c

@@ -378,22 +378,22 @@ void signedvCoordFromLin(long int *ret, long int line, dimension *dim ){
 long int* signedCoordFromLin(long int line, dimension *dim){
     long int *ret;
     ret=malloc(dim->size*sizeof(long int));
-    vCoordFromLin(ret,line,dim);
+    signedvCoordFromLin(ret,line,dim);
     return ret;
 }
 
 /* */
 /* unsigned */
 size_t LineFromCoord(size_t *coo, dimension *dim) {
-  return signedLineFromCoord(coo,dim);
+  return (long)signedLineFromCoord((long*)coo,dim);
 }
 
 void vCoordFromLin(size_t *ret, size_t line, dimension *dim ){
-  signedvCoordFromLin(ret, line, dim);
+  signedvCoordFromLin((long*)ret, (long)line, dim);
 }
 
 size_t* CoordFromLin(size_t line, dimension *dim){
-  return signedCoordFromLin(line, dim);
+  return (size_t*)signedCoordFromLin((long)line, dim);
 }
 
 

dimension_t/src/dimension_t/dimension_t.h

@@ -51,9 +51,9 @@ size_t LineFromCoord(size_t *coo, dimension *dim);
 size_t* CoordFromLin(size_t line, dimension *dim);
 void vCoordFromLin(size_t *ret, size_t line, dimension *dim );
 
-long int signedLineFromCoord(long int *coo, dimension *dim);
-long int* signedCoordFromLin(long int line, dimension *dim);
-void signedvCoordFromLin(long int *ret, long int line, dimension *dim );
+long int signedLineFromCoord(long *coo, dimension *dim);
+long int* signedCoordFromLin(long line, dimension *dim);
+void signedvCoordFromLin(long *ret, long int line, dimension *dim );
 
 
 void increment_dim_var(dimension *d);

neuron_t/src/neuron_t/neuron_t.c

@@ -768,11 +768,11 @@ neurons_##type * calculate_output_by_network_neurons_##type(neurons_##type *base
     if(tmp->next_layer==NULL){\
       /*print_tensor_msg_##type(tmp->output,"retult");*/\
       *output_link = tmp->output;\
-      \
       return tmp;\
     }\
     tmp = tmp->next_layer;\
   }\
+  return NULL;\
 \
 }\
 void print_predict_by_network_neurons_##type(neurons_##type *base, tensor_##type *input){\

neuron_t/src/neuron_t/nneuron_t_file.h

@@ -7,7 +7,7 @@
 #include "neuron_t/neuron_t.h"
 #include "tensor_t/tensor_t.h"
 
-//#define GEN_TYPE_FILE_NN(type)\
+//#define GEN_TYPE_FILE_NN(type)
 //void export_to_file_weight_in_nneurons_##type(char *fileName, neurons_##type *src);
 
 #define EXPORT_TO_FILE_TENSOR_ATTRIBUTE_IN_NNEURONS(type,nneurons ,attribute, file_name) \