make format

Author: saaramahmoudi

vpr/src/place/RL_agent_util.cpp

@@ -117,20 +117,20 @@ void update_move_generator(std::unique_ptr<MoveGenerator>& move_generator, std::
     }
 }
 
-void determine_agent_block_types(){
+void determine_agent_block_types() {
     //Loop through all available logical block types and store the ones that exist in the netlist
     auto& device_ctx = g_vpr_ctx.device();
     auto& cluster_ctx = g_vpr_ctx.clustering();
     auto& place_ctx = g_vpr_ctx.mutable_placement();
     int agent_type_index = 0;
     for (auto itype : device_ctx.logical_block_types) {
         if (itype.index == 0) //ignore empty type
-        continue;
+            continue;
         auto blk_per_type = cluster_ctx.clb_nlist.blocks_per_type(itype);
         if (blk_per_type.size() != 0) {
-        place_ctx.phys_blk_type_to_agent_blk_type_map.insert(std::pair<int, int>(agent_type_index, itype.index));
-        place_ctx.agent_blk_type_to_phys_blk_type_map.insert(std::pair<int, int>(itype.index, agent_type_index));
-        agent_type_index++;
+            place_ctx.phys_blk_type_to_agent_blk_type_map.insert(std::pair<int, int>(agent_type_index, itype.index));
+            place_ctx.agent_blk_type_to_phys_blk_type_map.insert(std::pair<int, int>(itype.index, agent_type_index));
+            agent_type_index++;
         }
     }
 }

vpr/src/place/place.cpp

@@ -3224,7 +3224,7 @@ static void print_placement_move_types_stats(
     float moves, accepted, rejected, aborted;
 
     float total_moves = 0;
-    for(size_t iaction = 0; iaction < move_type_stat.blk_type_moves.size(); iaction++){
+    for (size_t iaction = 0; iaction < move_type_stat.blk_type_moves.size(); iaction++) {
         total_moves += move_type_stat.blk_type_moves[iaction];
     }
 

vpr/src/place/simpleRL_move_generator.cpp

@@ -82,12 +82,12 @@ void KArmedBanditAgent::process_outcome(double reward, e_reward_function reward_
     //write agent internal q-table and actions into a file for debugging purposes
     //agent_info_file_ variable is a NULL pointer by default
     //info file is not generated unless the agent_info_file_ set to a filename in "init_q_scores" function
-    if(agent_info_file_) {
+    if (agent_info_file_) {
         write_agent_info(last_action_, reward);
     }
 }
 
-void KArmedBanditAgent::write_agent_info(int last_action, double reward){
+void KArmedBanditAgent::write_agent_info(int last_action, double reward) {
     fseek(agent_info_file_, 0, SEEK_END);
     fprintf(agent_info_file_, "%d,", last_action);
     fprintf(agent_info_file_, "%g,", reward);
@@ -134,9 +134,9 @@ void EpsilonGreedyAgent::init_q_scores() {
 
     //agent_info_file_ = vtr::fopen("agent_info.txt", "w");
     //write agent internal q-table and actions into file for debugging purposes
-    if(agent_info_file_) {
+    if (agent_info_file_) {
         //we haven't performed any moves yet, hence last_aciton and reward are 0
-        write_agent_info(0,0);
+        write_agent_info(0, 0);
     }
 
     set_epsilon_action_prob();
@@ -255,9 +255,9 @@ void SoftmaxAgent::init_q_scores() {
 
     //    agent_info_file_ = vtr::fopen("agent_info.txt", "w");
     //write agent internal q-table and actions into file for debugging purposes
-    if(agent_info_file_) {
+    if (agent_info_file_) {
         //we haven't performed any moves yet, hence last_aciton and reward are 0
-        write_agent_info(0,0);
+        write_agent_info(0, 0);
     }
 
     /*
@@ -269,7 +269,6 @@ void SoftmaxAgent::init_q_scores() {
         set_block_ratio();
     }
     set_action_prob();
-
 }
 
 t_propose_action SoftmaxAgent::propose_action() {

vpr/src/place/simpleRL_move_generator.h

@@ -17,27 +17,27 @@ class KArmedBanditAgent {
     virtual ~KArmedBanditAgent() {}
 
     /**
-    * @brief Choose a move type to perform and a block type that move should be performed with based on Q-table
-    *
-    * @return A move type and a block type as a "t_propose_action" struct
-    * If the agent is set to only propose move type, then block type index in the struct will be set to -1
-    */
+     * @brief Choose a move type to perform and a block type that move should be performed with based on Q-table
+     *
+     * @return A move type and a block type as a "t_propose_action" struct
+     * If the agent is set to only propose move type, then block type index in the struct will be set to -1
+     */
     virtual t_propose_action propose_action() = 0;
 
     /**
-    * @brief Update the agent Q-table based on the reward received by the SA algorithm
-    *
-    *   @param reward A double value calculated in "place.cpp" file showing how placement cost was affected by the prior action taken
-    *   @param reward_func The reward function used by the agent, detail explanation can be found on "directed_moves_util.h" file
-    */
+     * @brief Update the agent Q-table based on the reward received by the SA algorithm
+     *
+     *   @param reward A double value calculated in "place.cpp" file showing how placement cost was affected by the prior action taken
+     *   @param reward_func The reward function used by the agent, detail explanation can be found on "directed_moves_util.h" file
+     */
     void process_outcome(double, e_reward_function);
 
     /**
-    * @brief write all agent internal information (Q-table, reward for each performed action, ...) to a file (agent_info_file_)
-    *
-    *   @param last_action Last action performed by the RL-agent
-    *   @param reward A double value calculated in "place.cpp" file showing how placement cost was affected by the prior action taken
-    */
+     * @brief write all agent internal information (Q-table, reward for each performed action, ...) to a file (agent_info_file_)
+     *
+     *   @param last_action Last action performed by the RL-agent
+     *   @param reward A double value calculated in "place.cpp" file showing how placement cost was affected by the prior action taken
+     */
     void write_agent_info(int last_action, double reward);
 
   protected:
@@ -72,32 +72,31 @@ class EpsilonGreedyAgent : public KArmedBanditAgent {
     t_propose_action propose_action() override; //Returns the type of the next action as well as the block type the agent wishes to perform
 
   public:
-
     /**
-    * @brief Set the user-specified epsilon for the E-greedy agent
-    *
-    *   @param epsilon Epsilon value for the agent, can be specified by the command-line option "--place_agent_epsilon"
-    *   Epsilon default value is 0.3.
-    */
+     * @brief Set the user-specified epsilon for the E-greedy agent
+     *
+     *   @param epsilon Epsilon value for the agent, can be specified by the command-line option "--place_agent_epsilon"
+     *   Epsilon default value is 0.3.
+     */
     void set_epsilon(float epsilon);
 
     /**
-    * @brief Set equal action probability to all available actions.
-    */
+     * @brief Set equal action probability to all available actions.
+     */
     void set_epsilon_action_prob();
 
     /**
-    * @brief Set step size for q-table updates
-    *
-    *   @param gamma Controls how quickly the agent's memory decays, can be specified by the command-line option "--place_agent_gamma"
-    *   Gamma default value is 0.05.
-    *   @param move_lim Number of moves per temperature
-    */
+     * @brief Set step size for q-table updates
+     *
+     *   @param gamma Controls how quickly the agent's memory decays, can be specified by the command-line option "--place_agent_gamma"
+     *   Gamma default value is 0.05.
+     *   @param move_lim Number of moves per temperature
+     */
     void set_step(float gamma, int move_lim);
 
     /**
-    * @brief Initialize agent's Q-table and internal variable to zero (RL-agent learns everything throughout the placement run and has no prior knowledge)
-    */
+     * @brief Initialize agent's Q-table and internal variable to zero (RL-agent learns everything throughout the placement run and has no prior knowledge)
+     */
     void init_q_scores();
 
   private:
@@ -122,32 +121,30 @@ class SoftmaxAgent : public KArmedBanditAgent {
     t_propose_action propose_action() override; //Returns the type of the next action as well as the block type the agent wishes to perform
 
   public:
-
     /**
-    * @brief Calculate the fraction of total netlist blocks for each agent block type and will be used by the "set_action_prob" function.
-    */
+     * @brief Calculate the fraction of total netlist blocks for each agent block type and will be used by the "set_action_prob" function.
+     */
     void set_block_ratio();
 
-
     /**
-    * @brief Set action probability for all available actions.
-    * If agent only proposes move type, the action probabilities would be equal for all move types at the beginning.
-    * If agent proposes both move and block type, the action_prob for each action would be based on its block type count in the netlist.
-    */
+     * @brief Set action probability for all available actions.
+     * If agent only proposes move type, the action probabilities would be equal for all move types at the beginning.
+     * If agent proposes both move and block type, the action_prob for each action would be based on its block type count in the netlist.
+     */
     void set_action_prob();
 
     /**
-    * @brief Set step size for q-table updates
-    *
-    *   @param gamma Controls how quickly the agent's memory decays, can be specified by the command-line option "--place_agent_gamma"
-    *   Gamma default value is 0.05.
-    *   @param move_lim Number of moves per temperature
-    */
+     * @brief Set step size for q-table updates
+     *
+     *   @param gamma Controls how quickly the agent's memory decays, can be specified by the command-line option "--place_agent_gamma"
+     *   Gamma default value is 0.05.
+     *   @param move_lim Number of moves per temperature
+     */
     void set_step(float gamma, int move_lim);
 
     /**
-    * @brief Initialize agent's Q-table and internal variable to zero (RL-agent learns everything throughout the placement run and has no prior knowledge)
-    */
+     * @brief Initialize agent's Q-table and internal variable to zero (RL-agent learns everything throughout the placement run and has no prior knowledge)
+     */
     void init_q_scores();
 
   private: