diff --git a/mushr_rhc_ros/launch/sim/sim_server_eval.launch b/mushr_rhc_ros/launch/sim/sim_server_eval.launch
index 71d7f8a..ca45e59 100644
--- a/mushr_rhc_ros/launch/sim/sim_server_eval.launch
+++ b/mushr_rhc_ros/launch/sim/sim_server_eval.launch
@@ -10,9 +10,13 @@
     <arg name="n_layers" default="12" />
 
     <!-- action model -->
-    <arg name="model_path_act" default="/home/rb/hackathon_data_premium/aml_outputs/log_output/hvd_test_16/GPTcorl_scratch_trainm_e2e_statet_pointnet_traini_1_nla_12_nhe_8_statel_0.01_2022-06-02_1654131996.2524076_2022-06-02_1654131996.2524228/model/epoch30.pth.tar" />
+    <arg name="model_path_act" type="str" default="" />
+    <!-- <arg name="model_path_act" default="/home/rb/hackathon_data_premium/aml_outputs/log_output/hvd_test_16/GPTcorl_scratch_trainm_e2e_statet_pointnet_traini_1_nla_12_nhe_8_statel_0.01_2022-06-02_1654131996.2524076_2022-06-02_1654131996.2524228/model/epoch30.pth.tar" /> -->
     <!-- <arg name="model_path_act" default="/home/rb/hackathon_data_premium/aml_outputs/log_output/model_sizes_0/GPTcorl_scratch_trainm_e2e_statet_pointnet_traini_0_nla_6_nhe_8_statel_0.01_2022-06-03_1654253046.3212142_2022-06-03_1654253046.3212266/model/epoch30.pth.tar" /> -->
     <!-- <arg name="model_path_act" default="/home/rb/hackathon_data_premium/aml_outputs/log_output/model_sizes_0/GPTcorl_scratch_trainm_e2e_statet_pointnet_traini_1_nla_24_nhe_8_statel_0.01_2022-06-03_1654235683.085602_2022-06-03_1654235683.0856125/model/epoch30.pth.tar" /> -->
+    <!-- <arg name="model_path_act" default="/home/rb/hackathon_data_premium/aml_outputs/log_output/model_sizes_1/GPTcorl_scratch_trainm_e2e_statet_pointnet_traini_1_nla_12_nhe_8_statel_0.1_2022-06-06_1654492441.2570548_2022-06-06_1654492441.2570653/model/epoch74.pth.tar" /> -->
+    <!-- <arg name="model_path_act" default="/home/rb/hackathon_data_premium/aml_outputs/log_output/model_sizes_1/GPTcorl_scratch_trainm_e2e_statet_pointnet_traini_1_nla_6_nhe_8_statel_0.1_2022-06-06_1654513698.5957458_2022-06-06_1654513698.5957568/model/epoch64.pth.tar" /> -->
+    <!-- <arg name="model_path_act" default="/home/rb/hackathon_data_premium/aml_outputs/log_output/model_sizes_1/GPTcorl_scratch_trainm_e2e_statet_pointnet_traini_1_nla_24_nhe_8_statel_0.1_2022-06-06_1654493649.8333972_2022-06-06_1654493649.8334105/model/epoch51.pth.tar" /> -->
 
     <!-- map model -->
     <arg name="use_map" default="false" />
@@ -26,7 +30,7 @@
     <arg name="use_loc" default="false" />
     <arg name="model_path_loc" default="/home/rb/hackathon_data_premium/aml_outputs/log_output/locscratch_new_0/GPTcorl_loc_trainm_loc_sta_pointnet_lr_6e-5_traini_1_nla_12_nhe_8_locx_0.01_locy_1_loca_10_locd_joint_2022-05-31_1653978601.5423563_2022-05-31_1653978601.5423756/model/epoch30.pth.tar" />
 
-    <arg name="deployment_map" default="test" />
+    <arg name="deployment_map" default="train" />
     <!-- <arg name="deployment_map" default="test" /> -->
 
     <group if="$(eval arg('deployment_map') == 'train')">
diff --git a/mushr_rhc_ros/src/rhcnode_network_pcl_new.py b/mushr_rhc_ros/src/rhcnode_network_pcl_new.py
index 5ba14fd..f9321d5 100755
--- a/mushr_rhc_ros/src/rhcnode_network_pcl_new.py
+++ b/mushr_rhc_ros/src/rhcnode_network_pcl_new.py
@@ -70,6 +70,9 @@ def __init__(self, dtype, params, logger, name):
         self.time_started_goal = None
         self.num_trials = 0
 
+        self.act_inference_time_sum = 0.0
+        self.act_inference_time_count = 0
+
         self.cur_rollout = self.cur_rollout_ip = None
         self.traj_pub_lock = threading.Lock()
 
@@ -107,7 +110,7 @@ def __init__(self, dtype, params, logger, name):
         self.use_map = rospy.get_param("~use_map", False)
         self.use_loc = rospy.get_param("~use_loc", False)
 
-        saved_model_path_action = rospy.get_param("~model_path_act", 'default_value')
+        saved_model_path_action = rospy.get_param("~model_path_act", '')
         self.out_path = rospy.get_param("~out_path", 'default_value')
 
         self.n_layers = rospy.get_param("~n_layers", 12)
@@ -127,19 +130,20 @@ def __init__(self, dtype, params, logger, name):
         model = GPT(mconf, device)
         # model=torch.nn.DataParallel(model)
 
-        checkpoint = torch.load(saved_model_path_action, map_location=device)
-        # old code for loading model
-        model.load_state_dict(checkpoint['state_dict'])
-        # new code for loading mode
-        # new_checkpoint = OrderedDict()
-        # for key in checkpoint['state_dict'].keys():
-        #     new_checkpoint[key.split("module.",1)[1]] = checkpoint['state_dict'][key]
-        # model.load_state_dict(new_checkpoint)
+        if len(saved_model_path_action)>0:
+            checkpoint = torch.load(saved_model_path_action, map_location=device)
+            # old code for loading model
+            model.load_state_dict(checkpoint['state_dict'])
+            # new code for loading mode
+            # new_checkpoint = OrderedDict()
+            # for key in checkpoint['state_dict'].keys():
+            #     new_checkpoint[key.split("module.",1)[1]] = checkpoint['state_dict'][key]
+            # model.load_state_dict(new_checkpoint)
 
-        # ckpt = torch.load('/home/rb/downloaded_models/epoch30.pth.tar')['state_dict']
-        # for key in ckpt:
-        #     print('********',key)
-        # model.load_state_dict(torch.load('/home/rb/downloaded_models/epoch30.pth.tar')['state_dict'], strict=True)
+            # ckpt = torch.load('/home/rb/downloaded_models/epoch30.pth.tar')['state_dict']
+            # for key in ckpt:
+            #     print('********',key)
+            # model.load_state_dict(torch.load('/home/rb/downloaded_models/epoch30.pth.tar')['state_dict'], strict=True)
 
         model.eval()
         # model.half()
@@ -532,6 +536,7 @@ def publish_vel_marker(self):
 
 
     def apply_network(self):
+        start_zero = time.time()
         x_imgs, x_act, t = self.prepare_model_inputs(queue_type='small')
         start = time.time()
         # with torch.set_grad_enabled(False):
@@ -539,15 +544,18 @@ def apply_network(self):
             # action_pred = 0.0
             action_pred, _, _, _ = self.model(states=x_imgs, actions=x_act, targets=x_act, gt_map=None, timesteps=t, poses=None, compute_loss=False)
             finished_action_network = time.time()
-            rospy.loginfo("action network delay: "+str(finished_action_network-start))
-            # rospy.loginfo_throttle(10, "action network delay: "+str(finished_action_network-start))
+            # rospy.loginfo("action network delay: "+str(finished_action_network-start))
+            # self.act_inference_time_sum += finished_action_network-start
+            # self.act_inference_time_count += 1
+            rospy.loginfo_throttle(10, "action network delay: "+str(finished_action_network-start))
+            # rospy.loginfo_throttle(10, "AVG action network delay: "+str(self.act_inference_time_sum/self.act_inference_time_count))
             action_pred = action_pred[0,-1,0].cpu().flatten().item()
             # if self.use_map:
             #     map_pred, loss = self.map_model(states=x_imgs, actions=x_act, targets=x_act, gt_map=None, timesteps=t, poses=None)
             #     finished_map_network = time.time()
             #     rospy.loginfo("map network delay: "+str(finished_map_network-finished_action_network))
         finished_network = time.time()
-        # rospy.loginfo("network delay: "+str(finished_network-finish_processing))
+        # rospy.loginfo("network delay total: "+str(finished_network-start_zero))
         # de-normalize
         action_pred = pre.denorm_angle(action_pred)
         return action_pred