diff --git a/sac.py b/sac.py
index f494344..141c0b8 100644
--- a/sac.py
+++ b/sac.py
@@ -17,7 +17,7 @@ class SAC(object):
         self.target_update_interval = args.target_update_interval
         self.automatic_entropy_tuning = args.automatic_entropy_tuning
 
-        self.device = torch.device("cuda" if args.cuda else "cpu") 
+        self.device = torch.device("cuda" if args.cuda else "cpu")
 
         self.critic = QNetwork(num_inputs, action_space.shape[0], args.hidden_size).to(device=self.device)
         self.critic_optim = Adam(self.critic.parameters(), lr=args.lr)
@@ -41,9 +41,9 @@ class SAC(object):
             self.policy = DeterministicPolicy(num_inputs, action_space.shape[0], args.hidden_size, action_space).to(self.device)
             self.policy_optim = Adam(self.policy.parameters(), lr=args.lr)
 
-    def select_action(self, state, eval=False):
+    def select_action(self, state, evaluate=False):
         state = torch.FloatTensor(state).to(self.device).unsqueeze(0)
-        if eval is False:
+        if evaluate is False:
             action, _, _ = self.policy.sample(state)
         else:
             _, _, action = self.policy.sample(state)
@@ -119,7 +119,7 @@ class SAC(object):
         print('Saving models to {} and {}'.format(actor_path, critic_path))
         torch.save(self.policy.state_dict(), actor_path)
         torch.save(self.critic.state_dict(), critic_path)
-    
+        
     # Load model parameters
     def load_model(self, actor_path, critic_path):
         print('Loading models from {} and {}'.format(actor_path, critic_path))