diff --git a/sac.py b/sac.py
index 103d1a6..f494344 100644
--- a/sac.py
+++ b/sac.py
@@ -27,7 +27,7 @@ class SAC(object):
 
         if self.policy_type == "Gaussian":
             # Target Entropy = −dim(A) (e.g. , -6 for HalfCheetah-v2) as given in the paper
-            if self.automatic_entropy_tuning == True:
+            if self.automatic_entropy_tuning is True:
                 self.target_entropy = -torch.prod(torch.Tensor(action_space.shape).to(self.device)).item()
                 self.log_alpha = torch.zeros(1, requires_grad=True, device=self.device)
                 self.alpha_optim = Adam([self.log_alpha], lr=args.lr)
@@ -43,7 +43,7 @@ class SAC(object):
 
     def select_action(self, state, eval=False):
         state = torch.FloatTensor(state).to(self.device).unsqueeze(0)
-        if eval == False:
+        if eval is False:
             action, _, _ = self.policy.sample(state)
         else:
             _, _, action = self.policy.sample(state)