diff --git a/head/metrics.py b/head/metrics.py
index 466dc83..4ee714b 100644
--- a/head/metrics.py
+++ b/head/metrics.py
@@ -79,10 +79,7 @@ def __init__(self, in_features, out_features, s = 64.0, m = 0.50, easy_margin =
     def forward(self, embbedings, label):
         embbedings = l2_norm(embbedings, axis = 1)
         kernel_norm = l2_norm(self.kernel, axis = 0)
-        cos_theta = torch.mm(embbedings, kernel_norm)
-        cos_theta = cos_theta.clamp(-1, 1)  # for numerical stability
-        with torch.no_grad():
-            origin_cos = cos_theta.clone()
+        cos_theta = torch.mm(embbedings, kernel_norm).clamp_(-1, 1)  # for numerical stability
         target_logit = cos_theta[torch.arange(0, embbedings.size(0)), label].view(-1, 1)
 
         sin_theta = torch.sqrt(1.0 - torch.pow(target_logit, 2))
@@ -341,10 +338,7 @@ def __init__(self, in_features, out_features, m = 0.5, s = 64.):
     def forward(self, embbedings, label):
         embbedings = l2_norm(embbedings, axis = 1)
         kernel_norm = l2_norm(self.kernel, axis = 0)
-        cos_theta = torch.mm(embbedings, kernel_norm)
-        cos_theta = cos_theta.clamp(-1, 1)  # for numerical stability
-        with torch.no_grad():
-            origin_cos = cos_theta.clone()
+        cos_theta = torch.mm(embbedings, kernel_norm).clamp_(-1, 1)  # for numerical stability
         target_logit = cos_theta[torch.arange(0, embbedings.size(0)), label].view(-1, 1)
 
         sin_theta = torch.sqrt(1.0 - torch.pow(target_logit, 2))
@@ -584,4 +578,4 @@ def forward(self, input, label):
 
         output = torch.logsumexp(logit_n, dim=1) + torch.logsumexp(logit_p, dim=1)
 
-        return output
\ No newline at end of file
+        return output