diff --git a/modules/transformation.py b/modules/transformation.py
index e543e0c..7c4dd5a 100755
--- a/modules/transformation.py
+++ b/modules/transformation.py
@@ -90,8 +90,12 @@ class GridGenerator(nn.Module):
         self.F = F
         self.C = self._build_C(self.F)  # F x 2
         self.P = self._build_P(self.I_r_width, self.I_r_height)
+        ## for multi-gpu, you need register buffer
         self.register_buffer("inv_delta_C", torch.tensor(self._build_inv_delta_C(self.F, self.C)).float())  # F+3 x F+3
         self.register_buffer("P_hat", torch.tensor(self._build_P_hat(self.F, self.C, self.P)).float())  # n x F+3
+        ## for fine-tuning with different image width, you may use below instead of self.register_buffer
+        #self.inv_delta_C = torch.tensor(self._build_inv_delta_C(self.F, self.C)).float().cuda()  # F+3 x F+3
+        #self.P_hat = torch.tensor(self._build_P_hat(self.F, self.C, self.P)).float().cuda()  # n x F+3
 
     def _build_C(self, F):
         """ Return coordinates of fiducial points in I_r; C """