diff --git a/models/dcgan.py b/models/dcgan.py
index 9a9ae4c..1dd8dbf 100644
--- a/models/dcgan.py
+++ b/models/dcgan.py
@@ -44,10 +44,11 @@ class DCGAN_D(nn.Module):
 
 
     def forward(self, input):
-        gpu_ids = None
         if isinstance(input.data, torch.cuda.FloatTensor) and self.ngpu > 1:
-            gpu_ids = range(self.ngpu)
-        output = nn.parallel.data_parallel(self.main, input, gpu_ids)
+            output = nn.parallel.data_parallel(self.main, input, range(self.ngpu))
+        else: 
+            output = self.main(input)
+            
         output = output.mean(0)
         return output.view(1)
 
@@ -98,11 +99,11 @@ class DCGAN_G(nn.Module):
         self.main = main
 
     def forward(self, input):
-        gpu_ids = None
         if isinstance(input.data, torch.cuda.FloatTensor) and self.ngpu > 1:
-            gpu_ids = range(self.ngpu)
-        return nn.parallel.data_parallel(self.main, input, gpu_ids)
-
+            output = nn.parallel.data_parallel(self.main, input, range(self.ngpu))
+        else: 
+            output = self.main(input)
+        return output 
 ###############################################################################
 class DCGAN_D_nobn(nn.Module):
     def __init__(self, isize, nz, nc, ndf, ngpu, n_extra_layers=0):
@@ -143,10 +144,11 @@ class DCGAN_D_nobn(nn.Module):
 
 
     def forward(self, input):
-        gpu_ids = None
         if isinstance(input.data, torch.cuda.FloatTensor) and self.ngpu > 1:
-            gpu_ids = range(self.ngpu)
-        output = nn.parallel.data_parallel(self.main, input, gpu_ids)
+            output = nn.parallel.data_parallel(self.main, input, range(self.ngpu))
+        else: 
+            output = self.main(input)
+            
         output = output.mean(0)
         return output.view(1)
 
@@ -190,7 +192,8 @@ class DCGAN_G_nobn(nn.Module):
         self.main = main
 
     def forward(self, input):
-        gpu_ids = None
         if isinstance(input.data, torch.cuda.FloatTensor) and self.ngpu > 1:
-            gpu_ids = range(self.ngpu)
-        return nn.parallel.data_parallel(self.main, input, gpu_ids)
+            output = nn.parallel.data_parallel(self.main, input,  range(self.ngpu))
+        else: 
+            output = self.main(input)
+        return output