diff --git a/test.py b/test.py
old mode 100755
new mode 100644
index 2729657..8a5adf6
--- a/test.py
+++ b/test.py
@@ -19,13 +19,16 @@ def detect(net,img):
     img = img.transpose(2, 0, 1)
     img = img.reshape((1,)+img.shape)
 
-    img = Variable(torch.from_numpy(img).float(),volatile=True).cuda()
+    img = Variable(torch.from_numpy(img).float())
+    if use_cuda:
+        img = img.cuda()
     BB,CC,HH,WW = img.size()
-    olist = net(img)
+    with torch.no_grad():
+        olist = net(img)
 
     bboxlist = []
-    for i in range(len(olist)/2): olist[i*2] = F.softmax(olist[i*2])
-    for i in range(len(olist)/2):
+    for i in range(int(len(olist)/2)): olist[i*2] = F.softmax(olist[i*2])
+    for i in range(int(len(olist)/2)):
         ocls,oreg = olist[i*2].data.cpu(),olist[i*2+1].data.cpu()
         FB,FC,FH,FW = ocls.size() # feature map size
         stride = 2**(i+2)    # 4,8,16,32,64,128
@@ -58,7 +61,8 @@ def detect(net,img):
 net = getattr(net_s3fd,args.net)()
 if args.model!='' :net.load_state_dict(torch.load(args.model))
 else: print('Please set --model parameter!')
-net.cuda()
+if use_cuda:
+    net.cuda()
 net.eval()
 
 
@@ -82,4 +86,4 @@ def detect(net,img):
         if cv2.waitKey(1) & 0xFF == ord('q'): break
     else:
         cv2.imwrite(args.path[:-4]+'_output.png',imgshow)
-        if cv2.waitKey(0) or True: break
\ No newline at end of file
+        if cv2.waitKey(0) or True: break