sb

app.py

@@ -24,7 +24,7 @@ net_c=net_c.to('cpu')
 #net_c=net_c.to('cuda')
 net_i.eval().to('cuda')
 net_c.eval().to('cuda')
-
+image_tensor = torch.zeros((1, 3, 420, 420), device='cuda')
 def align(x1):
     h, w = x1.shape[:2]
     h, w = h // 32 * 32, w // 32 * 32
@@ -33,8 +33,8 @@ def align(x1):
 
 def pipe(img):
     img=align(img)
-    image_tensor=TF.to_tensor(img)
-    image_tensor=image_tensor.unsqueeze(0).to('cuda')
+    img=TF.to_tensor(img)
+    image_tensor=img.unsqueeze(0)
     return predict(image_tensor)
 
 @spaces.GPU(duration=120)