Update app.py

app.py

@@ -26,7 +26,7 @@ cwd = os.getcwd()
 print("Current working directory:", cwd)
 
 # Installing dependencies not in requirements.txt
-#@spaces.GPU
+@spaces.GPU
 def install_add_dependencies():
     print("inside install_add_dependencies")
     print(torch.cuda.is_available())
@@ -41,8 +41,8 @@ def build_custom_prompter():
 
 build_custom_prompter()
 from gradio_image_prompter import ImagePrompter
-print("torch version")
-print(torch.version.cuda)
+#print("torch version")
+#print(torch.version.cuda)
 #install_add_dependencies()
 
 class AppSteps(Enum):
@@ -112,8 +112,9 @@ def get_args_parser():
     parser.add_argument("--amp", action="store_true", help="Train with mixed precision")
     return parser
 
-@spaces.GPU
+
 # Get counting model.
+@spaces.GPU
 def build_model_and_transforms(args):
     normalize = T.Compose(
         [T.ToTensor(), T.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])]
@@ -161,10 +162,11 @@ def build_model_and_transforms(args):
 
 parser = argparse.ArgumentParser("Counting Application", parents=[get_args_parser()])
 args = parser.parse_args()
-if torch.cuda.is_available():
-    args.device = torch.device('cuda')
-else:
-    args.device = torch.device('cpu')
+#if torch.cuda.is_available():
+#    args.device = torch.device('cuda')
+#else:
+#    args.device = torch.device('cpu')
+args.device = torch.device('cuda')
 model, transform = build_model_and_transforms(args)
 
 examples = [