Removed GPU for building models and transforms

app.py

@@ -116,7 +116,6 @@ def get_device():
         return torch.device('cpu')
 
 # 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])]
@@ -137,7 +136,8 @@ def build_model_and_transforms(args):
         else:
             raise ValueError("Key {} can used by args only".format(k))
 
-    device = torch.device(args.device)
+    # Start with model on CPU.
+    args.device = "cpu"
     # fix the seed for reproducibility
     seed = 42
     torch.manual_seed(seed)
@@ -156,7 +156,6 @@ def build_model_and_transforms(args):
     model.load_state_dict(checkpoint, strict=False)
 
     model.eval()
-    model.cpu()
 
     return model, data_transform
 
@@ -164,7 +163,7 @@ def build_model_and_transforms(args):
 parser = argparse.ArgumentParser("Counting Application", parents=[get_args_parser()])
 args = parser.parse_args()
 
-args.device = get_device()
+device = get_device()
 model, transform = build_model_and_transforms(args)
 
 examples = [
@@ -406,7 +405,7 @@ As shown earlier, there are 3 ways to specify the object to count: (1) with text
 
 with gr.Blocks(title="CountGD: Multi-Modal Open-World Counting", theme="soft", head="""<meta name="viewport" content="width=device-width, initial-scale=1, user-scalable=1">""") as demo:
     state = gr.State(value=[AppSteps.JUST_TEXT])
-    device = gr.State(args.device)
+    device = gr.State(device)
     with gr.Tab("Tutorial"):
         with gr.Row():
             with gr.Column():