Upscaler.load_model: don't return None, just use exceptions

extensions-builtin/ScuNET/scripts/scunet_model.py

@@ -1,4 +1,3 @@
-import os.path
 import sys
 
 import PIL.Image
@@ -8,7 +7,7 @@ from tqdm import tqdm
 
 import modules.upscaler
 from modules import devices, modelloader, script_callbacks, errors
-from scunet_model_arch import SCUNet as net
+from scunet_model_arch import SCUNet
 
 from modules.modelloader import load_file_from_url
 from modules.shared import opts
@@ -88,9 +87,10 @@ class UpscalerScuNET(modules.upscaler.Upscaler):
 
         torch.cuda.empty_cache()
 
-        model = self.load_model(selected_file)
-        if model is None:
-            print(f"ScuNET: Unable to load model from {selected_file}", file=sys.stderr)
+        try:
+            model = self.load_model(selected_file)
+        except Exception as e:
+            print(f"ScuNET: Unable to load model from {selected_file}: {e}", file=sys.stderr)
             return img
 
         device = devices.get_device_for('scunet')
@@ -123,11 +123,7 @@ class UpscalerScuNET(modules.upscaler.Upscaler):
             filename = load_file_from_url(self.model_url, model_dir=self.model_download_path, file_name=f"{self.name}.pth")
         else:
             filename = path
-        if not os.path.exists(os.path.join(self.model_path, filename)) or filename is None:
-            print(f"ScuNET: Unable to load model from {filename}", file=sys.stderr)
-            return None
-
-        model = net(in_nc=3, config=[4, 4, 4, 4, 4, 4, 4], dim=64)
+        model = SCUNet(in_nc=3, config=[4, 4, 4, 4, 4, 4, 4], dim=64)
         model.load_state_dict(torch.load(filename), strict=True)
         model.eval()
         for _, v in model.named_parameters():