Upload app.py

app.py

@@ -407,8 +407,9 @@ class SpanStrategy(UpscalerStrategy):
                         elif (psutil.cpu_count(logical=False) or 0) < 4 and Config.DEVICE == 'cpu':
                              logger.info("ℹ Skipping torch.compile on low-core CPU.")
                         else:
-                            self.model = torch.compile(self.model)
-                            logger.info("✓ torch.compile enabled (default mode)")
+                            # SPAN architecture uses .data.clone() in forward pass which breaks torch.compile/inductor
+                            logger.info("ℹ Skipping torch.compile for SPAN (incompatible architecture).")
+                            # self.model = torch.compile(self.model) 
                         self.compiled = True
                     except Exception:
                         self.compiled = True
@@ -524,10 +525,11 @@ class HatsStrategy(UpscalerStrategy):
         h, w = img_np.shape[:2]
         tile_config = select_tile_config(h, w)
         
-        dtype = torch.float16 if Config.DEVICE == 'cuda' else torch.bfloat16
+        dtype = torch.float16 if Config.DEVICE == 'cuda' else torch.float32
         
         try:
-            with torch.autocast(device_type=Config.DEVICE, dtype=dtype):
+            context = torch.autocast(device_type=Config.DEVICE, dtype=dtype) if Config.DEVICE != 'cpu' else torch.no_grad()
+            with context:
                 if tile_config['tile'] > 0:
                      output_tensor = manual_tile_upscale(
                         self.model,