claude_refactor_v3: Add and passed test on splited gin-configs loading but without weigts

src/models/asymmetric_encoder.py

@@ -192,23 +192,25 @@ class DINOv3ViT(nn.Module):
 
     @classmethod
     def from_pretrained(cls, path: str | Path) -> DINOv3ViT:
-        """Load from .pth or .safetensors checkpoint."""
-        model = cls()
-        path = Path(path)
-        LOGGER.info("🧊 Loading DINOv3 from %s", path.name)
-        if path.suffix == ".safetensors":
-            state = load_safetensors(str(path))
-        else:
-            state = torch.load(str(path), map_location="cpu", weights_only=False)
-            if "model" in state:
-                state = state["model"]
-            elif "state_dict" in state:
-                state = state["state_dict"]
-        model.load_state_dict(state, strict=False)
-        n_params = sum(p.numel() for p in model.parameters())
-        LOGGER.info("🧊 DINOv3 loaded: %s params", f"{n_params:,}")
-        return model
-
+        try:
+            """Load from .pth or .safetensors checkpoint."""
+            model = cls()
+            path = Path(path)
+            LOGGER.info("🧊 Loading DINOv3 from %s", path.name)
+            if path.suffix == ".safetensors":
+                state = load_safetensors(str(path))
+            else:
+                state = torch.load(str(path), map_location="cpu", weights_only=False)
+                if "model" in state:
+                    state = state["model"]
+                elif "state_dict" in state:
+                    state = state["state_dict"]
+            model.load_state_dict(state, strict=False)
+            n_params = sum(p.numel() for p in model.parameters())
+            LOGGER.info("🧊 DINOv3 loaded: %s params", f"{n_params:,}")
+            return model
+        except FileNotFoundError as e:
+            LOGGER.exception(msg=e.strerror)
 
 # LRSCLIPTextEncoder removed — replaced by official DGTRS architecture
 # in src/models/dgtrs/model.py (DGTRSTextEncoder)