remove clip and dino loss in evaluation

Author: yd-yin

lerf/lerf.py

@@ -206,10 +206,11 @@ def _get_outputs_nerfacto(self, ray_samples: RaySamples):
 
     def get_loss_dict(self, outputs, batch, metrics_dict=None):
         loss_dict = super().get_loss_dict(outputs, batch, metrics_dict)
-        loss_dict["clip_loss"] = self.config.clip_loss_weight * torch.nn.functional.huber_loss(
-            outputs["clip"], batch["clip"], delta=1.25
-        )
-        loss_dict["dino_loss"] = torch.nn.functional.mse_loss(outputs["dino"], batch["dino"])
+        if self.training:
+            loss_dict["clip_loss"] = self.config.clip_loss_weight * torch.nn.functional.huber_loss(
+                outputs["clip"], batch["clip"], delta=1.25
+            )
+            loss_dict["dino_loss"] = torch.nn.functional.mse_loss(outputs["dino"], batch["dino"])
         return loss_dict
 
     def get_param_groups(self) -> Dict[str, List[Parameter]]: