apply z-loss and aux-loss only during training

aria/model/moe_lm.py

@@ -255,7 +255,8 @@ def routing(
                 - top_indices: Indices of top-k experts for each token.
                 - tokens_per_expert: Number of tokens assigned to each expert.
         """
-        logits = self.apply_z_loss(logits)
+        if self.training:
+            logits = self.apply_z_loss(logits)
 
         top_logits, top_indices = torch.topk(logits, k=self.config.moe_topk, dim=1)
         scores = torch.softmax(top_logits, dim=-1, dtype=torch.float32).type_as(logits)
@@ -267,7 +268,8 @@ def routing(
             max=self.config.moe_num_experts - 1,
         )
 
-        scores = self.apply_aux_loss(logits, tokens_per_expert, scores)
+        if self.training:
+            scores = self.apply_aux_loss(logits, tokens_per_expert, scores)
         return scores, top_indices, tokens_per_expert
 
     def forward(