Fix DeepSeek error when using DeepEP mode (#5190)

python/sglang/srt/models/deepseek_v2.py

@@ -280,10 +280,7 @@ class DeepseekV2MoE(nn.Module):
             return self.forward_deepep(hidden_states, forward_mode)
 
     def forward_normal(self, hidden_states: torch.Tensor) -> torch.Tensor:
-        if self.n_shared_experts is not None and self.n_share_experts_fusion == 0:
-            shared_output = self.shared_experts(hidden_states)
-        else:
-            shared_output = None
+        shared_output = self._forward_shared_experts(hidden_states)
         # router_logits: (num_tokens, n_experts)
         router_logits = self.gate(hidden_states)
         final_hidden_states = (
@@ -313,8 +310,7 @@ class DeepseekV2MoE(nn.Module):
         ):
             # router_logits: (num_tokens, n_experts)
             router_logits = self.gate(hidden_states)
-            if self.n_shared_experts is not None:
-                shared_output = self.shared_experts(hidden_states)
+            shared_output = self._forward_shared_experts(hidden_states)
             topk_weights, topk_idx = select_experts(
                 hidden_states=hidden_states,
                 router_logits=router_logits,
@@ -364,6 +360,12 @@ class DeepseekV2MoE(nn.Module):
 
         return final_hidden_states
 
+    def _forward_shared_experts(self, hidden_states):
+        if self.n_shared_experts is not None and self.n_share_experts_fusion == 0:
+            return self.shared_experts(hidden_states)
+        else:
+            return None
+
 
 def yarn_get_mscale(scale: float = 1, mscale: float = 1) -> float:
     import math