Overlap the gating function with shared experts in DeepSeek (#7978)

python/sglang/srt/models/deepseek_v2.py

@@ -437,21 +437,21 @@ class DeepseekV2MoE(nn.Module):
     def forward_normal_dual_stream(
         self, hidden_states: torch.Tensor, can_fuse_mlp_allreduce: bool = False
     ) -> torch.Tensor:
-        # router_logits: (num_tokens, n_experts)
-        router_logits = self.gate(hidden_states)
 
         current_stream = torch.cuda.current_stream()
         self.alt_stream.wait_stream(current_stream)
         shared_output = self._forward_shared_experts(hidden_states)
 
         with torch.cuda.stream(self.alt_stream):
+            # router_logits: (num_tokens, n_experts)
+            router_logits = self.gate(hidden_states)
             final_hidden_states = self.experts(
                 hidden_states=hidden_states, router_logits=router_logits
             )
             if not _is_cuda:
                 final_hidden_states *= self.routed_scaling_factor
         current_stream.wait_stream(self.alt_stream)
-        final_hidden_states = final_hidden_states + shared_output
+        final_hidden_states += shared_output
         if self.tp_size > 1 and not can_fuse_mlp_allreduce:
             final_hidden_states = tensor_model_parallel_all_reduce(final_hidden_states)
         return final_hidden_states