[Feature] Support moe multi-stream for aclgraph. (#2946)

This PR puts the calculation of shared experts into a separate stream,
overlaping with routing experts.

- vLLM version: v0.10.2
- vLLM main:
fbd6523ac0

---------

Signed-off-by: whx-sjtu <2952154980@qq.com>

vllm_ascend/torchair/models/torchair_deepseek_v2.py

@@ -322,8 +322,8 @@ class TorchairDeepseekV2MoE(nn.Module):
 
         ascend_config = get_ascend_config()
         self.torchair_graph_enabled = ascend_config.torchair_graph_config.enabled
-        self.enable_multistream_moe = \
-            ascend_config.torchair_graph_config.enable_multistream_moe and \
+        self.multistream_overlap_shared_expert = \
+            ascend_config.multistream_overlap_shared_expert and \
             self.torchair_graph_enabled
 
         self.gate = ReplicatedLinear(config.hidden_size,
@@ -364,7 +364,7 @@ class TorchairDeepseekV2MoE(nn.Module):
                 hidden_act=config.hidden_act,
                 quant_config=quant_config,
                 reduce_results=reduce_results,
-                force_replicate=self.enable_multistream_moe
+                force_replicate=self.multistream_overlap_shared_expert
                 or enable_shared_expert_dp,
                 prefix=f"{prefix}.shared_experts",
             )
@@ -406,7 +406,7 @@ class TorchairDeepseekV2MoE(nn.Module):
 
         # router_logits: (num_tokens, n_experts)
         router_logits = None
-        if not self.rm_router_logits and not self.enable_multistream_moe:
+        if not self.rm_router_logits and not self.multistream_overlap_shared_expert:
             router_logits, _ = self.gate(hidden_states)
 
         experts_hidden_states = self.experts(
@@ -524,7 +524,7 @@ class TorchairDeepseekV2MLAAttention(DeepseekV2MLAAttention):
         elif (config.n_routed_experts is not None
               and self.debug_layer_idx >= config.first_k_dense_replace
               and self.debug_layer_idx % config.moe_layer_freq == 0
-              and (ascend_config.torchair_graph_config.enable_multistream_moe
+              and (ascend_config.multistream_overlap_shared_expert
                    or self.enable_shared_expert_dp)):
             self.o_proj = TorchairDeepseekV2RowParallelLinearReplaceAllreduce(
                 self.num_heads * self.v_head_dim,
@@ -697,7 +697,7 @@ class TorchairDeepseekV2DecoderLayer(DeepseekV2DecoderLayer):
                 quant_config=quant_config,
                 prefix=f"{prefix}.mlp",
             )
-            self.mla_moe_communication = ascend_config.torchair_graph_config.enable_multistream_moe \
+            self.mla_moe_communication = ascend_config.multistream_overlap_shared_expert \
                 and model_config.use_mla and self.tp_size > 1
         else:
             self.mlp = TorchairDeepseekV2MLP(