[Feature]EPLB:Adapt DispatchGmmCombineDecode operator to eplb tensor list and expert token numbers (#5552)

#### What this PR does / why we need it?
This PR adapt DispatchGmmCombineDecode operator to eplb tensor list and
expert token numbers.

This operator support gmm1, gmm2, gmm1Scale and gmm2Scale in format of
list.
This operator support couting how many token each local expert recieves
by expertTokensNum .


- vLLM version: v0.13.0
- vLLM main:
7157596103

More info about this operator, please refer to RFC: issue
https://github.com/vllm-project/vllm-ascend/issues/5476

vllm_ascend/ops/fused_moe/moe_comm_method.py

@@ -300,6 +300,8 @@ class FusedMC2CommImpl(MoECommMethod):
 
         assert isinstance(self.token_dispatcher, TokenDispatcherWithMC2), \
             "token_dispatcher must be an instance of TokenDispatcherWithMC2."
+        group_list_type = None
+        expert_tokens = None
         if envs_ascend.VLLM_ASCEND_ENABLE_FUSED_MC2 == 1:
             out = torch.empty_like(hidden_states)
             torch.ops._C_ascend.dispatch_ffn_combine(  # type: ignore
@@ -316,13 +318,14 @@ class FusedMC2CommImpl(MoECommMethod):
             )
         elif envs_ascend.VLLM_ASCEND_ENABLE_FUSED_MC2 == 2:
             assert expert_map is not None, "expert_map cannot be None."
-            out, _ = torch.ops._C_ascend.dispatch_gmm_combine_decode(  # type: ignore
+            group_list_type = 1
+            out, expert_tokens = torch.ops._C_ascend.dispatch_gmm_combine_decode(  # type: ignore
                 x=hidden_states,
                 expert_ids=topk_ids,
-                gmm1_permuted_weight=w1[0],
-                gmm1_permuted_weight_scale=w1_scale[0],
-                gmm2_weight=w2[0],
-                gmm2_weight_scale=w2_scale[0],
+                gmm1_permuted_weight=w1,
+                gmm1_permuted_weight_scale=w1_scale,
+                gmm2_weight=w2,
+                gmm2_weight_scale=w2_scale,
                 expert_smooth_scales=None,
                 expert_scales=topk_weights.to(torch.float32),
                 group_ep=self.token_dispatcher.moe_all_to_all_group_name,
@@ -333,4 +336,6 @@ class FusedMC2CommImpl(MoECommMethod):
         else:
             raise ValueError(
                 f"Wrong value of {envs_ascend.VLLM_ASCEND_ENABLE_FUSED_MC2=}")
-        return FusedExpertsResult(routed_out=out)
+        return FusedExpertsResult(routed_out=out,
+                                  group_list_type=group_list_type,
+                                  expert_tokens=expert_tokens)