[bugfix] Use FUSED_MC2 MoE comm path for the op dispatch_ffn_combine (#5156)

### What this PR does / why we need it?

- Renames the MoE comm enum value `MoECommType.FUSED_ALLTOALL` to
`MoECommType.FUSED_MC2` and updates all call sites.
- Updates `select_moe_comm_method` to optionally select `FUSED_MC2` on
Ascend A3 when:
  - `enable_expert_parallel=True`
  - quantization is `w8a8_dynamic`
  - `EP <= 16`
  - `dynamic_eplb` is disabled
  - `is_mtp_model = False`
- Replaces the old “fused all-to-all” comm implementation with
`FusedMC2CommImpl`, using `TokenDispatcherWithMC2` /
`PrepareAndFinalizeWithMC2` and `dispatch_ffn_combine`.

- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c

---------

Signed-off-by: Chen Chen <0109chenchen@gmail.com>

vllm_ascend/ops/fused_moe/fused_moe.py

@@ -533,7 +533,7 @@ class AscendSharedFusedMoE(SharedFusedMoE, AscendFusedMoE):
             # NOTE: This is exactly the opposite of `maybe_all_reduce_tensor_model_parallel`
             forward_context = get_forward_context()
             moe_comm_type = forward_context.moe_comm_type
-            if moe_comm_type in {MoECommType.ALLTOALL, MoECommType.MC2, MoECommType.FUSED_ALLTOALL} \
+            if moe_comm_type in {MoECommType.ALLTOALL, MoECommType.MC2, MoECommType.FUSED_MC2} \
                     and not shared_expert_dp_enabled():
                 shared_out = tensor_model_parallel_all_reduce(shared_out)
         else: