[Feature]Use DispatchGmmCombineDecode operator to replace MC2(Optional) (#5040)

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

This PR adds model-side integration for the previously introduced
experimental AscendC fused operator DispatchGmmCombineDecode, used in
MoE decoding.

The operator implementation itself was added in a prior PR[#4139
](https://github.com/vllm-project/vllm-ascend/pull/4139).
This change only adapts the model execution path to optionally use the
fused operator.

When the environment variable VLLM_ASCEND_ENABLE_FUSED_MC2=2 is set, the
original MC2 path composed of multiple operators (A8W8 dispatch → GMM →
SwiGLU → GMM → combine) might be replaced by the single fused operator
DispatchGmmCombineDecode.

By default, the existing multi-operator MC2 implementation is preserved.

### Does this PR introduce _any_ user-facing change?

### How was this patch tested?

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

Signed-off-by: wangqiankun <wangqiankun13@huawei.com>

vllm_ascend/ops/fused_moe/fused_moe.py

@@ -345,7 +345,7 @@ class AscendFusedMoE(FusedMoE):
                 shared_out = fc3_context.shared_experts(hidden_states)
                 # NOTE: This is exactly the opposite of `maybe_all_reduce_tensor_model_parallel`
                 moe_comm_type = forward_context.moe_comm_type
-                if moe_comm_type in {MoECommType.ALLTOALL, MoECommType.MC2} \
+                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)
                 set_flash_common3_context(shared_out=shared_out)