[1/N][Feat] Support MoE models with ACL Graph and refactor MoE communication logic (#2125)

### What this PR does / why we need it?
This PR refactors the MoE (Mixture of Experts) communication logic by
introducing a strategy pattern. It defines an abstract base class,
`MoECommMethod`, which encapsulates different communication strategies
for MoE layers. By decoupling the MoE implementation from any single
communication method, this change makes it simpler to add, replace, or
optimize communication strategies in the future.

Plan / Roadmap

1. Introduce `MoECommMethod`, implement `AllGatherImpl`, and adapt ACL
Graph handling to cover all scenarios (this PR).
2. Implement `MC2CommImpl` and `AllToAllCommImpl` to optimize
performance in specific scenarios.
3. Enable W8A8 / Int8 models to use `unified_fused_experts`.

Other notes

* Data-parallel (DP) communication currently does not work with vLLM's
dispatch/combine mechanisms; an alternative approach is required to
resolve this incompatibility.

- vLLM version: v0.10.0
- vLLM main:
f7ad6a1eb3

---------

Signed-off-by: Yizhou Liu <liu_yizhou@outlook.com>

vllm_ascend/platform.py

@@ -205,8 +205,15 @@ class NPUPlatform(Platform):
         register_ascend_customop()
 
     @classmethod
-    def get_attn_backend_cls(cls, selected_backend, head_size, dtype,
-                             kv_cache_dtype, block_size, use_v1, use_mla):
+    def get_attn_backend_cls(cls,
+                             selected_backend,
+                             head_size,
+                             dtype,
+                             kv_cache_dtype,
+                             block_size,
+                             use_v1,
+                             use_mla,
+                             has_sink=False):
         if not use_v1:
             raise ValueError("vLLM Ascend does not support V0 engine.")