[Refactor] Adapt deepseek-v3.2 to vllm 0.11.0 (#3432)

### What this PR does / why we need it?
Adapt deepseek-v3.2 to vllm 0.11.0, removing the useless patch.

The final goal is to remove all the patches and align the code arch to
vllm, thus we need to do the following work in next prs.
TODO:
- [x] remove patch on attention spec
- [ ] refactor the kvcache creation logic

### Does this PR introduce _any_ user-facing change?
N/A

### How was this patch tested?
1. CI passed with existing test.
2. Test pass with deepseek-v3.2-exp


- vLLM version: v0.11.0rc3
- vLLM main: https://github.com/vllm-project/vllm/commit/v0.11.0

Signed-off-by: MengqingCao <cmq0113@163.com>

vllm_ascend/platform.py

@@ -164,6 +164,9 @@ class NPUPlatform(Platform):
             "kv_cache_dtype", None)
         if kv_cache_dtype is not None:
             vllm_config.cache_config.cache_dtype = kv_cache_dtype
+        elif model_config and hasattr(model_config.hf_config, "index_topk"):
+            vllm_config.cache_config.cache_dtype = str(
+                model_config.dtype).replace("torch.", "")
         if model_config is None:
             logger.warning("Model config is missing. This may indicate "
                            "that we are running a test case")
@@ -284,25 +287,27 @@ class NPUPlatform(Platform):
             vllm_config.scheduler_config = ascend_scheduler_config
 
     @classmethod
-    def get_attn_backend_cls(cls,
-                             selected_backend,
-                             head_size,
-                             dtype,
-                             kv_cache_dtype,
-                             block_size,
-                             use_v1,
-                             use_mla,
-                             use_sfa,
-                             has_sink=False):
+    def get_attn_backend_cls(
+        cls,
+        selected_backend,
+        head_size,
+        dtype,
+        kv_cache_dtype,
+        block_size,
+        use_v1,
+        use_mla,
+        has_sink=False,
+        use_sparse=False,
+    ):
         if not use_v1:
             raise ValueError("vLLM Ascend does not support V0 engine.")
 
         ascend_config = get_ascend_config()
 
         if use_mla and ascend_config.enable_shared_expert_dp:
-            if use_mla and not use_sfa:
+            if use_mla and not use_sparse:
                 return "vllm_ascend.torchair.torchair_mla.AscendMLATorchairBackend"
-            if use_mla and use_sfa:
+            if use_mla and use_sparse:
                 return "vllm_ascend.torchair.torchair_sfa.AscendSFATorchairBackend"
 
         use_torchair = ascend_config.torchair_graph_config.enabled
@@ -321,7 +326,7 @@ class NPUPlatform(Platform):
             (True, True, True):
             "vllm_ascend.torchair.torchair_sfa.AscendSFATorchairBackend",
         }
-        return backend_map[(use_mla, use_sfa, use_torchair)]
+        return backend_map[(use_mla, use_sparse, use_torchair)]
 
     @classmethod
     def get_punica_wrapper(cls) -> str: