[CustomOp] Register AscendSharedFusedMoE custom op (#2980)

### What this PR does / why we need it?
Register `AscendSharedFusedMoE` custom op.

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

No.

### How was this patch tested?

`DeepSeek-V2-Lite` is a MoE model with shared experts.

Test:

```bash
vllm serve /root/.cache/modelscope/hub/models/deepseek-ai/DeepSeek-V2-Lite \
--trust-remote-code \
--enforce-eager \
--no-enable-prefix-caching \
--gpu-memory-utilization 0.95

curl -X POST http://localhost:8000/v1/chat/completions \
    -H "Content-Type: application/json" \
    -d '{
        "model": "/root/.cache/modelscope/hub/models/deepseek-ai/DeepSeek-V2-Lite",
        "messages": [
            {"role": "user", "content": "介绍一下联通公司？"}
        ],
        "stream": false,
        "max_tokens": 100
    }'
```

Output:

```bash
中国联合网络通信集团有限公司（简称“中国联通”）于2009年1月6日在原中国网通和原中国联通的基础上合并组建而成，在国内31个省（自治区、直辖市）和境外多个国家和地区设有分支机构，是中国唯一一家在纽约、香港、上海三地同时上市的电信运营企业，连续多年入选“世界500强企业”。\n\n中国联通主要经营固定通信业务，移动通信业务，国内
```


- vLLM version: v0.10.2
- vLLM main:
vllm-project/vllm@486c559

---------

Signed-off-by: Shanshan Shen <87969357+shen-shanshan@users.noreply.github.com>
Signed-off-by: shen-shanshan <467638484@qq.com>

Author: shen-shanshan

vllm_ascend/ops/common_fused_moe.py

@@ -27,6 +27,7 @@
     FusedMoEParallelConfig  # isort: skip
 from vllm.model_executor.layers.fused_moe.layer import (
     FusedMoE, UnquantizedFusedMoEMethod, determine_expert_map)
+from vllm.model_executor.layers.shared_fused_moe import SharedFusedMoE
 
 from vllm_ascend.ascend_config import get_ascend_config
 from vllm_ascend.distributed.parallel_state import get_mc2_group
@@ -415,15 +416,15 @@ def _load_w2(self,
         expert_data.copy_(loaded_weight)
 
 
-class AscendSharedFusedMoE(AscendFusedMoE):
+class AscendSharedFusedMoE(SharedFusedMoE, AscendFusedMoE):
 
     def __init__(
         self,
         shared_experts: torch.nn.Module,
         use_overlapped: bool = True,
         **kwargs,
     ):
-        super().__init__(**kwargs)
+        AscendFusedMoE.__init__(self, **kwargs)
         self._shared_experts = shared_experts
         self.use_overlapped = use_overlapped
         self.shared_expert_stream = None
@@ -452,7 +453,8 @@ def forward(
             if moe_comm_method_name in {"alltoallcommimpl", "mc2commimpl"}:
                 shared_out = tensor_model_parallel_all_reduce(shared_out)
 
-        fused_out = super().forward(
+        _, fused_out = AscendFusedMoE.forward(
+            self,
             hidden_states=hidden_states,
             router_logits=router_logits,
         )
@@ -461,6 +463,16 @@ def forward(
             torch.npu.current_stream().wait_stream(self.shared_expert_stream)
         return shared_out, fused_out
 
+    def forward_impl(self, hidden_states: torch.Tensor,
+                     router_logits: torch.Tensor):
+        shared_output = torch.empty(1)
+        fused_output = AscendFusedMoE.forward_impl(
+            self,
+            hidden_states=hidden_states,
+            router_logits=router_logits,
+        )
+        return shared_output, fused_output
+
 
 UnquantizedFusedMoEMethod.__init__ = unquantized_fused_moe_init_func
 UnquantizedFusedMoEMethod.process_weights_after_loading = process_weights_after_loading

vllm_ascend/patch/worker/patch_common/__init__.py

@@ -18,4 +18,3 @@
 import vllm_ascend.patch.worker.patch_common.patch_distributed  # noqa
 import vllm_ascend.patch.worker.patch_common.patch_logits  # noqa
 import vllm_ascend.patch.worker.patch_common.patch_minicpm  # noqa
-import vllm_ascend.patch.worker.patch_common.patch_shared_fused_moe  # noqa

vllm_ascend/patch/worker/patch_common/patch_shared_fused_moe.py

@@ -498,7 +498,8 @@ def register_ascend_customop(vllm_config: Optional[VllmConfig] = None):
 
     from vllm_ascend.models.layers.mla import AscendMultiHeadLatentAttention
     from vllm_ascend.ops.activation import AscendQuickGELU, AscendSiluAndMul
-    from vllm_ascend.ops.common_fused_moe import AscendFusedMoE
+    from vllm_ascend.ops.common_fused_moe import (AscendFusedMoE,
+                                                  AscendSharedFusedMoE)
     from vllm_ascend.ops.layernorm import AscendQuantRMSNorm, AscendRMSNorm
     from vllm_ascend.ops.linear import (AscendColumnParallelLinear,
                                         AscendMergedColumnParallelLinear,
@@ -525,6 +526,7 @@ def register_ascend_customop(vllm_config: Optional[VllmConfig] = None):
         "LogitsProcessor": AscendLogitsProcessor,
         "RMSNorm": AscendRMSNorm,
         "FusedMoE": AscendFusedMoE,
+        "SharedFusedMoE": AscendSharedFusedMoE,
         "MultiHeadLatentAttention": AscendMultiHeadLatentAttention,
     }