[task] Add fused gdn gating triton kernel (#4304)

### What this PR does / why we need it?
This commit introduces a Triton-based fused GDN gating kernel for Ascend
NPU, aimed at improving performance in the Gated Delta Net workflow.
### Does this PR introduce _any_ user-facing change?
It only adds and refactors internal Triton kernels and wrappers for
Ascend. These are backend implementation details. There are no new APIs,
flags, CLI options, or behavior changes visible to end users.
### How was this patch tested?

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

---------

Signed-off-by: Ascendyh <hw7osiris@outlook.com>

vllm_ascend/patch/worker/patch_qwen3_next.py

@@ -35,6 +35,7 @@ from vllm_ascend.ops.triton.fla.fused_qkvzba_split_reshape import \
     fused_qkvzba_split_reshape_cat
 from vllm_ascend.ops.triton.fla.sigmoid_gating import \
     fused_sigmoid_gating_delta_rule_update
+from vllm_ascend.ops.triton.fused_gdn_gating import fused_gdn_gating_patch
 
 
 class AscendQwen3Next_GatedDeltaNet(nn.Module, MambaBase):
@@ -151,7 +152,6 @@ class AscendQwen3Next_GatedDeltaNet(nn.Module, MambaBase):
         # 1. Convolution sequence transformation
         conv_weights = self.conv1d.weight.view(self.conv1d.weight.size(0),
                                                self.conv1d.weight.size(2))
-
         if spec_sequence_masks is not None:
             if attn_metadata.num_prefills == 0 and attn_metadata.num_decodes == 0:
                 mixed_qkv_spec = mixed_qkv
@@ -211,14 +211,18 @@ class AscendQwen3Next_GatedDeltaNet(nn.Module, MambaBase):
             )
         else:
             mixed_qkv_non_spec = None
-
         query_spec, key_spec, value_spec = self.rearrange_mixed_qkv(
             mixed_qkv_spec)
         query_non_spec, key_non_spec, value_non_spec = self.rearrange_mixed_qkv(
             mixed_qkv_non_spec)
 
         if attn_metadata.num_prefills > 0 or spec_sequence_masks is not None:
-            g, beta = fused_gdn_gating(self.A_log, a, b, self.dt_bias)
+            is_cuda_graph = forward_context.cudagraph_runtime_mode != CUDAGraphMode.NONE
+            if (is_cuda_graph):
+                g, beta = fused_gdn_gating_patch(self.A_log, a, b,
+                                                 self.dt_bias)
+            else:
+                g, beta = fused_gdn_gating(self.A_log, a, b, self.dt_bias)
 
             if spec_sequence_masks is not None:
                 if attn_metadata.num_prefills == 0 and attn_metadata.num_decodes == 0: