[NPU] use causal_conv1d_update_v2 for performance (#24595)

Co-authored-by: iridiumine <iridiumine@users.noreply.github.com>

python/sglang/srt/hardware_backend/npu/attention/ascend_gdn_backend.py

@@ -8,6 +8,7 @@ from sgl_kernel_npu.fla.fused_gdn_gating import (
 from sgl_kernel_npu.mamba.causal_conv1d import (
     causal_conv1d_fn_npu,
     causal_conv1d_update_npu,
+    causal_conv1d_update_v2,
 )
 
 from sglang.srt.hardware_backend.npu.attention.ascend_hybrid_linear_attn_backend import (
@@ -224,9 +225,7 @@ class AscendGDNAttnBackend(AscendMambaAttnBackendBase):
         else:
             has_initial_states = forward_batch.extend_prefix_lens > 0
         if is_target_verify:
-            draft_token_num = forward_batch.spec_info.draft_token_num
             num_token_padding = mixed_qkv.shape[0]
-            batch_size = cache_indices.shape[0]
             if (
                 not self.graph_mode
                 and forward_batch.num_token_non_padded_cpu != num_token_padding
@@ -236,23 +235,24 @@ class AscendGDNAttnBackend(AscendMambaAttnBackendBase):
                 b = b[: forward_batch.num_token_non_padded_cpu]
                 seq_len = forward_batch.num_token_non_padded_cpu
 
-            mixed_qkv_reshaped = mixed_qkv.view(batch_size, draft_token_num, -1)
-            num_accept_tokens = torch.full(
+            batch_size = cache_indices.shape[0]
+            draft_token_num = forward_batch.spec_info.draft_token_num
+            num_accepted_tokens = torch.full(
                 (batch_size,),
                 draft_token_num,
                 dtype=torch.int32,
                 device=mixed_qkv.device,
             )
-            mixed_qkv = torch.ops.npu.causal_conv1d_update(
-                mixed_qkv_reshaped,
-                layer.conv_weights.transpose(0, 1).contiguous(),
-                conv_states,
-                cache_indices,
-                layer.bias,
-                num_accept_tokens,
-                None,
-                layer.activation == "silu",
-                self.pad_slot_id,
+            mixed_qkv = causal_conv1d_update_v2(
+                x=mixed_qkv.view(batch_size, draft_token_num, -1).contiguous(),
+                conv_state=conv_states.contiguous(),
+                weight=layer.conv_weights.transpose(0, 1).contiguous(),
+                bias=layer.bias,
+                activation=layer.activation,
+                conv_state_indices=cache_indices,
+                num_accepted_tokens=num_accepted_tokens,
+                pad_slot_id=-1,
+                validate_data=False,
             ).view(seq_len, -1)
         else:
             mixed_qkv = mixed_qkv.transpose(0, 1)