limit sgl-kernel causal conv1d to cuda only (#10648)

Co-authored-by: Jinyan Chen <jinyanc@nvidia.com>

python/sglang/srt/layers/attention/hybrid_linear_attn_backend.py

@@ -13,9 +13,6 @@ from sglang.srt.layers.attention.fla.fused_recurrent import (
 from sglang.srt.layers.attention.fla.fused_sigmoid_gating_recurrent import (
     fused_sigmoid_gating_delta_rule_update,
 )
-from sglang.srt.layers.attention.mamba.causal_conv1d import (
-    causal_conv1d_fn as causal_conv1d_fn_sgl,
-)
 from sglang.srt.layers.attention.mamba.causal_conv1d_triton import (
     causal_conv1d_fn,
     causal_conv1d_update,
@@ -26,9 +23,15 @@ from sglang.srt.model_executor.forward_batch_info import ForwardBatch, ForwardMo
 from sglang.srt.model_executor.model_runner import ModelRunner
 from sglang.srt.models.qwen3_next import Qwen3HybridLinearDecoderLayer, fused_gdn_gating
 from sglang.srt.speculative.eagle_utils import EagleDraftInput, EagleVerifyInput
-from sglang.srt.utils import is_npu
+from sglang.srt.utils import is_cuda, is_npu
+
+if is_cuda():
+    from sglang.srt.layers.attention.mamba.causal_conv1d import (
+        causal_conv1d_fn as causal_conv1d_fn_cuda,
+    )
 
-if is_npu():
+    causal_conv1d_fn = causal_conv1d_fn_cuda
+elif is_npu():
     from sgl_kernel_npu.fla.chunk import chunk_gated_delta_rule_npu
     from sgl_kernel_npu.fla.fused_sigmoid_gating_recurrent import (
         fused_sigmoid_gating_delta_rule_update_npu,
@@ -350,7 +353,7 @@ class MambaAttnBackend(AttentionBackend):
                 mixed_qkv_processed.transpose(1, 2).contiguous().view(seq_len, -1)
             )
         else:
-            mixed_qkv = causal_conv1d_fn_sgl(
+            mixed_qkv = causal_conv1d_fn(
                 mixed_qkv.transpose(0, 1),
                 conv_weights,
                 bias,