[PERF] Add conv1d metadata to GDN attn (#25105)

Signed-off-by: Vadim Gimpelson <vadim.gimpelson@gmail.com>

vllm/model_executor/layers/mamba/mamba2_metadata.py

@@ -11,6 +11,7 @@ from vllm.attention.backends.placeholder_attn import (
     PlaceholderAttentionMetadata)
 from vllm.attention.backends.utils import PAD_SLOT_ID
 from vllm.platforms import current_platform
+from vllm.v1.attention.backends.gdn_attn import GDNAttentionMetadata
 from vllm.v1.attention.backends.mamba2_attn import (
     Mamba2AttentionMetadata, _query_start_loc_to_chunk_indices_offsets)
 
@@ -45,8 +46,8 @@ class Mamba2Metadata:
     """
     nums_dict: Optional[dict] = None
     cu_seqlen: Optional[int] = None
-    batch_ptr: Optional[torch.tensor] = None
-    token_chunk_offset_ptr: Optional[torch.tensor] = None
+    batch_ptr: Optional[torch.Tensor] = None
+    token_chunk_offset_ptr: Optional[torch.Tensor] = None
 
 
 def get_platform_metadata_classes() -> tuple[type[AttentionMetadata], ...]:
@@ -117,7 +118,8 @@ def prepare_mamba2_metadata(
 
 def update_metadata(x: torch.Tensor, query_start_loc: torch.Tensor,
                     mamba2_metadata: Union[Mamba2Metadata,
-                                           Mamba2AttentionMetadata]):
+                                           Mamba2AttentionMetadata,
+                                           GDNAttentionMetadata]):
     """
     this is triggered upon handling a new input at the first layer
     """

vllm/model_executor/models/qwen3_next.py

@@ -35,6 +35,7 @@ from vllm.model_executor.layers.linear import (ColumnParallelLinear,
                                                RowParallelLinear)
 from vllm.model_executor.layers.logits_processor import LogitsProcessor
 from vllm.model_executor.layers.mamba.abstract import MambaBase
+from vllm.model_executor.layers.mamba.mamba2_metadata import update_metadata
 from vllm.model_executor.layers.mamba.mamba_mixer2 import (
     mamba_v2_sharded_weight_loader)
 from vllm.model_executor.layers.mamba.mamba_utils import (
@@ -414,6 +415,7 @@ class Qwen3NextGatedDeltaNet(nn.Module, MambaBase):
 
         assert isinstance(attn_metadata, dict)
         attn_metadata = attn_metadata[self.prefix]
+        conv_metadata = attn_metadata
         assert isinstance(attn_metadata, GDNAttentionMetadata)
         has_initial_state = attn_metadata.has_initial_state
         spec_query_start_loc = attn_metadata.spec_query_start_loc
@@ -475,10 +477,15 @@ class Qwen3NextGatedDeltaNet(nn.Module, MambaBase):
 
         # 2.2: process the remaining part
         if attn_metadata.num_prefills > 0:
+            mixed_qkv_non_spec_T = mixed_qkv_non_spec.transpose(0, 1)
+            if conv_metadata.cu_seqlen is None:
+                conv_metadata = update_metadata(mixed_qkv_non_spec_T,
+                                                non_spec_query_start_loc,
+                                                conv_metadata)
             # - "cache_indices" updates the conv_state cache in positions
             #   pointed to by "mamba_cache_params.state_indices_tensor"
             mixed_qkv_non_spec = causal_conv1d_fn(
-                mixed_qkv_non_spec.transpose(0, 1),
+                mixed_qkv_non_spec_T,
                 conv_weights,
                 self.conv1d.bias,
                 activation=self.activation,
@@ -486,6 +493,7 @@ class Qwen3NextGatedDeltaNet(nn.Module, MambaBase):
                 has_initial_state=has_initial_state,
                 cache_indices=non_spec_state_indices_tensor,
                 query_start_loc=non_spec_query_start_loc,
+                metadata=conv_metadata,
             ).transpose(0, 1)
         elif attn_metadata.num_decodes > 0:
             mixed_qkv_non_spec = causal_conv1d_update(

vllm/v1/attention/backends/gdn_attn.py

@@ -50,6 +50,12 @@ class GDNAttentionMetadata:
         Tensor] = None  # shape: [num_prefill_tokens + num_decode_tokens,]
     num_accepted_tokens: Optional[torch.Tensor] = None  # shape: [batch,]
 
+    # The following attributes are for triton implementation of causal_conv1d
+    nums_dict: Optional[dict] = None
+    cu_seqlen: Optional[int] = None
+    batch_ptr: Optional[torch.Tensor] = None
+    token_chunk_offset_ptr: Optional[torch.Tensor] = None
+
 
 class GDNAttentionMetadataBuilder(
         AttentionMetadataBuilder[GDNAttentionMetadata]):

vllm/v1/attention/backends/mamba2_attn.py

@@ -132,8 +132,8 @@ class Mamba2AttentionMetadata:
     # The following attributes are for triton implementation of causal_conv1d
     nums_dict: Optional[dict] = None
     cu_seqlen: Optional[int] = None
-    batch_ptr: Optional[torch.tensor] = None
-    token_chunk_offset_ptr: Optional[torch.tensor] = None
+    batch_ptr: Optional[torch.Tensor] = None
+    token_chunk_offset_ptr: Optional[torch.Tensor] = None
 
 
 class Mamba2AttentionMetadataBuilder(

vllm/v1/attention/backends/short_conv_attn.py

@@ -34,8 +34,8 @@ class ShortConvAttentionMetadata:
     # For causal_conv1d
     nums_dict: Optional[dict] = None
     cu_seqlen: Optional[int] = None
-    batch_ptr: Optional[torch.tensor] = None
-    token_chunk_offset_ptr: Optional[torch.tensor] = None
+    batch_ptr: Optional[torch.Tensor] = None
+    token_chunk_offset_ptr: Optional[torch.Tensor] = None
 
 
 class ShortConvAttentionMetadataBuilder(