[Mamba] eliminate D2H if tracking mamba states (#20522)

Co-authored-by: hzh0425 <hzh0425@apache.org>

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

@@ -217,6 +217,11 @@ class MambaAttnBackendBase(AttentionBackend):
         else:
             raise ValueError(f"Invalid forward mode: {forward_batch.forward_mode=}")
 
+        has_mamba_track_mask = bool(
+            forward_batch.mamba_track_mask is not None
+            and forward_batch.mamba_track_mask.any()
+        )
+
         return ForwardMetadata(
             query_start_loc=query_start_loc,
             mamba_cache_indices=mamba_cache_indices,
@@ -228,6 +233,7 @@ class MambaAttnBackendBase(AttentionBackend):
             track_ssm_h_dst=track_ssm_h_dst,
             track_ssm_final_src=track_ssm_final_src,
             track_ssm_final_dst=track_ssm_final_dst,
+            has_mamba_track_mask=has_mamba_track_mask,
         )
 
     def init_forward_metadata(self, forward_batch: ForwardBatch):
@@ -613,10 +619,7 @@ class MambaAttnBackendBase(AttentionBackend):
         Note: Conv state tracking for extend is handled separately via gather operations
         using indices computed by `_init_track_conv_indices`.
         """
-        if (
-            forward_batch.mamba_track_mask is not None
-            and forward_batch.mamba_track_mask.any()
-        ):
+        if forward_metadata.has_mamba_track_mask:
             h = h.squeeze(0)
 
             if forward_metadata.track_ssm_h_src.numel() > 0:

python/sglang/srt/layers/attention/linear/gdn_backend.py

@@ -256,6 +256,18 @@ class GDNAttnBackend(MambaAttnBackendBase):
         prefill_backend = get_linear_attn_prefill_backend()
         self.kernel_dispatcher = GDNKernelDispatcher(decode_backend, prefill_backend)
 
+    def init_forward_metadata(self, forward_batch: ForwardBatch):
+        super().init_forward_metadata(forward_batch)
+        if self.forward_metadata.has_mamba_track_mask:
+            self.forward_metadata.mamba_track_mask_indices = (
+                forward_batch.mamba_track_mask.nonzero(as_tuple=True)[0]
+            )
+            self.forward_metadata.conv_states_mask_indices = (
+                forward_batch.mamba_track_indices[
+                    self.forward_metadata.mamba_track_mask_indices
+                ]
+            )
+
     def forward_decode(
         self,
         layer: RadixLinearAttention,
@@ -394,16 +406,13 @@ class GDNAttnBackend(MambaAttnBackendBase):
             mixed_qkv = mixed_qkv_processed.transpose(1, 2).view(seq_len, -1)
         else:
             mixed_qkv = mixed_qkv.transpose(0, 1)
-            if (
-                forward_batch.mamba_track_mask is not None
-                and forward_batch.mamba_track_mask.any()
-            ):
-                conv_dst = forward_batch.mamba_track_indices
+            if forward_metadata.has_mamba_track_mask:
                 mixed_qkv_to_track = mixed_qkv[
                     :, forward_metadata.track_conv_indices
                 ].transpose(0, 1)
-                mask_indices = forward_batch.mamba_track_mask.nonzero(as_tuple=True)[0]
-                conv_states[conv_dst[mask_indices]] = mixed_qkv_to_track
+                conv_states[forward_metadata.conv_states_mask_indices] = (
+                    mixed_qkv_to_track
+                )
 
             mixed_qkv = causal_conv1d_fn(
                 mixed_qkv,

python/sglang/srt/layers/attention/mamba/mamba2_metadata.py

@@ -41,6 +41,10 @@ class ForwardMetadata:
     is_target_verify: bool = False
     draft_token_num: int = 1
 
+    has_mamba_track_mask: bool = False
+    mamba_track_mask_indices: Optional[torch.Tensor] = None
+    conv_states_mask_indices: Optional[torch.Tensor] = None
+
 
 @dataclass(kw_only=True)
 class Mamba2Metadata(ForwardMetadata):