refactor: unify attention mask to single attn_mask tensor

- CudaBackend.fwd_decode passes attn_mask directly instead of kv_cache.decode_mask
- TorchNativeBackend derives pos_mask from attn_mask[:,0,0] on decode
- Drop decode_mask and page_table fields from KVCache and bind_tasks
This commit is contained in:
2026-08-01 15:49:26 +08:00
parent 41dcf0feb9
commit 91acaf4b0b
2 changed files with 7 additions and 29 deletions
-18
View File
@@ -203,10 +203,6 @@ class KVCache:
seq_lens: [batch_size] — per-request total sequence lengths
out_cache_loc: [batch, new_seq_len] or [batch, 1] — write indices
max_len: max(seq_lens) as Python int — avoids GPU sync in decode
page_table: [batch, max_len] — precomputed gather indices for decode;
None for prefill or when not yet computed.
decode_mask: [batch, max_len] bool — precomputed position validity
mask for decode; None for prefill or single-batch decode.
"""
k_buffer: Tensor
@@ -216,8 +212,6 @@ class KVCache:
seq_lens: Tensor
out_cache_loc: Tensor
max_len: int = 0
page_table: Optional[Tensor] = None
decode_mask: Optional[Tensor] = None
class PagePool:
@@ -434,21 +428,11 @@ class PagePool:
out_cache_loc = self._req_pool.req_to_token[
req_pool_indices, start_pos:seq_len
]
page_table = None
decode_mask = None
else:
write_pos = seq_lens_t - 1
out_cache_loc = self._req_pool.req_to_token[
req_pool_indices, write_pos
].unsqueeze(-1)
ml = max(seq_lens)
page_table = self._req_pool.req_to_token[req_pool_indices, :ml]
if len(task_ids) > 1:
decode_mask = (
torch.arange(ml, device=device)[None, :] < seq_lens_t[:, None]
)
else:
decode_mask = None
return KVCache(
k_buffer=self._storage.k_buffer,
@@ -458,8 +442,6 @@ class PagePool:
seq_lens=seq_lens_t,
out_cache_loc=out_cache_loc,
max_len=max(seq_lens),
page_table=page_table,
decode_mask=decode_mask,
)
# ---- internals ----