[CPU][sgl-kernel] extend_attention_cpu and flash_attn_varlen_func: fix nan for large seq (#22434)

Co-authored-by: Ma Mingfei <mingfei.ma@intel.com>
This commit is contained in:
Chunyuan WU
2026-04-17 13:01:01 +08:00
committed by GitHub
co-authored by Ma Mingfei
parent f0f0148167
commit 6c89214584
4 changed files with 99 additions and 8 deletions
+37 -5
View File
@@ -74,13 +74,33 @@ class TestExtendAttention(CustomTestCase):
start_q, start_kv = end_q, end_kv
return output
def _test_extend_attention_once(self, B, N_CTX, H_Q, H_KV, D, DV, mla=False):
def _test_extend_attention_once(
self,
B,
N_CTX,
H_Q,
H_KV,
D,
DV,
mla=False,
*,
b_seq_len_prefix=None,
b_seq_len_extend=None,
):
dtype = torch.bfloat16
b_seq_len_prefix = torch.randint(1, N_CTX // 2, (B,), dtype=torch.int32)
if mla:
b_seq_len_prefix.zero_()
b_seq_len_extend = torch.randint(1, N_CTX // 2, (B,), dtype=torch.int32)
if b_seq_len_prefix is None:
b_seq_len_prefix = torch.randint(1, N_CTX // 2, (B,), dtype=torch.int32)
if mla:
b_seq_len_prefix.zero_()
else:
b_seq_len_prefix = torch.as_tensor(b_seq_len_prefix, dtype=torch.int32)
if b_seq_len_extend is None:
b_seq_len_extend = torch.randint(1, N_CTX // 2, (B,), dtype=torch.int32)
else:
b_seq_len_extend = torch.as_tensor(b_seq_len_extend, dtype=torch.int32)
b_seq_len = b_seq_len_prefix + b_seq_len_extend
max_len_in_batch = torch.max(b_seq_len, 0)[0].item()
@@ -185,6 +205,18 @@ class TestExtendAttention(CustomTestCase):
self._test_extend_attention_once(4, 1230, 16, 4, 128, 96, is_mla)
self._test_extend_attention_once(1, 9000, 16, 1, 32, 32, is_mla)
def test_extend_attention_large_seq_causal_mask(self):
self._test_extend_attention_once(
B=1,
N_CTX=5001,
H_Q=8,
H_KV=2,
D=64,
DV=64,
b_seq_len_prefix=[0],
b_seq_len_extend=[5000],
)
if __name__ == "__main__":
unittest.main()