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[pref] qwen3_next add triton ops : fused_sigmoid_gating_delta_rule_update (#4818)

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### What this PR does / why we need it?
qwen3_next add fused_sigmoid_gating_delta_rule_update op which fused
fused_gdn_gating+fused_recurrent_gated_delta_rule

- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c

Signed-off-by: wangxiaoxin-sherie <wangxiaoxin7@huawei.com>
Co-authored-by: wangxiaoxin-sherie <wangxiaoxin7@huawei.com>
This commit is contained in:
XiaoxinWang
2025-12-19 16:34:11 +08:00
committed by GitHub
parent 118b0ed346
commit 0cc3fc357f
5 changed files with 539 additions and 1 deletions
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tests/e2e/singlecard/test_fused_sigmoid_gating_delta_rule.py Normal file
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import torch
from vllm.model_executor.layers.fla.ops import fused_recurrent_gated_delta_rule
from vllm.model_executor.models.qwen3_next import fused_gdn_gating
from vllm_ascend.ops.triton.fla.sigmoid_gating import \
fused_sigmoid_gating_delta_rule_update
def test_triton_fusion_ops():
q = torch.randn(1, 1, 4, 128, dtype=torch.bfloat16).npu()
k = torch.randn(1, 1, 4, 128, dtype=torch.bfloat16).npu()
v = torch.randn(1, 1, 8, 128, dtype=torch.bfloat16).npu()
a = torch.tensor([[
-2.6094, -0.2617, -0.3848, 2.2656, 3.6250, -0.7383, -1.0938, -0.0505
]]).bfloat16().npu()
b = torch.tensor(
[[0.4277, 0.8906, 1.6875, 2.3750, 4.1562, 0.3809, 1.0625,
3.6719]]).bfloat16().npu()
ssm_state = torch.randn(1, 8, 128, 128, dtype=torch.bfloat16).npu()
non_spec_state_indices_tensor = torch.tensor([2]).int().npu()
non_spec_query_start_loc = torch.tensor([0, 1]).int().npu()
a_log = torch.tensor([
-2.6875, -3.2031, -3.3438, -2.7812, -3.0625, -4.0312, -5.3750, 5.7188
]).bfloat16().npu()
dt_bias = torch.tensor(
[-4.7812, -5.0938, -5.5000, 9.4375, 7.6250, -4.3750, -3.0938,
0.9688]).bfloat16().npu()
core_attn_out_non_spec_fused = fused_sigmoid_gating_delta_rule_update(
A_log=a_log.contiguous(),
dt_bias=dt_bias.contiguous(),
q=q.contiguous(),
k=k.contiguous(),
v=v.contiguous(),
a=a.contiguous(),
b=b.contiguous(),
initial_state_source=ssm_state,
initial_state_indices=non_spec_state_indices_tensor,
cu_seqlens=non_spec_query_start_loc,
use_qk_l2norm_in_kernel=True,
softplus_beta=1.0,
softplus_threshold=20.0,
)
g, beta = fused_gdn_gating(a_log, a, b, dt_bias)
g_non_spec = g
beta_non_spec = beta
core_attn_out_non_spec_split, last_recurrent_state = (
fused_recurrent_gated_delta_rule(
q=q,
k=k,
v=v,
g=g_non_spec,
beta=beta_non_spec,
initial_state=ssm_state,
inplace_final_state=True,
cu_seqlens=non_spec_query_start_loc,
ssm_state_indices=non_spec_state_indices_tensor,
use_qk_l2norm_in_kernel=True,
))
torch.testing.assert_close(core_attn_out_non_spec_fused,
core_attn_out_non_spec_split,
rtol=1e-02,
atol=1e-02,
equal_nan=True)