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[XPU] Fix XPU CI breaks from #41105 (KDA chunk_offsets) and #42588 (int4 test tp_group) #43334

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Merged
mingfeima merged 3 commits into from
Oct 10, 2026
Merged

[XPU] Fix XPU CI breaks from #41105 (KDA chunk_offsets) and #42588 (int4 test tp_group) #43334

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52a762c
[XPU] Accept chunk_offsets in the XPU chunk_gated_delta_rule_fwd_h
arathi-hlab Oct 9, 2026
4ba4d49
Merge branch 'main' into fix/xpu-kda-chunk-offsets
arathi-hlab Oct 9, 2026
c6962d8
[XPU] Fix int4 dense test to set TP size on the layer's tp_group
arathi-hlab Oct 9, 2026
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11 changes: 6 additions & 5 deletions python/sglang/srt/hardware_backend/xpu/kernels/fla/chunk_delta_h.py
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Original file line number Diff line number Diff line change
Expand Up @@ -271,6 +271,7 @@ def chunk_gated_delta_rule_fwd_h(
inplace_update: bool = True,
track_state: Optional[torch.Tensor] = None,
track_chunk_idx: Optional[torch.Tensor] = None,
chunk_offsets: Optional[torch.Tensor] = None,
) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor]:
if not inplace_update:
raise NotImplementedError(
Expand Down Expand Up @@ -298,11 +299,11 @@ def chunk_gated_delta_rule_fwd_h(
if cu_seqlens is None:
N, NT, chunk_offsets = B, triton.cdiv(T, BT), None
else:
N, NT, chunk_offsets = (
len(cu_seqlens) - 1,
len(chunk_indices),
prepare_chunk_offsets(cu_seqlens, BT),
)
# A caller-built chunk_offsets (CUDA-graph capture) must not go through
# prepare_chunk_offsets: its tensor_cache would replay capture-time values.
N, NT = len(cu_seqlens) - 1, len(chunk_indices)
if chunk_offsets is None:
chunk_offsets = prepare_chunk_offsets(cu_seqlens, BT)
assert K <= 256, "current kernel does not support head dimension larger than 256."

h = k.new_empty(B, NT, H, V, K)
Expand Down
12 changes: 6 additions & 6 deletions test/registered/xpu/test_xpu_int4_dense.py
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Original file line number Diff line number Diff line change
@@ -1,10 +1,10 @@
"""Numeric unit tests for the XPU int4 *dense* linear kernels (GPTQ / AWQ)."""

import unittest
from types import SimpleNamespace

import torch

from sglang.srt.runtime_context import get_parallel
from sglang.srt.utils import is_xpu
from sglang.test.ci.ci_register import register_xpu_ci
from sglang.test.test_utils import CustomTestCase
Expand Down Expand Up @@ -196,8 +196,8 @@ def _run_gptq(self, m, k, n, gs, dtype, desc_act, fmt, tp_size=1):
layer.g_idx = torch.nn.Parameter(g_idx, requires_grad=False)

kernel = GPTQXPULinearKernel(_gptq_config(gs, desc_act, fmt))
with get_parallel().override(tp_size=tp_size):
kernel.process_weights_after_loading(layer)
layer.tp_group = SimpleNamespace(world_size=tp_size)
kernel.process_weights_after_loading(layer)
out = kernel.apply(layer, x)

self.assertEqual(tuple(out.shape), (m, n))
Expand Down Expand Up @@ -239,9 +239,9 @@ def test_gptq_act_order_rejects_split_group_shard(self):
(2, r"tp_size=2.*--tp-size 1"),
):
with self.subTest(tp_size=tp_size):
with get_parallel().override(tp_size=tp_size):
with self.assertRaisesRegex(NotImplementedError, pattern):
kernel.process_weights_after_loading(layer)
layer.tp_group = SimpleNamespace(world_size=tp_size)
with self.assertRaisesRegex(NotImplementedError, pattern):
kernel.process_weights_after_loading(layer)

def test_gptq_group_aligned_shard_allows_tensor_parallel(self):
# Whole-group shards stay representable, so TP is only rejected when a
Expand Down
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