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[Multimodal][XPU]Enable vision attn backend for xpu platform (#27525)

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Signed-off-by: Yan Ma <yan.ma@intel.com>
Signed-off-by: Kunshang Ji <kunshang.ji@intel.com>
Co-authored-by: Yejing Lai <yejing.lai@intel.com>
Co-authored-by: Guancheng Fu <110874468+gc-fu@users.noreply.github.com>
Co-authored-by: Kunshang Ji <kunshang.ji@intel.com>
This commit is contained in:
Yan Ma
2025-11-01 12:45:02 +08:00
committed by GitHub
parent 3a5de7d2d6
commit 7e2729b57e
6 changed files with 88 additions and 51 deletions
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84
vllm/_ipex_ops.py
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@@ -270,21 +270,23 @@ class ipex_ops:
@staticmethod
def flash_attn_varlen_func(
out: torch.Tensor,
q: torch.Tensor,
k: torch.Tensor,
v: torch.Tensor,
cu_seqlens_q: torch.Tensor,
seqused_k: torch.Tensor, # we don't support this in ipex kernel
max_seqlen_q: int,
max_seqlen_k: int,
softmax_scale: float,
causal: bool,
block_table: torch.Tensor,
alibi_slopes: torch.Tensor | None,
softmax_scale: float | None = None,
causal: bool = False,
out: torch.Tensor | None = None,
block_table: torch.Tensor | None = None,
alibi_slopes: torch.Tensor | None = None,
window_size: list[int] | None = None,
softcap: float | None = 0.0,
seqused_k: torch.Tensor | None = None,
cu_seqlens_k: torch.Tensor | None = None,
# passed in qwen vl
dropout_p: float = 0.0,
# The following parameters are not used in ipex kernel currently,
# we keep API compatible to CUDA's.
scheduler_metadata=None,
@@ -295,31 +297,63 @@ class ipex_ops:
num_splits=0,
s_aux: torch.Tensor | None = None,
):
if out is None:
out = torch.empty(q.shape, dtype=q.dtype, device=q.device)
real_window_size: tuple[int, int]
if window_size is None:
real_window_size = (-1, -1)
else:
assert len(window_size) == 2
real_window_size = (window_size[0], window_size[1])
return ipex.llm.modules.PagedAttention.flash_attn_varlen_func(
out,
q.contiguous(),
k,
v,
cu_seqlens_q,
seqused_k,
max_seqlen_q,
max_seqlen_k,
softmax_scale,
causal,
block_table,
alibi_slopes,
softcap=softcap,
window_size_left=real_window_size[0],
window_size_right=real_window_size[1],
k_scale=1.0,
v_scale=1.0,
)
if block_table is None:
assert cu_seqlens_k is not None, (
"cu_seqlens_k can't be None when calling varlen_attention."
)
if softmax_scale is None:
softmax_scale = q.shape[-1] ** (-0.5)
ipex_ops.varlen_attention(
q.contiguous(),
k.contiguous(),
v.contiguous(),
out,
cu_seqlens_q,
cu_seqlens_k,
None,
max_seqlen_q,
max_seqlen_k,
0.0,
softmax_scale,
False,
causal,
False,
None,
real_window_size[0],
real_window_size[1],
-1,
)
return out
else:
return ipex.llm.modules.PagedAttention.flash_attn_varlen_func(
out,
q.contiguous(),
k,
v,
cu_seqlens_q,
seqused_k,
max_seqlen_q,
max_seqlen_k,
softmax_scale,
causal,
block_table,
alibi_slopes,
sink=s_aux,
softcap=softcap,
window_size_left=real_window_size[0],
window_size_right=real_window_size[1],
k_scale=1.0,
v_scale=1.0,
)
@staticmethod
def get_scheduler_metadata(