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[BugFix][VL] Fix FA selection on Qwen2.5-VL (#27790)

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Signed-off-by: zhewenli <zhewenli@meta.com>
Co-authored-by: Roger Wang <hey@rogerw.io>
This commit is contained in:
Zhewen Li
2025-10-30 00:54:44 -07:00
committed by GitHub
parent 5be1bed790
commit e806178d2a
2 changed files with 20 additions and 12 deletions
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30
vllm/model_executor/models/qwen2_5_vl.py
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@@ -43,10 +43,7 @@ from transformers.models.qwen2_5_vl.configuration_qwen2_5_vl import (
)
from vllm.attention.backends.registry import _Backend
from vllm.attention.layer import (
check_upstream_fa_availability,
maybe_get_vit_flash_attn_backend,
)
from vllm.attention.layer import maybe_get_vit_flash_attn_backend
from vllm.attention.ops.vit_attn_wrappers import (
vit_flash_attn_wrapper,
vit_xformers_attn_wrapper,
@@ -318,6 +315,7 @@ class Qwen2_5_VisionAttention(nn.Module):
use_data_parallel: bool = False,
attn_backend: _Backend = _Backend.TORCH_SDPA,
use_upstream_fa: bool = False,
attn_backend_override: _Backend | None = None,
) -> None:
super().__init__()
# Per attention head and per partition values.
@@ -358,8 +356,14 @@ class Qwen2_5_VisionAttention(nn.Module):
maybe_get_vit_flash_attn_backend(
self.attn_backend,
self.use_upstream_fa,
attn_backend_override=attn_backend_override,
)
)
# On ROCm with FLASH_ATTN backend, upstream flash_attn is used
from vllm.platforms import current_platform
if current_platform.is_rocm() and self.attn_backend == _Backend.FLASH_ATTN:
self.use_upstream_fa = True
self.is_flash_attn_backend = self.attn_backend in {
_Backend.FLASH_ATTN,
_Backend.ROCM_AITER_FA,
@@ -484,6 +488,7 @@ class Qwen2_5_VisionBlock(nn.Module):
use_data_parallel: bool = False,
attn_backend: _Backend = _Backend.TORCH_SDPA,
use_upstream_fa: bool = False,
attn_backend_override: _Backend | None = None,
) -> None:
super().__init__()
if norm_layer is None:
@@ -499,6 +504,7 @@ class Qwen2_5_VisionBlock(nn.Module):
use_data_parallel=use_data_parallel,
attn_backend=attn_backend,
use_upstream_fa=use_upstream_fa,
attn_backend_override=attn_backend_override,
)
self.mlp = Qwen2_5_VisionMLP(
dim,
@@ -698,13 +704,14 @@ class Qwen2_5_VisionTransformer(nn.Module):
dtype=torch.get_default_dtype(),
attn_backend_override=attn_backend_override,
)
if (
self.attn_backend != _Backend.FLASH_ATTN
and self.attn_backend != _Backend.ROCM_AITER_FA
and check_upstream_fa_availability(torch.get_default_dtype())
):
self.attn_backend = _Backend.FLASH_ATTN
use_upstream_fa = True
self.attn_backend, self.flash_attn_varlen_func = (
maybe_get_vit_flash_attn_backend(
self.attn_backend,
use_upstream_fa,
attn_backend_override=attn_backend_override,
)
)
if self.attn_backend not in {
_Backend.FLASH_ATTN,
@@ -730,6 +737,7 @@ class Qwen2_5_VisionTransformer(nn.Module):
use_data_parallel=use_data_parallel,
attn_backend=self.attn_backend,
use_upstream_fa=use_upstream_fa,
attn_backend_override=attn_backend_override,
)
for layer_idx in range(depth)
]