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[Attention] Refactor CUDA attention backend selection logic (#24794)

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Signed-off-by: Matthew Bonanni <mbonanni@redhat.com>
Signed-off-by: Matthew Bonanni <mbonanni001@gmail.com>
Co-authored-by: Luka Govedič <ProExpertProg@users.noreply.github.com>
This commit is contained in:
Matthew Bonanni
2025-11-11 06:40:44 -06:00
committed by GitHub
parent 2e78150d24
commit b30dfa03c5
61 changed files with 1338 additions and 1002 deletions
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8
tests/v1/spec_decode/test_tree_attention.py
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@@ -10,7 +10,7 @@ from tests.v1.attention.utils import (
create_vllm_config,
try_get_attention_backend,
)
from vllm.attention.backends.registry import _Backend
from vllm.attention.backends.registry import AttentionBackendEnum
from vllm.config import ParallelConfig, SpeculativeConfig
from vllm.v1.attention.backends.utils import CommonAttentionMetadata
@@ -35,7 +35,7 @@ def forward_attention(
block_table: torch.Tensor,
slot_mapping: torch.Tensor,
seqlen_k: int,
backend: _Backend,
backend: AttentionBackendEnum,
spec_token_tree: str | None = None,
num_spec_tokens: int = 0,
) -> torch.Tensor:
@@ -241,7 +241,7 @@ def test_tree_attn_correctness() -> None:
block_table=block_table,
slot_mapping=tree_slot_mapping,
seqlen_k=seqlen_k,
backend=_Backend.TREE_ATTN,
backend=AttentionBackendEnum.TREE_ATTN,
spec_token_tree=spec_token_tree,
num_spec_tokens=tree_size_q - 1,
).view(batch_size, -1, num_heads, dim_per_head)
@@ -278,7 +278,7 @@ def test_tree_attn_correctness() -> None:
block_table=block_table,
slot_mapping=branch_slot_mapping,
seqlen_k=sequence_position + q_len,
backend=_Backend.FLASH_ATTN,
backend=AttentionBackendEnum.FLASH_ATTN,
).view(batch_size, -1, num_heads, dim_per_head)
# Compare the outputs.