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vllm-omni/vllm_omni/diffusion/attention/selector.py
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2025-12-05 10:46:20 +00:00

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Python

# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import os
from functools import cache
from vllm.logger import init_logger
from vllm_omni.diffusion.attention.backends.abstract import (
AttentionBackend,
)
from vllm_omni.diffusion.attention.backends.flash_attn import FlashAttentionBackend
from vllm_omni.diffusion.attention.backends.sdpa import SDPABackend
logger = init_logger(__name__)
# environment variable value -> backend class
SUPPORTED_BACKENDS = {
"FLASH_ATTN": FlashAttentionBackend,
"TORCH_SDPA": SDPABackend,
}
@cache
def get_attn_backend(head_size: int) -> type[AttentionBackend]:
"""
Get attention backend for diffusion models.
The backend is selected based on the following priority:
1. DIFFUSION_ATTENTION_BACKEND environment variable (if set, e.g. export DIFFUSION_ATTENTION_BACKEND=FLASH_ATTN)
2. Default backend (SDPA)
Args:
head_size: Head size (currently not used for selection, but kept for API compatibility)
Returns:
The selected attention backend class
"""
# Check environment variable
backend_name: str | None = os.environ.get("DIFFUSION_ATTENTION_BACKEND")
if backend_name is not None:
backend_name_upper = backend_name.upper()
if backend_name_upper not in SUPPORTED_BACKENDS:
valid_backends = list(SUPPORTED_BACKENDS.keys())
raise ValueError(
f"Invalid attention backend for diffusion: '{backend_name}'. Valid backends are: {valid_backends}"
)
logger.info(f"Using attention backend '{backend_name_upper}' for diffusion")
return SUPPORTED_BACKENDS[backend_name_upper]
# Default to SDPA
return SDPABackend