vllm/vllm/attention/selector.py

93 lines
3.1 KiB
Python

import enum
from functools import lru_cache
from typing import Type
import torch
import vllm.envs as envs
from vllm.attention.backends.abstract import AttentionBackend
from vllm.logger import init_logger
from vllm.utils import is_cpu, is_hip
logger = init_logger(__name__)
class _Backend(enum.Enum):
FLASH_ATTN = enum.auto()
XFORMERS = enum.auto()
ROCM_FLASH = enum.auto()
TORCH_SDPA = enum.auto()
FLASHINFER = enum.auto()
@lru_cache(maxsize=None)
def get_attn_backend(dtype: torch.dtype) -> Type[AttentionBackend]:
backend = _which_attn_to_use(dtype)
if backend == _Backend.FLASH_ATTN:
logger.info("Using FlashAttention-2 backend.")
from vllm.attention.backends.flash_attn import ( # noqa: F401
FlashAttentionBackend)
return FlashAttentionBackend
elif backend == _Backend.XFORMERS:
logger.info("Using XFormers backend.")
from vllm.attention.backends.xformers import ( # noqa: F401
XFormersBackend)
return XFormersBackend
elif backend == _Backend.ROCM_FLASH:
logger.info("Using ROCmFlashAttention backend.")
from vllm.attention.backends.rocm_flash_attn import ( # noqa: F401
ROCmFlashAttentionBackend)
return ROCmFlashAttentionBackend
elif backend == _Backend.TORCH_SDPA:
logger.info("Using Torch SDPA backend.")
from vllm.attention.backends.torch_sdpa import TorchSDPABackend
return TorchSDPABackend
elif backend == _Backend.FLASHINFER:
logger.info("Using Flashinfer backend.")
logger.warning("Eager mode is enforced for the Flashinfer backend. ")
from vllm.attention.backends.flashinfer import FlashInferBackend
return FlashInferBackend
else:
raise ValueError("Invalid attention backend.")
def _which_attn_to_use(dtype: torch.dtype) -> _Backend:
"""Returns which flash attention backend to use."""
if is_cpu():
return _Backend.TORCH_SDPA
if is_hip():
# AMD GPUs.
if torch.cuda.get_device_capability()[0] != 9:
# not Instinct series GPUs.
logger.info("flash_atten is not supported on NAVI GPUs.")
return _Backend.ROCM_FLASH
# NVIDIA GPUs.
if torch.cuda.get_device_capability()[0] < 8:
# Volta and Turing NVIDIA GPUs.
logger.info("Cannot use FlashAttention-2 backend for Volta and Turing "
"GPUs.")
return _Backend.XFORMERS
if dtype not in (torch.float16, torch.bfloat16):
logger.info("Cannot use FlashAttention-2 backend for dtype other than "
"torch.float16 or torch.bfloat16.")
return _Backend.XFORMERS
try:
import vllm_flash_attn # noqa: F401
except ImportError:
logger.info(
"Cannot use FlashAttention-2 backend because the vllm_flash_attn "
"package is not found. `pip install vllm-flash-attn` for better "
"performance.")
return _Backend.XFORMERS
backend_by_env_var = envs.VLLM_ATTENTION_BACKEND
if backend_by_env_var is not None:
return _Backend[backend_by_env_var]
# Default case.
return _Backend.FLASH_ATTN