mirror of https://github.com/hpcaitech/ColossalAI
63 lines
1.9 KiB
Python
63 lines
1.9 KiB
Python
from ..base_extension import _Extension
|
|
|
|
|
|
class FlashAttentionNpuExtension(_Extension):
|
|
def __init__(self):
|
|
super().__init__(name="flash_attention_npu", support_aot=False, support_jit=False)
|
|
|
|
def is_available(self) -> bool:
|
|
try:
|
|
import torch_npu
|
|
|
|
return hasattr(torch_npu, "npu_fusion_attention")
|
|
except:
|
|
return False
|
|
|
|
def assert_compatible(self) -> bool:
|
|
pass
|
|
|
|
def build_aot(self) -> None:
|
|
raise NotImplementedError(
|
|
"Flash Attention NPU does not require ahead-of-time compilation. Please use it by installing torch_npu."
|
|
)
|
|
|
|
def build_jit(self) -> None:
|
|
raise NotImplementedError(
|
|
"Flash Attention NPU does not require just-in-time compilation. Please use it by installing torch_npu."
|
|
)
|
|
|
|
def load(self):
|
|
from typing import Optional
|
|
|
|
import torch
|
|
import torch_npu
|
|
|
|
def flash_attention(
|
|
q: torch.Tensor,
|
|
k: torch.Tensor,
|
|
v: torch.Tensor,
|
|
dropout_p: float = 0.0,
|
|
scale: Optional[float] = None,
|
|
attention_mask: Optional[torch.Tensor] = None,
|
|
is_causal: bool = False,
|
|
cu_seqlens_q: Optional[torch.Tensor] = None,
|
|
cu_seqlens_kv: Optional[torch.Tensor] = None,
|
|
max_seqlen_q: Optional[int] = None,
|
|
max_seqlen_kv: Optional[int] = None,
|
|
q_indices: Optional[torch.Tensor] = None,
|
|
kv_indices: Optional[torch.Tensor] = None,
|
|
):
|
|
num_heads = q.size(1)
|
|
return torch_npu.npu_fusion_attention(
|
|
q,
|
|
k,
|
|
v,
|
|
num_heads,
|
|
"BNSD",
|
|
atten_mask=attention_mask.bool(),
|
|
scale=scale,
|
|
keep_prob=1 - dropout_p,
|
|
)[0]
|
|
|
|
return flash_attention
|