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chore: import upstream snapshot with attribution
2026-07-13 12:38:16 +08:00

67 lines
1.7 KiB
Python

# Adapt from https://github.com/fla-org/flash-linear-attention/blob/main/fla/ops/utils/op.py
# -*- coding: utf-8 -*-
# Copyright (c) 2023-2025, Songlin Yang, Yu Zhang
import os
import triton
import triton.language as tl
import triton.language.extra.libdevice as tldevice
from sglang.srt.layers.attention.fla.utils import is_gather_supported
if os.environ.get("FLA_USE_FAST_OPS", "0") == "1":
exp = tldevice.fast_expf
exp2 = tldevice.exp2
log = tldevice.fast_logf
log2 = tldevice.fast_log2f
else:
exp = tl.exp
exp2 = tl.math.exp2
log = tl.log
log2 = tl.log2
@triton.jit
def safe_exp(x):
return exp(tl.where(x <= 0, x, float("-inf")))
if not is_gather_supported:
@triton.jit
def gather(src, index, axis, _builder=None):
"""
Gather operation that works when tl.gather is not supported.
This is a fallback implementation that returns None.
Just to make triton compiler happy.
"""
return None
else:
gather = tl.gather
if hasattr(triton.language, "_experimental_make_tensor_descriptor"):
# For Triton 3.3.x
make_tensor_descriptor = triton.language._experimental_make_tensor_descriptor
elif hasattr(triton.language, "make_tensor_descriptor"):
# For Triton 3.4.x and later
make_tensor_descriptor = triton.language.make_tensor_descriptor
else:
"""
Fallback implementation when TMA is not supported.
Returns None to indicate TMA descriptors are unavailable.
Just make triton compiler happy.
"""
@triton.jit
def make_tensor_descriptor(
base,
shape,
strides,
block_shape,
_builder=None,
):
return None