File size: 2,497 Bytes
b66f552 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 | import torch
import triton
import triton.language as tl
from fla.ops.utils import prepare_chunk_indices
@triton.heuristics({
'IS_VARLEN': lambda args: args['offsets'] is not None,
})
@triton.jit(do_not_specialize=['T'])
def parallel_path_fwd_kernel_prepare_k_cache(
k, k_new, w1, w2,
offsets, indices,
T,
H: tl.constexpr,
K: tl.constexpr,
BT: tl.constexpr, BK: tl.constexpr,
IS_VARLEN: tl.constexpr,
):
i_t, i_bh = tl.program_id(0), tl.program_id(1)
i_b, i_h = i_bh // H, i_bh % H
if IS_VARLEN:
i_n, i_t = tl.load(indices + i_t * 2).to(tl.int32), tl.load(indices + i_t * 2 + 1).to(tl.int32)
bos, eos = tl.load(offsets + i_n).to(tl.int32), tl.load(offsets + i_n + 1).to(tl.int32)
T = eos - bos
else:
i_n = i_b
bos, eos = i_n * T, i_n * T + T
k += (bos * H + i_h) * K
k_new += (bos * H + i_h) * K
w1 += (bos * H + i_h) * K
w2 += (bos * H + i_h) * K
# constants
p_k = tl.make_block_ptr(k, (T, K), (H*K, 1), (i_t * BT, 0), (BT, BK), (1, 0))
b_k = tl.zeros([BT, BK], dtype=tl.float32)
b_k += tl.load(p_k, boundary_check=(0, 1))
for k_block_idx in range(i_t + 1, tl.cdiv(T, BT)):
p_w1 = tl.make_block_ptr(w1, (T, K), (H*K, 1), (k_block_idx * BT, 0), (BT, BK), (1, 0))
p_w2 = tl.make_block_ptr(w2, (T, K), (H*K, 1), (k_block_idx * BT, 0), (BT, BK), (1, 0))
b_w1 = tl.load(p_w1, boundary_check=(0, 1))
b_w2 = tl.load(p_w2, boundary_check=(0, 1))
b_A = tl.dot(b_k.to(b_w2.dtype), tl.trans(b_w2))
b_k = b_k - tl.dot(b_A.to(b_w1.dtype), b_w1)
p_k_new = tl.make_block_ptr(k_new, (T, K), (H*K, 1), (i_t * BT, 0), (BT, BK), (1, 0))
tl.store(p_k_new, b_k.to(p_k_new.dtype.element_ty), boundary_check=(0, 1))
def prepare_k_cache_fn(k, w1, w2, cu_seqlens, BS, use_cache=False):
if not use_cache:
return None
else:
B, T, H, K = k.shape
k_new = torch.empty_like(k)
indices = prepare_chunk_indices(cu_seqlens, BS) if cu_seqlens is not None else None
NT = triton.cdiv(T, BS) if cu_seqlens is None else len(indices)
grid = (NT, B * H)
parallel_path_fwd_kernel_prepare_k_cache[grid](
k=k,
k_new=k_new,
w1=w1,
w2=w2,
offsets=cu_seqlens,
indices=indices,
H=H,
T=T,
K=K,
BT=BS,
BK=triton.next_power_of_2(K),
)
return k_new
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